Designing Cities for Tsunami Impact Mitigation: Evaluating Physical Planning Using Structural Equation Models in Makassar City, Indonesia

DESIGNING CITIES FOR TSUNAMI IMPACT MITIGATION: EVALUATING PHYSICAL PLANNING USING STRUCTURAL EQUATION MODELS IN MAKASSAR CITY, INDONESIA

FAHMYDDIN ARAAF TAUHID

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2017

To my mother Fatimah, and Father Habuddin To my wife Astuty, my son Reza, Raihan, Rifaat, my daughter Jasmine To my mother and father in-law To our big families in Makassar, thank you for your supports and prayers

ACKNOWLEDGMENTS

I would like to express my sincere gratitude to my Supervisor, Prof. Dr. Christopher

Silver, AICP, for his excellent guidance, kindness and patience to provide me with an academic support for conducting my research. I would like also to thank my committee members Prof.

Pierce H. Jones, PhD, Dr. Kathryn Frank, and Dr. Jocelyn Widmer for their guidance and insight for the past two years. Without the participation of my supervisor and committee members, I would not be able to complete my doctoral program.

My sincere thanks go to the institutions and individuals that provided facilities or generous funding for my doctoral research: Fulbright Scholarships Indonesia and Directorate of

Islamic Higher Education, The Ministry of religious affair of Indonesia, staff of The American

Indonesian Exchange Foundation (AMINEF) in Jakarta Indonesia, Prof. Dr. Phil H. Kamaruddin,

M.A (Directorate General of Islamic Education, The Ministry of Religious Affair of Indonesia),

Dr. Wasilah, ST. MT. (Academic Vice Dean of Science and Technology, Islamic Alauddin

University, Makassar, Indonesia).

I would like to thank all the faculty members and administrators in the College of Design,

Construction, and Planning, University of Florida. I express my gratitude to all Indonesian families and students in Gainesville for their supports and kindheartedness. My high appreciation also to my colleagues Sri Ersina, ST. MT., Mutmainnah, ST. MT., Prof. Baharuddin, S.T.,

M.Arch., Ph.D., Dr. Eng. Ihsan, ST., MT and Dahniar, S.T., M.T. for their supports.

Finally, my deepest thank to my mother, Fatimah B, my father, Habuddin P, for their strong encouragement and moral support during my academic studies. My great thank to my wife Astuti; my son Reza, Raihan, and Rifaat; my daughter Jasmine; my mother in law Tieneke; my brother Faisal, and Fajar; my sisters, Halifah, and Hafnyrika; my brother in law, Iman,

Irawan; my sister in-law, Minda and Wahyuni and the big families in Makassar, Indonesia.

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 8

LIST OF FIGURES ...... 10

LIST OF ABBREVIATIONS ...... 15

ABSTRACT ...... 16

CHAPTER

1 INTRODUCTION ...... 18

Research Objective ...... 25 Research Questions ...... 26 Significance of the Study ...... 26 Context of the Study ...... 27 Analytical Approaches ...... 28 Research Process ...... 29 Expected Output ...... 31 Research Structures ...... 31

2 LITERATURE REVIEW ...... 32

Introduction ...... 32 Natural Disaster: Trend and Impacts ...... 32 Tsunami: Trend and Impacts ...... 44 Tsunami in Indonesia: Nature and Cause ...... 50 Tsunami Risk Level in Indonesia ...... 51 Tsunami History in Indonesia ...... 54 Tsunami in Makassar; Potential and History ...... 59 General Introduction ...... 59 Tsunami Potential ...... 63 Cities and Tsunami Impact ...... 65 Theoretical Aspects of Disaster Management ...... 69 Interdisciplinary Approach for Tsunami Mitigation ...... 73 Spatial and Physical Planning in Indonesia ...... 73 Physical Planning ...... 80 Evaluating Physical Planning ...... 85 Theoretical Gap and Planning Implications ...... 88 Tsunami Impact Mitigation Measures ...... 91 Public Awareness ...... 92 Land Use and Development Regulation ...... 95

Land and Property Acquisition ...... 99 Transportation Plan ...... 100 Environmental Management Plan ...... 101 Housing Strategy ...... 103 Fiscal and Taxation ...... 105 Public Emergency Infrastructure ...... 107 Evacuation ...... 109 Emergency Road Network Plan ...... 112 Transportation Plan ...... 113 Coastal Forest ...... 114 Vital Infrastructure and Critical Facilities ...... 116 Warning Systems ...... 118 Buildings Design and Construction ...... 119 Conceptual Map ...... 119 Statement of the Hypotheses ...... 125

3 THE METHODOLOGY ...... 126

Study Variables ...... 126 Sampling ...... 135 Analysis and Sample Size Calculations ...... 136 Data Collection ...... 137 Survey Construction ...... 137 Survey Administration ...... 138 Statistical Analysis ...... 139 Structural Equation Model ...... 139 Assessment of Measurement Model ...... 139 Assessment of Structural Model ...... 145 Human Subject ...... 146

4 FINDINGS ...... 148

Descriptive Statistics ...... 148 Exogenous Variables ...... 148 Social ...... 149 Economics ...... 152 Environment ...... 154 Infrastructure ...... 156 Endogenous Variable ...... 160 Missing Value Analysis ...... 163 Removing Duplicates ...... 165 Assessment of Measurement Model ...... 166 Confirmatory Factor Analysis ...... 166 Social ...... 166 Economics ...... 169 Environment ...... 171 Infrastructure ...... 173

Tsunami Mitigation ...... 175 Assessment of Structural Model ...... 177 Hypotheses Testing ...... 181

5 DISCUSSIONS, IMPLICATIONS AND LIMITATIONS ...... 184

Discussions ...... 184 Social ...... 184 Economics ...... 185 Environment ...... 186 Infrastructure ...... 187 Tsunami Mitigation...... 188 Implications ...... 189 Theoretical ...... 189 Methodological ...... 189 Policy ...... 190 Limitations ...... 191 Future Research ...... 193

APPENDIX

A INFORMED CONSENT FORM ...... 194

B QUESTIONNAIRE TO RESPONDENTS...... 198

LIST OF REFERENCES ...... 209

BIOGRAPHICAL SKETCH ...... 233

LIST OF TABLES

Table page

2-1 Potential effects of natural hazards on urban areas ...... 33

2-2 Summary of distribution of the pre-tsunami population and tsunami victims as adapted from Rofi et al...... 48

2-3 Land Use Pattern in the Makassar City ...... 62

2-4 Earthquake parameters to generating Tsunami in Makassar Strait ...... 64

2-5 Summary of Comparison Impact of the 2004 Indian Ocean tsunami and the 2011 Great East Japan tsunami ...... 69

2-6 Vital infrastructure ...... 116

2-7 Critical facilities ...... 117

2-8 Variables, dimensions and Indicator for tsunami impact mitigation in Makassar City, Indonesia ...... 120

3-1 Operational Definitions of Study Variables ...... 127

3-2 The Index of goodness of fit ...... 141

4-1 The missing data of Social Variables ...... 149

4-2 The response frequency distribution of Social Variables ...... 150

4-3 The missing data of Economic variables ...... 152

4-4 The response frequency distribution of Economic Variables ...... 153

4-5 The missing data of Environment Variables ...... 154

4-6 The response frequency distribution of Environment Variables ...... 155

4-7 The missing data of Infrastructure Variables ...... 156

4-8 The response frequency distribution of Infrastructure Variables ...... 157

4-9 The missing data of Tsunami Mitigation Variables ...... 160

4-10 The response frequency distribution of Tsunami Variables ...... 161

4-11 Data treatment...... 164

4-12 The result of dataset duplicate ...... 165

4-13 The result of model fit of Social Latent ...... 167

4-14 The result of model reliability of Social Latent ...... 168

4-15 The result of model fit of Economics Latent ...... 170

4-16 The result of model reliability of Environment Latent ...... 170

4-17 The result of model fit of Economics Latent ...... 172

4-18 The result of model reliability of Environment Latent ...... 172

4-19 The result of model reliability of Infrastructure Latent ...... 174

4-20 The result of model reliability of Infrastructure Latent ...... 174

4-21 The result of model fit of Tsunami Mitigation Latent ...... 176

4-22 The result of model reliability of Tsunami Mitigation Latent ...... 177

4-23 The result of model fitness ...... 178

4-24 Hypotheses Testing H1 – H4 ...... 181

LIST OF FIGURES

Figure page

1-1 The existing plates composing Indonesia as adapated from Hall et al. (Source: Hall & Wilson (2000). Journal of Asian Earth Sciences 18 (p. 782, Figure 1) ...... 19

1-2 Tsunami generation, propagation and inundation (Source: National Tsunami Hazard Mitigation Program (U.S.) (2001). Designing for tsunamis: seven principles for planning and designing for tsunami hazards (p.5) ...... 20

1-3 Makassar city location in Indonesia as modified from BAKOSURTANAL (Source: BAKOSURTANAL, 2016. Retrieved from http://www.bakosurtanal.go.id/topographic-map/) ...... 21

1-4 Flow chart of research process ...... 30

2-1 Natural disaster summary 1900-2011 (Source: EM-DAT: The OFDA/CRED International Disaster Database, 2012. Retrieved from http://www.emdat.be/sites/default/files/Trends/natural/world_1900_2011/kefyr1.pdf) ...34

2-2 Disaster impact model as adapted from Lindell. (Source: Lindell, 2013. Disaster studies. Current Sociology Review 61(5-6) (p.799)...... 35

2-3 The macro economic impacts pre and post 2004 tsunami in Aceh, Indonesia (Source: analysis, 2014) ...... 37

2-4 25 countries in absolute or relative values of loss of lives and affected between 1994 –2003 (Source: EM-DAT: The OFDA/CRED International Disaster Database. Retrieved from http://www.em-dat.net, UCL - Brussels, Belgium) ...... 39

2-5 Disaster Risk-Poverty Nexus (Source: Jha & Duyne, 2010. Safer homes, stronger communities: a handbook for reconstructing after natural disasters (p. 343)...... 41

2-6 The tsunami prone-area globally. (Source: Preventionweb, 2017. Retrieved from http://www.preventionweb.net/english/professional/maps/v.php?id=10602) ...... 44

2-7 Tsunami events affecting human populations by decade as modified from Doocy et al. (Source: Doocy S, Daniels A, Dick A, Kirsch TD., 2013. The Human Impact of Tsunamis: a Historical Review of Events 1900-2009 and Systematic Literature Review. PLOS Currents Disasters 1) ...... 46

2-8 Tsunamis-related mortality by tsunami damage, age and gender (Source: Elizabeth Frankenberg, Thomas Gillespie, Samuel Preston, Bondan Sikoki and Duncan Thomas ,2011). Mortality, the family and the Indian ocean Tsunami (p.168, Figure 2) ...... 48

2-9 Subduction process as configured from platetectonics (Source: platetectonics, 2008.Retrieved from http://www.sjvgeology.org/geology/tectonics.html) ...... 50

2-10 Tsunami occurrence probability between 0.5 – 3.0 metres yearly (Source Horspool, N.; Pranantyo, I.; Griffin,J.; Latief,H.; Natawidjaja,DH; Kongko,W.; Cipta,A.; Bustaman,B.; Anugrah,SD; Thio,HK., 2013. A probabilistic tsunami hazard assessment for Indonesia (p.6)...... 52

2-11 Tsunami occurrence probability over 3.0 meters yearly (Source Horspool, N.; Pranantyo, I.; Griffin,J.; Latief,H.; Natawidjaja,DH; Kongko,W.; Cipta,A.; Bustaman,B.; Anugrah,SD; Thio,HK, 2013. A probabilistic tsunami hazard assessment for Indonesia (p.7)...... 53

2-12 Tsunami maximum height every 100 years period (Source Horspool, N.; Pranantyo, I.; Griffin,J. ; Latief,H.; Natawidjaja,DH; Kongko,W.; Cipta,A.; Bustaman,B.; Anugrah,SD; Thio,HK., 2013. A probabilistic tsunami hazard assessment for Indonesia (p.8)...... 53

2-13 Tsunami maximum height every 500-year periods (Source Horspool, N.; Pranantyo, I.; Griffin,J.; Latief,H.; Natawidjaja,DH; Kongko,W.; Cipta,A.; Bustaman,B.; Anugrah,SD; Thio,HK., 2013. A probabilistic tsunami hazard assessment for Indonesia (p.9)...... 54

2-14 The crater of Tambora as adapted from Heinrich Zollinger’s 1847 expedition publication in 1855 (Source: University of Oxford, Bodleian Library Collection) ...... 55

2-15 Pre-and Post 2004 Indian Ocean Earthquake and Tsunami in Banda Aceh, Indonesia (Source: International Charter space and major disaster, 2005. Retieved from https://www.disasterscharter.org/image/journal/article.jpg?img_id=36843&t=141145 4230892) ...... 58

2-16 The geographic position and Map of Makassar City as adapted from The Makassar Municipal Government data map (Source: modified by author based on The Makassar Municipal Government Map, 2014) ...... 60

2-17 The Administration Map of Makassar City as configured from The Makassar Municipal Government data (Source: The Makassar Municipal Government, 2014) ...... 61

2-18 Land Pattern as adapted from The Makassar Municipal Government. (Source: The Makassar Municipal Government, 2005) ...... 62

2-19 The earthquake distribution in the Makassar Strait (As modified from Prasetya, G. S., De Lange, W. P., & Healy, T. R., 2001. The Makassar strait tsunamigenic region, Indonesia. Natural Hazards, 24(3) (p.300, Figure 5) ...... 63

2-20 Makassar position and Earthquake Epicenter Generating tsunami simulation (Source: Baeda, Yasir; Klara, Syerly; Hendra, Hendra; Muliyati, Rita., 2015. Mitigasi Bencana Tsunami di Pantai Losari Makassar, Sulawesi Selatan. Jurnal Penelitian Enjiniring 20 (1) (p.25, Figure 2)...... 64

2-21 Tsunami 0.5-3 m occurrence possibility per 1/50-1/100 year for Makassar City (Source: modified from Horspool, N.; Pranantyo, I.; Griffin,J.; Latief,H.; Natawidjaja,DH; Kongko,W.; Cipta,A.; Bustaman,B.; Anugrah,SD; Thio,HK., 2013. A probabilistic tsunami hazard assessment for Indonesia (p.6)...... 65

2-22 The disaster management cycle (Source: Coppola, 2015. Introduction to International Disaster Management) ...... 71

2-23 Spatial Planning system in Indonesia (source: Hudalah, 2007). Spatial Planning System in Transitional Indonesia 12 (3) (p.294, Figure 1) ...... 78

2-24 The combination of factor analysis, multiple regression analysis, and path analysis to measure variables and latent constructs (source: Byrne, Barbara M., 1998. Structural equation modeling with LISREL, PRELIS, and SIMPLIS: basic concepts, applications, and programming)...... 90

2-25 A logic model of SEM (source: Byrne, Barbara M., 1998. Structural equation modeling with LISREL, PRELIS, and SIMPLIS: basic concepts, applications, and programming) ...... 91

2-26 Downtown redevelopment plan for Hilo, Hawaii using the seven key principles for incorporating tsunami risk into design (Source: Modified from National Tsunami Hazard Mitigation Program (U.S.) , 2001).Designing for tsunamis: seven principles for planning and designing for tsunami hazards (p.27) ...... 96

2-27 The Schematic land use and design regulation of reconstruction plan for Banda Aceh City from coastal area to settlement area. Top: shore area, bottom: ring and relief road (Source: The Study on the Urgent Rehabilitation and Reconstruction Support Program for Aceh Province and Affected Areas in North Sumatra, Japan International Cooperation Agency (JICA), Badan Perencanaan Pembangunan Nasional (Bappenas), and Provincial Government of Nanggroe Aceh Darussalaam, Banda Aceh, 2005)...... 97

2-28 The Schematic land use and design to anticipate the development growth under the tsunami mitigation approach (Source: Spatial Planning of Banda Aceh city, Indonesia for 2009- 2029, 2009) ...... 98

2-29 Map for restriction Zones in Constitucion City, Chili (Source: adapted from MINVU, 2010) ...... 99

2-30 Graphical scheme of environmental protection and mitigation function (Source: Green Coast - the Tsunami Response project of Wetlands, 2005. Retrieved from http://southasia.wetlands.org/WhatWeDo/Allourprojects/tabid/639/mod/601/articleT ype/ArticleView/articleId/10/Green-Coast--the-Tsunami-Response.aspx) ...... 102

2-31 Relocation of housing to designated safety areas (Source: The Current State of Reconstruction in Sendai City, 2012） ...... 104

2-32 Clustered and tower building schematic for evacuation purpose (Source: Designed by Author) ...... 104

2-33 Proposed orientation (Source: Budiarjo, A., 2006. Evacuation shelter building planning for tsunami-prone area; a case study of Meulaboh city, Indonesia) ...... 105

2-34 Avoided orientation (Source: Budiarjo, A., 2006. Evacuation shelter building planning for tsunami-prone area; a case study of Meulaboh city, Indonesia) ...... 105

2-35 An integrated tsunami evacuation shelter system in city of Kochi-shi, Japan (Source: Clouds Architecture Office, 2012) ...... 108

2-36 Raised Road for embankment (Source: The Current State of Reconstruction in Sendai City, 2012) ...... 108

2-37 Vertical and horizontal evacuation plan in Japan (Source: Nagao I., 2005. Disaster Management in Japan, Fire and Disaster Management Agency (FDMA), Ministry of Internal Affairs and Communication, Japan.) ...... 109

2-38 The Hilo City’s tsunami evacuation map (Source: The Multi-Hazard Mitigation Plan, 2017. Retrived from http://apps.pdc.org/tsunami/hawaii/01_Hawaii.pdf) ...... 110

2-39 Map of tsunami damages by Tsunami 2010. Source INE 2010. Inundated area covers 34% of urban area (Source: INE, 2010)...... 112

2-40 The integration emergency road with other mitigation measures (Source: Sendai City, 2011) ...... 113

2-41 Tsunami measurement for reconstruction and mitigation (Source: The Current State of Reconstruction in Sendai City, 2012） ...... 114

2-42 Ikonos imageries of pre-and post the 2006 West Java tsunami shows the role of coastal forest to reduce tsunami at the Pangandaran Beach, Indonesia (Source: CRPS 2006.Retrieved from www.crips.nus.edu.sg)...... 115

2-44 A case of tsunami debris captured by premise forest (Source: Imai, K., A. Hayashi, and F. Imamura, 2012. An investigation for trapping floating objectsduring tsunami due to align trees, J. JSCE, Ser. B2. Coastal Engineering, 68(2)...... 115

2-46 The conceptual map and Hypotheses (Source: Author) ...... 125

3-1 The social measurement model (Source: analysis)...... 142

3-2 The economic measurement model (Source: analysis) ...... 143

3-3 The economic measurement model (Source: analysis) ...... 143

3-4 The infrastructure measurement model (Source: analysis) ...... 144

3-5 The tsunami mitigation measurement model (Source: analysis) ...... 144

3-6 The hypothesized Structural Equation Model (Source: analysis) ...... 145

4-1 Path of Social (t-value) (Source: Output LISREL 8.80 by researcher) ...... 167

4-2 Path of Economics (t-value) (Source: Output LISREL 8.80 by researcher) ...... 169

4-3 Path of Environment (t-value) (Source: Output LISREL 8.80 by researcher) ...... 171

4-4 Path of Infrastructure (t-value) (Source: Output LISREL 8.80 by researcher) ...... 173

4-5 Path of Tsunami Mitigation (t-value) (Source: Output LISREL 8.80 by researcher) ...... 176

4-5 The Structural Model Output (t-value) (Source: Output LISREL 8.80 by researcher) ....179

4-6 The Structural Model Output (standardized solutions) (Source: Output LISREL 8.80 by researcher) ...... 180

LIST OF ABBREVIATIONS

BAPPENAS National Development Planning Agency (Badan Perencanaan Pembangunan Nasional)

DMA Local Disaster Management Agency of Indonesia (Badan Daerah Penanggulangan Bencana/ BPBD)

ECLAC Economic Commission for Latin America and the Caribbean

GOI Government of Indonesia

Kabupaten Regency, the government tiers in local level within provincial area.

Kecamatan District, a subdivision of administrative territory within regency or city

Kelurahan Sub district, a subdivision of administrative territory within Kecamatan

Kota City, categorized as functional urban area or as decentralized city with the same level with regency

LEED Leadership in Energy and Environmental Design

LMA Local Disaster Management Agency of Indonesia

NTHMP National Tsunami Hazard Mitigation Program of USA

RTRWK Regional Spatial Plan in Kabupaten or City Level

RTRWN National Spatial Plan

RDTRK Detail Spatial Plan, for functional area within regency or decentralized city

RTRWP Provincial Spatial Plan

UNISDR United Nations International Strategy for Disaster Reduction

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

DESIGNING CITIES FOR TSUNAMI IMPACT MITIGATION: EVALUATING PHYSICAL PLANNING USING STRUCTURAL EQUATION MODELS IN MAKASSAR CITY, INDONESIA

Fahmyddin Araaf Tauhid

August 2017

Chair: Christopher Silver Major: Design, Construction, and Planning

The geodynamic position of Indonesia puts it as one of the most seismically active areas in the world causing earthquake followed by tsunamis. Nevertheless, integrating mitigation and urban planning is a low-priority issue for Indonesian government. The adoption of Act number

24 of 2007 on Disaster Management bring a new perspective to disaster by having disaster management inserted not only in emergency response context, but also in particular for tsunami impact mitigation.

Indonesia lacks an integrated-system to reduce tsunami impact on urban structural and non-structural components. The incorporation of physical planning and tsunami impact mitigation management could be employed to address potential impacts to enhance disaster mitigation. The problem is whether this integration addresses the local context and problem is suitable for other cities.

This research proposes a systematic scheme to understand the sustainable relationship between physical planning and tsunami impact mitigation on evaluating pre-implementation and by advancing a new interdisciplinary approach between. The study evaluates the physical planning’s latent (unobservable) variables (LVs) and observable variable(s) as identified from

previous research for validity. It is based on structural equation modelling (SEM) to systematically find errors in the planning process. It is proposed that social, economics, environment, and infrastructure variables have a positive impact on tsunami impact mitigation.

An Online questionnaire was sent to 336 selected respondents through email. These respondents were identified from the Makassar City database. The survey had 255 responses or a

75.8% response rate. Structural equation modeling was used to evaluate whether social, economics, environment, and infrastructure variables have a positive impact on tsunami impact mitigation on tsunami impact mitigation programs.

The result showed that there is a positive relationship between economics and infrastructure on tsunami impact mitigation as confirmed with the t-value greater than to 1.96.

The study also found that there is not a positive relationship between social and environment variables on tsunami impact mitigation efforts as indicated by the low value of t-value less than

1.96. The result suggests that urban stakeholders in Makassar need to enhance the people participation in urban planning process for mitigation efforts while also improve the awareness about the tsunami disaster and its impacts.

CHAPTER 1 INTRODUCTION

The world has witnessed numerous natural disasters over the centuries causing enormous negative impacts on human and material assets. This issue is a global concern that is related to the sustainable agenda to improve the quality of life in urban areas for present and future generations (Jenks & Dempsey, 2005). As the world becomes urban, natural disasters exert even greater impacts since cities concentrate people and large-scale infrastructures and properties

(United Nations Population Fund, 2007). The current city sustainability agenda has called for the integration of disaster management mitigation with urban planning policy (Brody, 2003; D. R.

Godschalk, 2003; Preuss, 1982). As a component of urban planning, physical planning is fundamental to achieving this integration because it encompasses non-structural/ social and structural measures such as planning, monitoring, evaluation and revising plans as well as the public participation process (Eldeen, 1980).

Because of the variety of social, economic and environmental factors, the aim of physical planning may be diverse. For instance, the U.S. emphasizes conservation of the natural and built environments while balancing social and economic interests (R. Hu, 2013). Evaluation systems have been developed to measure impacts such as LEED for Neighborhood Development (Kubba,

2012). In contrast, Japan’s physical planning prioritizes reducing the impact of earthquakes, tsunamis and the development of the escape route and resettlement sites for disaster’s victims

(Ranghieri, Ishiwatari, & World Bank, 2014). Japan’s assessment of compact city index (CCI) is one of example of assessing urban compactness of facilities, amenities and disaster management.

However, the approach to physical planning created by these countries may not be applied in Indonesia because of the variances in social, economic and environmental issues. For instance, considering its geodynamic position, the disaster management mitigation must be prioritized to

minimize adverse impacts on communities in tsunami prone areas in Indonesia (James, 2008). The

United Nations data (2005) confirms that the number of lives lost during disasters is three to four times higher in developing countries such as Indonesia than in the developed countries. It is estimated that the number of affected people is 40 times higher in developing countries (Center for Reserach on the Eidemology of Disasters, CRED, 2015).

Indonesia is located at the conjunction of three tectonic plates, namely the Eurasian,

Pacific, and Australian plates (Gaina & Müller, 2007) (Figure 1-1). This geodynamic position puts it seismically active areas, making it prone to earthquake followed by tsunamis.

Figure 1-1. The existing plates composing Indonesia as adapated from Hall et al. (Source: Hall & Wilson (2000). Journal of Asian Earth Sciences 18 (p. 782, Figure 1)

As the result, 150 out of 497 municipalities and regencies in Indonesia are under the threat of tsunamis, with the probability of expected wave height ranging between 0.5 m – 30 m in different regions (Horspool et al., 2014). The risk of tsunamis in areas closest to coastlines are also severe because increasing population leads to densely populated areas, minimal infrastructure and land-use planning, low enforced zoning which enables people to settle in hazard areas, and destruction of natural coastal protection such as mangrove forests (Kodoatie,

2006). Earthquakes followed by tsunamis are the most natural hazard occur in Indonesia. Cannon

et al. (2014) confirms that in Indonesia, earthquakes and tsunamis account for 28 percent of total

disasters (Cannon, T., & Schipper, L., 2014).

A tsunami is described as a series of ocean waves generated by abrupt, large disturbances

of the ocean bottom such as earthquakes (Bryant, 2014)(Figure 1-2). Tsunami is a major hazard

that cause catastrophic loss of life, a large-scale destruction, and lead to major economic loses

especially in urban areas.

Figure 1-2. Tsunami generation, propagation and inundation (Source: National Tsunami Hazard Mitigation Program (U.S.) (2001). Designing for tsunamis: seven principles for planning and designing for tsunami hazards (p.5)

The 2004 Indian Ocean Tsunami caused the death of over 167,000 people in northwestern Aceh

province and cost Indonesia $4.5 billion in GDP of the affected provinces. This tsunami travelled

across the Indian Ocean to India and Sri Lanka caused the death toll to over 250,000 in fourteen

countries (Badan Perencanaan Pembangunan Nasional, Bappenas, 2005).

The City of Makassar, the fourth largest city in Indonesia, function as a main hub city in the eastern part of Indonesia. It is one of Indonesian’s major cities for a distribution and transshipment point for goods from Europe and Asia, and is a regional center of services. The city is located in front of the Makassar Strait strengthening its position as economic center in

Indonesia (Figure 1-3). Yet, according to geological reports, Makassar Strait has been recorded having high frequency of historical tsunami events (Prasetya, De Lange, & Healy, 2001). These have been caused by seismic activities generated by shifting the tectonic plates. These tectonic plates are the Palu-Koro and Pasternostertransform fault zones. This geological composition makes Makassar vulnerable to earthquake and tsunami disaster. Responding to the disaster potential, through physical planning can be used to reduce the future impacts.

Figure 1-3. Makassar city location in Indonesia as modified from BAKOSURTANAL (Source: BAKOSURTANAL, 2016. Retrieved from http://www.bakosurtanal.go.id/topographic-map/)

Responding to the increasing natural disaster particularly tsunami, since 1999 as the

beginning of a democratized governmental system, government of Indonesia (GOI) implemented

a policy of transferring power and funding resources to over 30 provinces and over 400 district

levels. The GOI created the Disaster Management Agencies/ Badan Nasional Penanggulangan

Bencana (BNPB) at the national level, and local disaster management agencies/ Badan Daerah

Penanggulangan Bencana (BPBDs) at the provincial and district level (Give2Asia, 2009). These

provincial BPBDs aims to support disaster management practices in their areas and to provide

technical and operational support in mitigation, preparedness and reconstruction program in the

affected province.

In the past, the Indonesian government considered emergency response and reconstruction program following disaster events as the most important and priority in disaster management. Integrating disaster management and physical planning up front for mitigation was a low-priority (Dahuri, 2007). In addition, limited financial resources, low human capacity, inadequate facilities, and lack of preparedness plans were commonplace (Hadi, 2008; World

Bank, 2011). Furthermore, in the post - 2004 Indian Ocean earthquake and tsunami, The GOI adopted Law Number 24 of 2007 on Disaster Management (Indonesian National Board for

Disaster Management, 2007). The law brought a new perspective to disaster management, calling for management not only as an emergency response context, but also as mitigation especially for tsunami disasters.

Although the Indonesian government has developed and implemented policy and programs to reduce the impact of tsunamis, several studies show that Indonesia still lacks an effective disaster-management process that can work to prevent risky areas from great damage by integrating the environment, economic and social potentials into the management efforts

(Brassard, 2009; Rofi, Doocy, & Robinson, 2006; Strunz et al., 2011). Several studies believe that integrating them is the most effective mean to reduce the damages and losses in the city where people and buildings are concentrated (Lindsay, 1993; Orhan, 2015; Wilkie & Leon,

2014). Incorporating physical planning with a disaster management can be effective key to integrate these potentials (Tobin & Montz, 1997). The life cycle of disaster management particularly in mitigation programs in tandem with the physical planning process and policy ensure adequate planning, monitoring, evaluation and plans revision (Nijkamp, Rietveld, &

Voogd, 1990) as well as a public participation process (Fiskaa, 2005). This merging of disaster

management and planning can be an effective mean since it is a process that takes into consideration of local urban potentials (Habitat, 1995).

The occurrence of natural hazard events cannot be avoided; therefore, impacts can be reduced and minimized through proactive and appropriate planning for these hazards (Coppola,

2015). Several studies classify the mitigation differently based on social, economic and environmental perspective, and types of disaster. Mileti et al. (2005) recommend an array of practices to address the mitigation of disasters, including land use planning, warning systems, engineering and building codes, insurance, new technology, emergency preparedness and recovery (D. S. Mileti & Gailus, 2005). While Emdad et al. (2005) acknowledge local, and regional issues in mitigation, noting that different cultural perspectives are fundamental factor to successful mitigation (Emdad & Ian, 2005).

Despite these different approaches, based upon the approach of the US Federal

Emergency Management Agency/FEMA (1986) and Copolla (2015), risk reduction measures employed to address a hazard's vulnerability or its impacts may be done through structural or nonstructural mitigation (Coppola, 2015; Federal Emergency Management Agency, 1986). These two approaches will be used as the basis for this research. Several methods for reducing the effect of tsunamis have been developed. One set of principles is developed by National Tsunami

Hazard Mitigation Program/ NTHMP (2001) to plan and design for mitigating the impacts in the vulnerable states (Dunbar, Weaver, National Geophysical Data Center, Geological Survey

(U.S.), & National Tsunami Hazard Mitigation Program (U.S.), 2008). These include following; recognizing the community’s risk, avoiding new development in tsunami run-up areas, configuring new development in tsunami run-up areas; designing and constructing new buildings to minimize damage, protecting existing development from losses, taking special precautions in

locating infrastructure and critical facilities; and planning for evacuation (National Tsunami

Hazard Mitigation Program, NTHMP, 2001). As the most frequent country hit by tsunami with one event every 6.7 years (Fumihiko, Noritake, & Yasuo, 2005), Japan also advances its mitigation through integration with physical planning. These measures range from non-structural countermeasures such as effective evacuation, dissemination of tsunami knowledge, land usage planning to structural countermeasure such as seawalls, dike, breakwater, gate, artificial high ground (Sendai City, 2011). Case studies of other cities as example that deal with tsunami impacts will be also discussed in this study. Nevertheless, the different types of mitigation strategies to integrate with planning policy should be in accord with both the local potentials and the vulnerabilities of the exposed cities.

The issue is whether a physical planning and tsunami impact mitigation conform to the local context while also adopting suitable approaches borrowed from other cities. In this context, planning scholars have identified evaluation as tool for assessment. The integration of evaluation in the plan making process is the application of the rational comprehensive model employed by planners since the beginning of the second half of the twentieth century (Oliveira & Pinho,

2010). The evaluation in the planning is complex, based on a variety of method, and taking into account the context, meaning and application (Talen, 1996). To simplify, Talen (1996) has classified the typology for evaluating to include evaluation prior to implementation, evaluation of planning practice, policy implementation analysis, and evaluation of the implementation of plans. The evaluation of planning particularly for physical needs to determine what the impact of pre- or - post implementation on the economy, environment, and urban systems (Zhang & Sun,

2013). To question the standard of physical planning quality while integrated with mitigation program, this research will show that evaluation prior to implementation can be viewed as a

justifiable approach. Beyond this evaluating method, the significance and validity of variables developed can be calculated to improve planning quality.

This research proposes a systematic scheme to understand the poorly defined relationship between physical planning and tsunami impact mitigation through evaluation prior to implementation, and advances a new interdisciplinary field between these two prosses using a structural equation model (SEM) that considers latent (unobservable) variables (LVs) and observable variables from previous research and case studies. It aims to evaluate pre- implementation of physical planning in Makassar city, Indonesia as a mean to mitigate tsunami impacts and improving the planning process for sustainable urban development.

Research Objective

The general objective of this research is to understand the role of tsunami mitigation efforts to reduce the impact in urban areas. More specifically, this research aims to evaluate developed variables/ indicators prior to implementation of physical planning for tsunami impact mitigation in Makassar city, Indonesia. The research analyzes and seeks to:

1. Review concepts and theories regarding to tsunami impact mitigation;

2. Identify the impact of tsunami disasters on cities in Indonesia;

3. Describe Indonesian urban planning system particularly its physical planning related to tsunami mitigation program;

4. Construct and confirm a structural equation model (SEM) of the evaluation of physical planning;

5. Score a set of latent (unobserved) variables (LVs) and manifest (observable) variables (OVs) of the statistical model;

6. Examine reliability of the statistical model;

7. Discuss the result findings for improvement, validity and critique.

Research Questions

To operationalize the research objective of this study, the following specific research questions will be addressed:

1. What is the role of social variable to influence the level of planning policy implementation for tsunami impact mitigation?

2. What is the role of economic measures to determine the level of planning policy for tsunami impact mitigation?

3. How does environmental resources have a positive impact on the planning policy implementation for tsunami impact mitigation?

4. How does infrastructure contribute to planning policy implementation for tsunami impact mitigation?

Significance of the Study

Makassar is susceptible to tsunamis that may cause significant property damage and loss of life. Its geographical position and geological composition makes Makassar city is vulnerable to earthquake and tsunami disasters (Prasetya et al., 2001). Several tsunamis have been recorded on the Makassar straits including in 1820 (Harris, 2016), December 1927, April 1967, February

1969, January 1984 (Baeda, 2011), that several devastating Makassar and its surrounding area.

As the fourth largest city in Indonesia and a main hub city in the eastern part of Indonesia for the distribution and transshipment of international goods, the frequency of tsunami may threaten the safety of Makassar’s residents and interrupt its economic activities. While this tsunami hazard impends it, there has not been significant emphasis on how to manage resources for minimizing the impact of Tsunami. Responding to it, physical planning assessment can be viewed as mean for reducing impacts. Therefore, this research aims to contribute to the efforts of fulfilling this need.

Context of the Study

Cities are high vulnerable to the threat of natural hazards impacting their development considering the complexity of their system (P. R. Berke, 1995; D. Mileti, 1999; D. S. Mileti,

Darlington, Passerini, Forrest, & Myers, 1995). Because the population and physical size of cities grow, the risk vulnerability increase more substantial (Paton et al., 2008). The growing population in almost all world’s cities have amplified the urbanization effect. Governments and urban stakeholders have made many endeavors to minimize the impacts of disaster by developing measures to address and mitigate their impacts.

The tsunami is the one of the deadliest catastrophes for waterfront cities showing a substantial rise in the number of people impacted and the occurrences since the mid-1990s

(Adikari & Yoshitani, 2009). The growing number of affected is caused by increasing urbanization due to economic growth especially in developing countries (Adikari & Yoshitani,

2009). The direct social and economic impacts by tsunamis in cities touch employment, the balance of trade and foreign indebtedness, and funds intended for recovery and reconstruction efforts. Nevertheless, tsunami-prone cities may reduce their impact by employing appropriate mitigation strategies. Choosing the suitable mitigation policy can be complicated since there are many available alternatives to be integrated within a local setting. Despite these challenged, mitigation can be viewed as the “cornerstone of disaster management” (Federal Emergency

Management Agency, FEMA, 1995). It aims to minimize the effect of disaster before a disaster ever occurs rather than a reaction after the hazard.

Mitigation efforts usually do not operate as intended due to the political, economic, and social variables that may change (Coppola, 2015). Bringing mitigation programs in public discussion is a challenge since the political will may be absent, and the community’s attention tends to put mitigation lower on the public agenda due to a lack of awareness and education

(Coppola, 2015). One strategy to deal with these hurdles is to integrate mitigation aspects with ongoing urban planning processes. Still, it poses a challenge to city government to systematically evaluate the validity of disaster mitigation infusion into physical planning. Although disaster mitigation can be an essential component of physical planning, this relationship has rarely been discussed in the literature (Kuroiwa, 1988).

In this context, focusing on disaster management through mitigation, the quality of the physical planning, effectiveness and sustainability of implementation can provide a baseline to understand the strong relationship between tsunami disaster mitigation and physical planning policy for urban community disaster resiliency.

Analytical Approaches

The respondents that are identified in the Data of Makassar City have been surveyed. The purpose of the survey instrument was to assess pre-physical planning implementation by identify and validate different variables on tsunami impact mitigation. The survey instrument was designed and distributed by combining the web-based survey tool QUALTRIC and fieldwork to

336 respondents. The URL links of the survey questionnaire were emailed to potential respondents. Responses from participants were analyzed in SPSS version 23 to acquire descriptive statistics to conduct data cleaning, and to identify multicollinearity problems. Then those were processed by LISREL for multivariate analyses. LISREL version 8.7 is used for building and validating measurement models for the latent constructs and to analyze the covariance structure model.

Research Process

Research Aims

Research Questions

Significance of the Study Background: Defining research problems. Context of the Study

Analytical Approaches

Expected Outputs

Research Structure

Tsunami disaster and Disaster Management

Tsunami exposure to Indonesia and Makassar city

Evaluating the physical Review planning for disaster mitigation

Urban and Physical Planning in Indonesia for tsunami mitigation

Tsunami impact mitigation measures

Analysis method: descriptive, appraising and synthesis of data for integrating the physical planning and tsunami impact mitigation plan Literature Review

Case Studies:

Hilo City, Hawaii, USA

Sendai City, Miyagi Japan

Constitution City, Maule Chile

Comprehensive set of evaluation indicators to success of integration

Concept map for developing latent (observable) variables (LVs) and observable variable(s) for SEM Model

Developing questionaries’ based on concept map, testing for validation

Distributing questionaries’ to 336 respondents and analysis collected Research Design & Method data using SPSS 23 for descriptive statistic

Developing SEM/ Structural Equation Model using LISREL 8.7 based on descriptive statistical analysis to evaluate pre- implementation physical planning policies integrating tsunami mitigation variables

Presents the study findings with results of data analyses, Results obtained from measurement model and structural tables, and figures. model are interpreted

The current status of the research, its significance to physical Summarizing planning practice and theories, critiques, limitations that should be addressed for the future research and policy implications of this research.

Conclusion and Discussion

Figure 1-4. Flow chart of research process

Expected Output

This research proposes a systematic scheme to understand the poorly defined relationship between physical planning and tsunami impact mitigation by evaluating and advancing a new interdisciplinary field that links them. This is possible by using a structural equation model

(SEM) set by latent (unobservable) variables (LVs) and observable variables synthesizing from previous research and case studies.

Research Structures

To address the aims of research systematically, this dissertation is structured as follow:  Chapter 1. Provides an introduction and justification to the research and problem, and puts forward the research objectives, research questions, significance of the study, context of the study, analytical approaches, research process, expected outputs and research structures;

 Chapter 2. Reviews the theory and current knowledge related to the theories and research regarding to disaster impact particularly tsunami and disaster management, the nature and history of tsunami in Indonesia and Makassar, the impact of tsunami in cities, theoretical aspect of disaster management, interdisciplinary approach for tsunami mitigation, evaluating method and theoretical gap between tsunami impact mitigation and physical planning, tsunami impact mitigation measures, and hypotheses.

 Chapter 3. Describes the methodology that is used in conducting this research. It explains the research design, data gathering methods, sampling, data analysis tools, and the other processes utilized to conduct the research in the case study area of Makassar city, South Sulawesi Province, Indonesia;

 Chapter 4. Presents the research findings with results of data analyses, tables, and figures. Results obtained from confirmatory factor analysis and covariance structure models are presented and interpreted in this section;

 Chapter 5. Summarizes the current status of the research, its significance to physical planning practice and theories, critiques, limitations that should be addressed for the future research and policy implications of this research.

CHAPTER 2 LITERATURE REVIEW

Introduction

This chapter reviews the literature on current knowledge related to the theories and research regarding to nature, history, impacts and mitigation effort of tsunami. The literature review of the natural disasters and their impact to cities also reviews disaster management as an effort to reduce the damage and loss especially caused by tsunami. This section also discusses research in evaluating physical planning for disaster mitigation particularly in Indonesia. Next, theories that inform the study of tsunami impact mitigation are presented. It also sketches an analytical framework to explain the relationships among various components of mitigation to reduce disaster impacts and how these components impact each other. Also, it identifies the theoretical gaps in disaster mitigation strategies and physical planning. The final part of this chapter presents the conceptual model that depicts the mitigation variables of tsunami mitigation impact and their relationship to physical planning.

Natural Disaster: Trend and Impacts

Disasters are common phenomena over the existence of human. It greatly influenced the rise and fall of civilization (Reilly, 2009). Since the number of events has increased significantly making the risk of disasters a worldwide concern (Reilly, 2009). United Nations International

Strategy for Disaster Reduction/ UNISDR (2009) defines disaster as “a serious disruption of the functioning of a community or a society involving widespread human, material, economic or environmental losses and impacts, which exceeds the ability of the affected community or society to cope using its own resources”. Disasters can take many different forms, and with any different durations. Based on their natural origins, disasters can be generally classified into two groups; natural and man-made disaster. United Nations International Strategy for Disaster

Reduction/ UNISDR (2009) describes “natural disaster” as the natural process or phenomenon that may cause loss of life, injury or other health impacts, property damage, loss of livelihoods and services, social and economic disruption, or environmental damage. The level of impacted to community can vary based on community’s resilience. The escalation of severe natural disaster events can pose a substantive risk to sustainable development (Table 2-1).

Table 2-1. Potential effects of natural hazards on urban areas Social or Human effect Physical effect Economic effect Primary Fatalities Ground Interruption of business due effects to damage to buildings and infrastructure Injuries Deformation and loss of Loss of productivity ground quality workforce through fatalities, injuries, and relief efforts Loss of income or Collapse and structural Capital cost of response and employment damage to building and relief opportunities, infrastructure homelessness Non-structural damage loss of Disease or permanent ground quality to buildings disability and infrastructure

Secondary Psychological impact of Progressive deterioration of Loss of markets and trade effect injury, bereavement, damaged buildings and opportunities through short- shock infrastructure which are not term business interruption repaired Loss of social cohesion Loss of confidence by due to disruption of investors, withdrawal of community investment

Public unrest when government response is inadequate Source: Casale, Riccardo, Margottini, Claudio (Eds.) (2004). Natural Disasters and Sustainable Development.

It is estimated that within the last four decades, natural disasters have caused more than

3.3 million deaths and 2.3 trillion dollars in economic disruption (World Bank & United

Nations., 2010). This trend shows the rising occurrence in natural disasters from 1900 – 2011 with a slight reduction after 2000 onward and increasing impacts affecting world’s population

and monetary damage (Figure 2-1). Natural disasters are also being less deadly globally. Yet, they more caused a greater financial impact especially in developed countries (Harrison &

Williams, 2016). Despite the reduction of the global death toll trend, the mean annual death toll based on developing and developed nation class shows the opposite finding (Cater, 1998). For instance, the mean yearly death tolls caused by natural disasters decreased over 75 percent in developed countries like Japan and the United States from the 1960s through the 1980s, but rose significantly by over 400 percent in developing countries such as Kenya and India in the same period (P. R. Berke, 1995)

Figure 2-1. Natural disaster summary 1900-2011 (Source: EM-DAT: The OFDA/CRED International Disaster Database, 2012. Retrieved from http://www.emdat.be/sites/default/files/Trends/natural/world_1900_2011/kefyr1.pdf)

The rising of cost of damages and losses caused by natural disaster have made disaster management to become an important component of agenda of affected countries, multilateral and bilateral agencies, NGOs, and other stakeholders (M. Lindell, Prater, & Perry, 2006; United

Nations International Strategy for Disaster Reduction,ISDR, 2002). Many studies have been carried out to research the natural disasters and their impacts encompassing social, economic,

and political aspects in order to develop suitable policies, strategies and methods (M. Lindell et al., 2006; M. K. Lindell & Prater, 2003; World Health Organization, 1992).

One famous study is the “Disaster impact model” (M. K. Lindell, 2013) (Figure 2-2).

M.K Lindel (2013) argues that the impact of natural disasters is influenced by three pre-impact conditions including hazard exposure, physical vulnerability, and social vulnerability; and by three specific conditions including hazard event characteristics, improvised disaster responses, and improvised disaster recovery. It further notes that hazard event characteristics and improvised disaster responses link with pre-impact conditions to create a disaster’s physical impacts. These physical impacts, sequentially, integrate with recovery efforts to create a disaster’s social impacts. Vulnerable inhabitants can use three types of emergency management interventions to lessen these impacts. Physical impacts can be reduced through mitigation programs and emergency preparedness practices, while social impacts can be lessened by recovery preparedness programs.

Figure 2-2. Disaster impact model as adapted from Lindell. (Source: Lindell, 2013. Disaster studies. Current Sociology Review 61(5-6) (p.799).

Measuring the macro-economy impact caused by natural disaster with variation of socio, economy and environment structure is challenging because of information scarcity and diverse concepts (Noy, 2009). The European Commission for Latin America and the Caribbean’s

(ECLAC) research assessing the macro-economic impacts have been widely discussed because it provides a comprehensive evaluation of direct damages (fixed assets, capitals and inventories, raw materials, and expenditure on relief and emergency response), indirect damages and flow losses (increase operational expenditure, losses of income etc.) and secondary effects ( macro- economic variables brought such as adjustment in national revenue and expenditure related to tangible and intangible asset) (Zapata-Marti, 1997).

There are many close relations between those types of damages and losses. For instance, direct damages that occur during the natural disaster will result in further disaster impacts on indirect losses that contribute to triggering a secondary effect during the recovery and reconstruction phase that can cause pre-condition for the next disaster vulnerability. Using the research of ECLAC, it was estimated that The Aceh’ Gross Regional Domestic Product and economic structure changed significantly from 2003 onward. The significant decrease of performance of the sub-sectors of oil and gas and other related industries since 2003 continued, while other economic sectors such as construction, trade, transport and service sectors began to rise even before the tsunami and continued to rise as a result of reconstruction effort (Figure 2-

3). The macro analysis became the basis for the GOI when budgeting spending, and making policy decisions particularly in reconstruction and rehabilitation in Aceh (Badan Perencanaan

Pembangunan Nasional, Bappenas, 2005).

Figure 2-3. The macro economic impacts pre and post 2004 tsunami in Aceh, Indonesia (Source: analysis, 2014)

However, a natural disaster does not always affect the macro-economic conditions of the affected countries. Cavallo et al. (2013) combined information from comparative case studies and compute the counterfactual by constructing synthetic controls. This study finds that only tremendously and large-scale disasters have a negative effect on macro-economic output in the short, mid and long periods.

The impacts of natural disasters not only have human and economy aspect but also environmental dimension. Natural disasters and environmental degradation create considerable problems particularly in developing countries. They are closely linked, but only few studies are conducted to reveal their interaction and impact (Tran & Shaw, 2007). It is important to assess this relationship since it may create an ongoing disaster. For instance, deterioration in the

environment by natural disasters, and inappropriate development program for restoration can contribute substantially to rising poverty which in turn, adds to the exposure of environmental systems, which in turn further increasing disaster losses. Since the environment is a complex, studies to assess the natural disaster impact on environment requires more attention for the following reasons; (1) not all-natural disasters result in substantial environment of impacts particularly in ecosystem. For instance, many earthquakes may have only slight impacts on ecosystems; (2) several extreme disasters may contribute positive impacts on environment. For example, floods may rejuvenate floodplain vegetation and play important role in ecological processes; and, (3) these impacts are largely nonmarket and therefore extraordinarily difficult to quantify (Costanza et al., 1998; Renaud, Sudmeier-Rieux, Estrella, & ebrary, 2013; Smith,

2004).

Studies to assess the impact of natural disaster on affected countries have given us a perspective that the acknowledgement of effects comprehensively must be put first. Poor knowledge of the resulting damages and losses in social, economic, and environment aspects may hinder development and implementation of effective disaster mitigation policies. Yet, since this impact must be well recognized, the acknowledgement how various countries are affected must be addressed. Despite the natural disasters are turning less deadly, developing countries may be arguably the most affected from all aspects than developed ones.

The comparison of impact in developing and develop countries shows a sharp contrast.

The countries with low or medium income and a low grade on The Human Development Index are the most severely affected (Planitz, 2007). Unfortunately, almost 80 percent natural disasters occurred in developing nations (D. Alexander, 1991). This high incidence contributes to the high number of people both affected and killed in 25 developing nations between 1994 -2003 (Figure

2-4). For instance, the Indian Ocean tsunami in December 2004 caused more than 200,000 people dead, and another 100,000 missing (Beppenas, 2006).

Figure 2-4. 25 countries in absolute or relative values of loss of lives and affected between 1994 –2003 (Source: EM-DAT: The OFDA/CRED International Disaster Database. Retrieved from http://www.em-dat.net, UCL - Brussels, Belgium)

The analysis data of EM-DAT suggests the correlation between income levels and death tolls. Mortality per 1,000 population in developed countries is 1, while in developing countries it is 69 per 1,000 (D. Alexander, 1993). On average, the number killed by natural disasters in developing countries is over a three time higher (332 deaths) per year as compared to the developed ones (105 deaths) per year. Taken together, developed countries experienced 56% of disasters but lost only 32% of lives. In contrast, developing countries experienced only 44% of disasters but suffered 68% of deaths (Center for Reserach on the Eidemology of Disasters,

CRED, 2015). Another study reports that the mean yearly death tolls caused by natural disasters decreased by over 75 percent in developed nations such as Japan and the United States between the 1960s and the 1980s, but in contrast, increased significantly by over 400 percent in developing countries like Kenya and India in the same period (P. R. Berke, 1995). These data show that levels of economic development, rather than exposure to hazards per se, are major factors of mortality rate.

Yet, the wide gap is in the number of affected people, that is estimated over 40 times higher in developing countries (Center for Reserach on the Eidemology of Disasters, CRED,

2015). For instance, in total numbers, the USA and China experienced the most natural disasters between 1994 and 2013, due to size, landmasses variety and high population densities.

Nevertheless, using the standardized data, Eritrea and Mongolia were the worst-affected countries in the world reflecting the numbers of people affected per 100,000 population (Center for Reserach on the Eidemology of Disasters, CRED, 2015). In the terms of economic losses,

East African countries like Ethiopia, Mozambique, Sudan, Tanzania and Uganda suffered economic losses more than 20 percent of their GNP during the 1980s, while in contrast from the

1992 Hurricane Andrew disaster in South Florida only affected undetectable proportion of

USA’s GNP (P. R. Berke, 1995).

Research to find the cause and impact of natural disasters on communities in developing nations has been intensively studied from various views. Mileti et al. (1995) view the losses from natural disasters as the result of unsustainable development caused by lack of land use planning’s regulation and employment, insufficiency of basic needs, and degradation of environment (D. S. Mileti et al., 1995). In the long run, land use planning needs to be integrated with disaster mitigation approach due to the massive destruction, damages and losses in affected developing countries (P. Berke & Smith, 2009).

The natural disaster impact on developing countries further may cause a cycle of losses, poverty traps and undermine efforts to lessen poverty (Skoufias, 2003). Poverty is therefore both a cause and consequence of natural disaster impacts (P. Blaikie, Cannon, Davis, & Wisner, 2004)

(Figure 2-5). In the view of Berke (1995), poverty in developing nations is believed as primary cause of vulnerability to natural hazard.

Figure 2-5. Disaster Risk-Poverty Nexus (Source: Jha & Duyne, 2010. Safer homes, stronger communities: a handbook for reconstructing after natural disasters (p. 343).

The effect on social and economic in such affected regions are also aggravated by pre- conditions including low human productivity, inadequate public infrastructure, under-exploited resources, as well as marginalization of public participation (Jeffrey, 1982), under development conditions, and rapidly expanding population (P. R. Berke, 1995). These pose severe obstacles to the ability to cope with natural disasters. The economic condition of developing countries creates the tendency to allocate resources to responding, rather than to mitigation and preparedness efforts (Aleskerov, Say, Toker, Akin, & Altay, 2005). The lack of support from institutions and adopted policy to integrate mitigation to reduce future losses and human suffering can be viewed as the main factor increasing vulnerability (P. R. Berke, 1995)

Ayala (2001) believes that in most cases, the high occurrence of natural disasters in developing countries links to two main factors. Firstly, it is the result of the transformation of geophysical setting by the human system (human vulnerability). When these vulnerabilities synchronize in space and time, natural disasters may occur. Secondly, it relates to the historical development, where the social, economic, cultural and political system did not function well due to low human resources, corruption, and undemocratic political system causing high vulnerability to natural disasters (economic, social political and cultural vulnerability)

(Alcántara-Ayala, 2002). Given these cause and impact data, it can be concluded that in reducing vulnerability to natural disaster, improved economic development can be a key contributor.

However, since a natural disaster, and its impact can be complex, other factors such as; educational accomplishment, greater public participation, and more democratic and effective government system can also significantly reduce the negative effects (Escaleras, Anbarci, &

Since natural disaster have multiple consequences, several arguments emphasize the opportunities particularly for developing countries. Some studies claim that the natural disaster, despite the widespread damages and losses they leave, may spur economic growth (Kellenberg &

Mobarak, 2011; Porfiriev, 2016; Toya & Skidmore, 2007). Reconstruction programs can serve as a short-term economic boost by attracting resources, increasing GDP in the immediate term

(Toya & Skidmore, 2007), and allow more efficient development of public and private infrastructure which in turn produce a more productive economy in the long term (Kellenberg &

Mobarak, 2011). Skidmore & Toya (2002) found a strong correlation between natural disasters and economic growth in the long period. They concluded that such economic growth is the result of capital stock accumulation, human capital accumulation, and improvements in technological capacity. Despite the destruction of capital assets, natural disasters can increase the return to human capital relative to investment capital and elevate productivity using new technologies for productivity.

Other opportunity from a social vantage point bring benefits to affected areas in developing countries. These benefits include strengthening local organizational capacity for facilitating social, economic, and physical development in the affected urban areas (P. R. Berke,

1995). Within this scheme, external aid can be allocated to improve local organizations capacity for being more effective in implementing sustainable-development program for disaster resilience. This view regards aid recipient as active participants with assets that can define their own goals and controls development particularly in reconstruction efforts rather than only recipient.

In view of the disproportionate burden of natural hazards in lower-income countries, and consideration of the scale damages and losses, identifying the strategies, methods and policies for disaster management mitigation is crucial to the research especially in urban planning.

Tsunami: Trend and Impacts

The massive impact of natural disasters provides further evidence of the need for government and other stakeholders to be aware of strategies that acknowledge the mitigation of consequences, reduce the vulnerability as well as the main causes as stressed in the post-2015

Hyogo Framework for Action (HFA) process (United Nations International Strategy for Disaster

Reduction, UNISDR, 2007). In this context, tsunamis must be examined due to their massive destruction and high number of death tolls that could be only reduced by effective mitigation plan. Most of the coastal cities in Asia continent are vulnerable to tsunamis and so do the cities on the western coast of the two American continents. This high vulnerability is caused by the 90 percent of world earthquakes that occur in the along the Pacific Ring of Fire, a belt that spans from Asia and Americas' Pacific coast (Figure 2-6) affecting 76 countries and territories with varying damages and losses values (Lovholt et al., 2012).

Figure 2-6. The tsunami prone-area globally. (Source: Preventionweb, 2017. Retrieved from http://www.preventionweb.net/english/professional/maps/v.php?id=10602)

The devastating 2004 Indian Ocean tsunami has been a milestone for government and other stakeholders to increase responsiveness to the destructing capabilities of tsunamis. During the year of 1990s, fourteen major tsunami events hit coastlines in the Pacific Ocean making scientists and public only more aware that the tsunami hazard is more likely occur within this ocean areas (Bryant, 2014).

These perceptions changed considerably after December 26, 2004 when one of the largest earthquakes in modern history occurred in centered off the coast of Aceh northern Indonesia, generated a tsunami that swept over the northern Indian Ocean leaving hundreds of thousands in death and tremendous destructions. This disastrous tsunami made people aware that many high vulnerable areas in the Indian Ocean lack early warning systems, capacity to coping (Satake,

Okal, & Borrero, 2007), evacuation system (Mas et al., 2015) and other deficiency of mitigation measure while also having different geophysical characteristic (Poisson, Oliveros, & Pedreros,

2011).

The record of event shows that there were 94 destructive tsunamis occurred between

1900 and 2009. This frequency was relatively constant from 1900s to 1980s (Figure 2-7).

However, tsunamis rose exceptionally after 1980s as the result of advancement to monitoring and reporting technology (Doocy, Daniels, Dick, & Kirsch, 2013) and the increasing population in coastal cities (Bryant, 2014).

Figure 2-7. Tsunami events affecting human populations by decade as modified from Doocy et al. (Source: Doocy S, Daniels A, Dick A, Kirsch TD., 2013. The Human Impact of Tsunamis: a Historical Review of Events 1900-2009 and Systematic Literature Review. PLOS Currents Disasters 1)

Tsunami frequency, damages, losses and mortality mostly occurred in the Western

Pacific, Southeast Asia, and Americas areas, represents nearly one-third of the events and loss of lives. Nevertheless, Southeast Asia countries accounted over 52% of the tsunami-affected communities from 1900 – 2009 and increased 95% between 1980 and 2009 (Doocy et al., 2013).

It is estimated that 2.5 million people were affected by tsunamis between 1900 and 2009 and the

2004 Indian Ocean tsunami have contributed to the substantial increase in mortality and affected population in the same period (Doocy et al., 2013).

Meanwhile another study by Lovholt et al. (2012) on global tsunami for a return period of about 475 years found another conclusion. The study confirmed that the huge Asian countries like Indonesia and Japan accounts for a significantly proportion of people living in tsunami prone areas, while Small Island Developing States (SIDS) represent the highest proportion of total inhabitants. This study also found that countries on the Pacific coast of South America, particularly Peru and Chile represents a high number of communities in absolute and relative terms (Lovholt et al., 2012).

Since the tsunami’s impact on mortality is immense, some studies have been conducted to increase understanding of mortality and people’s behavior under tsunami event. They found that the factors influencing the mortality rate in tsunami events include gender, age (Attanapola,

Brun, & Lund, 2013; Yeh, 2010), socio-economic status, demographic composition of the household (Attanapola et al., 2013; Frankenberg, Gillespie, Preston, Sikoki, & Thomas, 2011), level of education whether community received tsunami education, early warning, time until evacuation (Rofi et al., 2006), geographic conditions, stocks of social capital, and political policy

(Aldrich & Sawada, 2015).

However, the vulnerable groups like children, women, elderly people, and people who are living with chronic illness or permanent disability to mobilize in order to survive represent a dominant portion as the affected communities (Birkmann & Fernando, 2008; Frankenberg et al.,

2011; GuhaSapir, Parry, Degomme, Joshi, & Saulina Arnold, 2006; Nakahara & Ichikawa, 2013;

Nishikiori et al., 2006; Rofi et al., 2006; Steckley & Doberstein, 2011; Vijayakumar, Kannan, &

Daniel, 2006). For instance, mortality patterns by age, and gender confirms that compared to men, women were at the most vulnerable in the tsunami affected areas (Frankenberg et al.,

2011). The study of Frankenberg et al. (2011) in Aceh and North Sumatra, Indonesia, after the tsunami 2004 confirms that mortality is the lowest for adult males in their twenties. In the same group, males are about 10 percentage less likely to die than females. Yet, gender gaps are narrower among children under 15-years-old and among adults over 45-year-old that have the highest mortality. Frankenberg et al. (2011) believes that the mortality level of vulnerable groups is greatly influenced by household composition. Women aged 15-44 and children were more likely to survive if one or more men age 15-44 were living in the household (Frankenberg et al.,

2011)(Figure 2-8). This study also found that survival chances were strong linked between

husbands and wives, followed by mothers and their children. It concluded that stronger members of the household would help vulnerable group such as woman, children, and older man or woman in tsunami event.

Figure 2-8. Tsunamis-related mortality by tsunami damage, age and gender (Source: Elizabeth Frankenberg, Thomas Gillespie, Samuel Preston, Bondan Sikoki and Duncan Thomas ,2011). Mortality, the family and the Indian ocean Tsunami (p.168, Figure 2)

The study by Rofi et al. (2006) shows the same pattern for the mortality based on age and gender (Rofi et al., 2006). It is concluded that the risk of death was greatest in the group of youngest, oldest, and females. This study confirmed that the mortality risk among is 1.9 times greater than among males (Table 2-2).

Table 2-2. Summary of distribution of the pre-tsunami population and tsunami victims as adapted from Rofi et al. Pre-tsunami population Tsunami victims N=2,128 Percentage (95%) CI N=125 Percentage Sex Male 1,084 51.1 (48.1-54.2) 104 35.3 (28.8-42.7) Female 1,037 48.9 (46.0-52.0) 191 64.7 (55.9-74.6) Age 0-4 156 7.4 (6.3-8.6) 37 12.7 (9.1-17.1) 5-9 204 9.7 (8.5-11.0) 39 13.4 (9.7-17.9) 10-14 225 10.7 (9.4-12.1) 26 8.9 (5.9-12.8) 15-19 234 11.1 (9.8-12.5) 25 8.6 (5.6-12.4)

Table 2-2. Continued Pre-tsunami population Tsunami victims N=2,128 Percentage (95%) CI N=125 Percentage 20-29 424 20.2 (18.4-21.9) 39 13.4 (9.7-17.9) 30-39 352 11.9 (10.5-13.3) 31 10.7 (7.4-14.8) 40-49 249 7.4 (6.3-8.6) 36 12.4 (8.8-16.7) 50-59 123 5.9 (4.9-6.9) 21 7.2 (4.5-10.8) 60-69 86 4.1 (3.3-5.0) 22 7.6 (4.8-11.2) 70+ 46 2.2 (1.6-2.9) 15 5.27 (2.9-8.4) Source: Rofi, Abdur; Doocy, Shannon; Robinson, Courtland (2006). Tsunami mortality and displacement in Aceh province, Indonesia 3.

Tsunami mortality rates within age group differed substantially with the oldest and youngest age groups had the higher mortality rates while age group between 20 and 39 years had the lowest mortality rate. Risk of mortality for children under 10 years and adults over 60 years, was

2.3 and 3.1 times greater as compared to those in the 20–39-year group category (Rofi et al.,

2006).

Nevertheless, the research findings about the vulnerable group also do not always show a consistency in correlation. Suppasri et al. (2016) reveals that comparing to the 2004 Indian

Ocean Tsunami, the Great East Japan Tsunami 2011 caused a mortality rate slightly higher for men than women, particularly amongst the elderly as define above 60 years old. The research assumes that it may relate to attributes of risky behavior such as rescuing others, role of men as volunteer firefighters, as well as being civil servants who had the duty to give out evacuation warnings to residents until the last minute before the tsunami hit (Suppasri et al., 2016).

These facts contrast with the mortality trend which women group were consistently had a high mortality rate in The Indian Ocean Earthquake and tsunami 2004, especially in Sri Lanka and Indonesia. Using the Great East Japan Earthquake and Tsunami 2011 as the same case study, in contrast the other study found that there is no correlation between sex difference and mortality, expect that mortality only increases with age (Nakahara & Ichikawa, 2013).

Given the fact of the consequences of tsunami, it is suggested that further research in understanding social, economic and environmental aspects for the mitigation effort will play important role in urban planning policy than previously believed.

Tsunami in Indonesia: Nature and Cause

Indonesia, the 4th most populous country in the world, is highly vulnerable to natural disasters. It is situated over three crucial plates; the Eurasian, Pacific, and Australian plates

(Gaina & Müller, 2007). This geodynamic position makes it one of the most seismically active countries in the world and prone to earthquakes which may generate catastrophic tsunamis.

These plates always move to reach an equilibrium position. This movement, called subduction, is apparent to produce large devastating earthquakes due to the high intense energy release

(Petersen et al., 2007; Socquet et al., 2006) (Figure 2-9).

Figure 2-9. Subduction process as configured from platetectonics (Source: platetectonics, 2008.Retrieved from http://www.sjvgeology.org/geology/tectonics.html)

When the earthquake occurs under the ocean then it has the potential to create tsunamis, such as the one on December 26, 2004 in the Indian Ocean that caused by subduction of the

Indo-Australian Plate under the Eurasian Plate. This subduction also formed the volcano range in

Indonesia so its eruption may also generate tremendous tsunami disasters (Lee & Lawver, 1995).

Most of tsunami in Indonesia have occurred in the Banda, Molucca, and Celebes seas of Eastern

Indonesia, the Java-Makassar Strait region, and the Indian Ocean side of Indonesia including

Western Sumatra and Southern Java (Lockridge, 1988).

Some areas situated directly on the subduction zone, such as the western part of Sumatra

Island, south of Java, Nusa Tenggara, upstate Papua, Sulawesi and Maluku, are high vulnerable to tsunami (Badan Nasional Penanggulangan Bencana, 2012). The historical record of tsunami in

Indonesia indicates that approximately 172 tsunami disasters happened in the period between the

1600-2012 (Hamzah, Puspito, & Imamura, 2000). In the past 100 years, the tsunami major events caused fatalities over 458,800 (National Centers for Environmental Information, 2014).

Indonesia is estimated to have 5.5 million people at risk of once-in-500-years tsunami, making it as the third highest population vulnerable to tsunami (Lovholt et al., 2014; United Nations Office for Disaster Risk Reduction,UNISDR, 2013). Based on the source of disturbance, 90% tsunami were caused by tectonic earthquakes, 9% were triggered by tectonic earthquakes, and 1% by tectonic earthquakes that occur on the body of water (lake or sea) or avalanches from the land into the water body (Hamzah et al., 2000).

Tsunami Risk Level in Indonesia

Being composed of complex plates and an active subduction process, the tsunami prone areas encompasses almost the entire coastal area of Indonesia and creating exposure to over five million people (Badan Nasional Penanggulangan Bencana, 2012). For the purpose to assessing the threats posed by tsunamis to communities regarding risk mitigation efforts, the Government of Indonesia developed “A National Tsunami Hazard Assessment for Indonesia plan” (Horspool et al., 2013). This plan produced maps showing the probability of exceeding a tsunami height at the vulnerable coastal area in a given year. The study’s assessment revealed several findings regarding to vulnerability area as described as follow:

1. There is a greater than 10% chance that somewhere in Indonesia will experience a major tsunami warning (tsunami over 3 m) in any one year. 2. For most coastal regions of Indonesia there is a greater than 10% chance of experiencing a tsunami warning (tsunami between 0.5 – 3.0 m) in any one year (Figure 2-10).

Figure 2-10. Tsunami occurrence probability between 0.5 – 3.0 metres yearly (Source Horspool, N.; Pranantyo, I.; Griffin,J.; Latief,H.; Natawidjaja,DH; Kongko,W.; Cipta,A.; Bustaman,B.; Anugrah,SD; Thio,HK., 2013. A probabilistic tsunami hazard assessment for Indonesia (p.6).

3. Regions with low tsunami hazard are the north coast of Java, east coast of Sumatra, the west and south coasts of Kalimantan and the south coast of Papua 4. At short return periods, it is estimated that the west coast of Sumatra, south coast of Java and Nusa Tenggara Barat have the highest tsunami hazard and can expect tsunami with a height between 0.5 - 3 m (orange warning level) (fig 2.10) or > 3 m (red warning level) (Figure 2.11) in a given year.

Figure 2-11. Tsunami occurrence probability over 3.0 meters yearly (Source Horspool, N.; Pranantyo, I.; Griffin,J.; Latief,H.; Natawidjaja,DH; Kongko,W.; Cipta,A.; Bustaman,B.; Anugrah,SD; Thio,HK, 2013. A probabilistic tsunami hazard assessment for Indonesia (p.7).

5. The west coast of Sumatra, south coast of Java and Nusa Tenggara Barat have the highest tsunami hazard for a 100-year return period and would expect tsunami with a height between 5-10 m over this time period. Eastern Indonesia has a slightly lower tsunami hazard and can expect to have tsunami with heights between 2-3 m over a 100-year period (Figure 2-12);

Figure 2-12. Tsunami maximum height every 100 years period (Source Horspool, N.; Pranantyo, I.; Griffin,J. ; Latief,H.; Natawidjaja,DH; Kongko,W.; Cipta,A.; Bustaman,B.; Anugrah,SD; Thio,HK., 2013. A probabilistic tsunami hazard assessment for Indonesia (p.8).

6. At longer return periods of 500 years, parts of Sumatra Island, including the Mentawai Islands, are estimated to have the highest tsunami hazard. For this return period, there is also very high hazard probability for southern Java, Bali, Nusa Tenggara, and North cost of Papua, northern Sulawesi and Maluku (Figure 2-13).

Figure 2-13. Tsunami maximum height every 500-year periods (Source Horspool, N.; Pranantyo, I.; Griffin,J.; Latief,H.; Natawidjaja,DH; Kongko,W.; Cipta,A.; Bustaman,B.; Anugrah,SD; Thio,HK., 2013. A probabilistic tsunami hazard assessment for Indonesia (p.9).

7. The difference in tsunami hazard patterns between different return periods reflect the increasing contribution from earthquake sources that have lower frequency of occurrence in the short term (100 years), but over longer time periods they can cause large tsunami, particularly in eastern Indonesia. 8. The provincial capital cities most likely to experience tsunami are (in order of highest to lowest) Denpasar, Jayapura, Bengkulu, Ternate, Manado, Banda Aceh, Manokwari, Padang, Ambon and Mataram.

Tsunami History in Indonesia

Although the disaster from tsunami in Indonesia is not well documented before 1970 due to technology and policy obstacle (Hamzah et al., 2000), several studies have recorded catastrophic tsunamis and earthquake (trigger) in pre-and-post 1945. These disasters include; Tambora, the

Sumbawa Island, West Nusa Tenggara (1815), Krakatoa, Sunda Strait (1883), Bali (1917),

Tambu, Sulawesi (1968), Lunyuk, Sumbawa (1968), Flores (1992), Banyuwangi, East Java

(1994); Biak, Papua (1996); Banggai; central Sulawesi (2000); Aceh (2004); Nias (2005); West

Java (2006); and Mentawai (2010).

First recorded event is Tambora Volcano eruption and Tsunami in the Sumbawa Island,

West Nusa Tenggara (1815) (Figure 2-14). This was recorded as the greatest volcanic eruption in modern history with VEI=7 caused about 92,000 people loss their life. The total material erupted was estimated 100-300 km3 generated a moderate-sized tsunami with a height of up to 10 m caused the total loss of live about 4,600 people (Tomascik, Mah, Nontji, & Moosa, 1997).

Figure 2-14. The crater of Tambora as adapted from Heinrich Zollinger’s 1847 expedition publication in 1855 (Source: University of Oxford, Bodleian Library Collection)

Second event is Krakatoa volcanic eruption island and tsunami in Sunda strait located between

Java and Sumatra islands in 1883. This event was the fourth greatest volcano eruption in modern history and generated one of the largest and most destructive tsunamis ever recorded. This explosion triggered waves that reached 30 - 40 m high, destroyed urban and villages areas along the Sunda Strait and leaving 36, 417 fatalities. The coast of Java and Sumatra were hit by approximately 19 tsunamis (Tomascik et al., 1997; S. Winchester, 2003). Third event is

Earthquake and Tsunami occurred in Bali (1917). This earthquake with 6.5 on the Richter scale generated tsunami with the height wave as high above 2 meters together destroyed large settlements in the Bali Island. About 15,000 people losses of life during this disaster event

(Tomascik et al., 1997). It is considered as the 25 deadliest earthquakes in the world to present

(McCaffrey & Nabelek, 1987).

The fourth disaster is the Tambu– Sulawesi earthquake and tsunami in 1968. These catastrophes occurred on August 1968 off the northwest coast of Sulawesi island with Mw 7.4.

Tsunami swept the area of Tambu and Sabang with inundation reaching inland 300 meters and 8-

10 meters’ height. The deaths tolls reached over 200 and leaving 58 injured (Badan

Penanggulangan Bencana Daerah Palu, Palu, 2009). The fifth disaster is the Earthquake and

Tsunami Lunyuk Sumbawa in 1977. The earthquake (Mw 8.0) epicenter was on Southwest

Sumbawa Island, Indonesian’s Ocean. The tsunami’s waves (8 meters) reaching inlands 500 meters and swept out the southern area of Bali, Lombok, Sumbawa and Sumba islands. It caused the death toll at 198 and affected over 1,000 people.

The sixth recorded disaster is the Earthquake and tsunami on the Island of Flores in

December 1992. The earthquake with 7.5 Richter scale triggered tsunami waves as high as 26 meters tsunami causing at least 2,000 losses of lives and missing. This disaster caused about over

90,000 people in homeless condition. It is estimated that almost 80 percent of housing were destroyed (National Centers for Environmental Information, 2014; Tsuji et al., 1995). This event was disastrous in terms of loss of live and property damage. Yet, it also provided much information about the geophysical, geological, and engineering aspects of tsunamis and has advanced the understanding of tsunamis and their impact. The Banyuwangi Earthquake and

Tsunami (1994) is another seventh recorded event. A large earthquake of magnitude Mw 7.6 occurred off the southeast coast of Java Island created a 14 meters tsunami inundated 400 meters inland that swept several coastal areas in the Banyuwangi and Jember regencies of East Java

Province (Synolakis, 1995). This tsunami caused 223 fatalities, 15 persons were missing, and destroyed 70 percent of the houses (Tsuji et al., 1995).

The eighth disaster is the Earthquake and Tsunami Biak, Papua (1996). A large earthquake of

Mw = 8.2 occurred about 60 km off the northeast coast of Biak Island, Irian Jaya, Indonesia and triggered a large tsunami hitting Biak Island with the maximum run-up height reached 7.7 m above sea level. As the result 110 persons were killed, 51 persons were missing, 55 persons were seriously injured, and more than 2,700 houses were destroyed (Matsutomi, Shuto, Imamura, &

Takahashi, 2001). The Earthquake and Tsunami of Banggai in 2000 is the ninth event. An earthquake measuring 6.5 on the Richter scale generated a 5 meters tsunami hitting the populated city of Luwuk, Peleng and Banggai Island. It leaved 41 people losses of live, another 228 injured; and an estimated 10,500 families displaced due to homes destruction (Hiraishi & Kawai,

1998).

The tenth catastrophic disaster is the Indian Ocean Earthquake and Tsunami (2004)

(Figure 2-15). This is the worst natural disaster recorded in Indonesian history. The 2004 tsunami was generated by an earthquake of MW 9.2, which occurred in the Indian Ocean. The tsunami spread throughout the Indian Ocean, causing massive destructions in 12 countries. The most damaging effects were sustained by Indonesia. It hit the coastal area of the northern part and the western part of Aceh and North Sumatra and islands in the nearby regions like Nias and

Simeulue islands. The 2004 tsunami caused US$ 4.45 billion damages and losses in Indonesia

(Beppenas, 2006). The Indonesian’s report confirms over 126,000 fatalities, 93,000 missing; and more than 500,000 displacements (Beppenas, 2006). It is recorded that waves penetrated 10 km from the coastline with average wave height between 4 to 39 meters high. This disaster had affected urban population and destroyed more than 250 coastal urban areas in Aceh provinces,

Indonesia (Beppenas, 2006). The December 26 tsunami has become the most important event in tsunami research and disaster mitigation effort in the future particularly in Indonesia.

Figure 2-15. Pre-and Post-2004 Indian Ocean Earthquake and Tsunami in Banda Aceh, Indonesia (Source: International Charter space and major disaster, 2005. Retieved from https://www.disasterscharter.org/image/journal/article.jpg?img_id=36843&t=141145 4230892)

The next eleventh disaster regarding tsunami is The Nias–Simeulue earthquake and tsunami (2005). These disasters occurred on off the west coast of northern Sumatra, Indonesia with a Mw 8.7 and the shakes were felt over 1,000 kilometers away. It is recorded as the third greatest earthquake in modern history of Indonesia. The region was hit for the second time by earthquake and tsunami after devastated by the tsunami triggered by the 2004 Indian Ocean earthquake. The data report that the deaths tolls reached around 569, and 2000 injured. The number of temporary displaced has been recorded at 19,016 while the number of permanently displaced has been put at 35,235 people (Earthquake Engineering Research Institute, EERI,

2005). The West Java Earthquake and Tsunami (2006) is another twelfth disastrous tsunami. An earthquake (Mw = 7.7) occurred in south of Java on July 2006. Tsunami swept along the southern coast of Java that resulted in more than 600 fatalities while 75,000 people displaced.

This tsunami is categorized as a “tsunami earthquake,” meaning that the levels of high-frequency seismic radiation were relatively low for tsunami event and massive impacts (Mori et al., 2007).

The last disaster is the Mentawai Earthquake and Tsunami (2010). The earthquake with a magnitude of 7.7 happened in the western coast of Sumatra. The following tsunami struck the

Mentawai Islands off the western coast of Sumatra reaching a height of 3 meters and penetrating as far as 600 m inland. This tsunami leaved about 435 fatalities, over 100 missing, and displaced more than 20,000 (Newman, Hayes, Wei, & Convers, 2011).

Tsunami in Makassar; Potential and History

General Introduction

The municipality of Makassar is the capital city of South Sulawesi Province. The South

Sulawesi Province site located in the southern part of Sulawesi Island and divided into 20 regencies and 3 municipalities. The population of Makassar City is 1.47 million people

(Makassar Statistical Bureau, 2017) (Figure 2-16).

Figure 2-16. The geographic position and Map of Makassar City as adapted from The Makassar Municipal Government data map (Source: modified by author based on The Makassar Municipal Government Map, 2014)

The City of Makassar is in coastal area along west and north part of Sulawesi Island covering 175, 77 km2. It is located at coordinates of 119° 24 ‘17.38” east and 5° 6.19 ‘6.19” south with flat topography between 1-25 m above sea level. The city’s boundaries are Makassar

Strait to the west and north, Maros Regency to the east, and Gowa regency to the south.

Makassar has two major rivers flowing through the city; Tallo flows into north side of city and

Jeneberang flows to south (Department of Public Works of Indonesia, 2010). It was built in the

13th century and designated as the capital of the Kingdom of Gowa. It became one of world’s trading centers in the 15th century. The city was functioned as the capital city during Dutch colonial era from 1669 to 1945 (Sumalyo, 1996). Its geography position provides direct accesses to the busy sea lanes of the Java Sea, the Makassar Strait and the Sulawesi and Banda Seas.

Makassar city is the largest city in the Province of South Sulawesi and the eastern part of

Indonesia. It links western and eastern part of Indonesia due to its strategic position. The Central

Government of Indonesia/ GOI appointed Makassar city as the center to accelerate the less developed eastern Indonesia. Makassar consists of 15 districts that cover 153 sub districts. The shoreline is 22.8 km long with seven districts located in the waterfront area; Tamalate, Mariso,

Ujung Pandang, Wajo, Ujungtanah, Tallo and Biringkanaya (Makassar Municipal Government,

2015)(Figure 2-17). The waterfront is the focus of development since it becomes the center of commercial, services, industries, and government offices.

Figure 2-17. The Administration Map of Makassar City as configured from The Makassar Municipal Government data (Source: The Makassar Municipal Government, 2014)

The land use pattern is dominated by agriculture, residential and others uses including roads, rivers and public services (Table 2-3 and Figure 2-18). The overall area of waterfront only covers 15, 77 ha or 0.56 percent of the Makassar area, yet it is occupied by 15.05 percent of total population.

Table 2-3. Land Use Pattern in the Makassar City No Category of Land use Total Area (km2) % 1 Residential 25,19 14 2 CBD, Commercial 7,90 5 3 Education 0,88 0.5 4 Industrial estate/ Manufacture 0,88 0.5 5 Port sea 0,88 0.5 6 Agriculture 61,50 35 7 Swamp 35,85 20 8 Green park 1,05 0.6 9 Others (Streets, Rivers, public service etc.) 41,64 24 Total 175,77 100 Source: The Makassar Municipal Government, 2015

Figure 2-18. Land Pattern as adapted from The Makassar Municipal Government. (Source: The Makassar Municipal Government, 2005)

The exiting of Makassar Strait does not allow waterfront area to expand to the sea. This constraint forces the development gradually toward to east side where there is still available land and less dense population. However, the waterfront area still has an important role in the formation and activities. The concentration of population in the waterfront area creates high density areas. The more the distance from the waterfront the lesser the population density are. In

dealing with the increasing people and land scarcity in the waterfront areas, the new location for residential will be allocated in the east side of city that will change the land use pattern

(Makassar Municipal Government, 2015) .

Tsunami Potential

Numerous researchers confirm that Makassar is vulnerable to earthquake generating tsunamis. Prasetya et al. (2001) study records that Makassar Strait region had the highest frequency of recorded in Indonesia. Makassar Strait has been recognized as a main geophysical boundary between the western and eastern Indonesian (Katili, 1978; E. A. Silver, McCaffrey, &

Smith, 1983).

It is estimated that an anticipated tsunami would occur within 15 - 20 years (Hamzah et al., 2000). Six of eighteen major tsunamis recorded since 1900 were generated by large shallow earthquakes that defined having focal depth of <60 km (Prasetya et al., 2001). The study found that the strait has high seismic activity occurred in the Palu-Koro and Pasternoster fault zones

(Figure 2-19).

Figure 2-19. The earthquake distribution in the Makassar Strait (As modified from Prasetya, G. S., De Lange, W. P., & Healy, T. R., 2001. The Makassar strait tsunamigenic region, Indonesia. Natural Hazards, 24(3) (p.300, Figure 5)

Despite unavailable formal data before 1970 except in February 1929 (Passchier, 2016), the current research by Baeda et al. (2015) argued that the increased stress on the edge of the

Palu-Koro and Pasternoster rises the potential for undersea earthquakes generating tsunamis. The study goes on to conclude that based on the modelling for several scenarios (Figure 2-20 and

Table 2-4) tsunami waves may arrive at the Makassar coastal area in 6.07 minutes after first earthquake with maximal run-up reaching 9.0 meters.

Figure 2-20. Makassar position and Earthquake Epicenter Generating tsunami simulation (Source: Baeda, Yasir; Klara, Syerly; Hendra, Hendra; Muliyati, Rita., 2015. Mitigasi Bencana Tsunami di Pantai Losari Makassar, Sulawesi Selatan. Jurnal Penelitian Enjiniring 20 (1) (p.25, Figure 2).

Table 2-4. Earthquake parameters to generating Tsunami in Makassar Strait Reg Location Fault Plane Mag

Name Lat Long Depth Strike Dip Slip Strike 1 Dip1 Slip1

B -4.22 118.85 15.7 38 100 207 207 66 86 5.5

C -3.7 117.91 14.8 13 89 194 74 74 90 5.9

D -4.2 117.8 14.8 13 89 194 74 74 90 5.9

E -4.69 117.69 14.8 13 89 194 74 74 90 5.9

Source: Baeda, Yasir; Klara, Syerly; Hendra, Hendra; Muliyati, Rita. (2015). Mitigasi Bencana Tsunami di Pantai Losari Makassar, Sulawesi Selatan. Jurnal Penelitian Enjiniring 20(1) (p.25, Table 1)

A study of Horspol et al. (2013) found that there is chance that Makassar may experience a moderate tsunami warning wave between 0.5 - 3 meters, which may occur once within 50– 100 years (Figure 2-21). This can issue a “major tsunami warning with a yellow level” according to the InaTEWS scale. These findings of studies may justify the importance of doing research and developing tsunami mitigation measures that are suitable to the local context of Makassar City,

Indonesia.

Figure 2-21. Tsunami 0.5-3 m occurrence possibility per 1/50-1/100 year for Makassar City (Source: modified from Horspool, N.; Pranantyo, I.; Griffin,J.; Latief,H.; Natawidjaja,DH; Kongko,W.; Cipta,A.; Bustaman,B.; Anugrah,SD; Thio,HK., 2013. A probabilistic tsunami hazard assessment for Indonesia (p.6).

Cities and Tsunami Impact

A considerable degree of natural disaster vulnerability like tsunami currently have been a concern in urban areas. The urban context is important to any efforts of disaster management in natural disaster and its human vulnerability and risk. The natural disaster events such as tsunami and its disaster management system are likely to become more complex for cities. As the consequence, the cost may intensify to levels which equal or surpass those of other main urban problems; and they will take a high priority in uncertain socio-cultural, political, economic and technological contexts (Mitchell, 1995). In most part of the world, cities particularly in coastal areas may form the greatest center of natural hazard risk (D. Alexander, 2000). However, while

on the one hand cities are more vulnerable to natural disasters, on the other hand urban people is less sensitive to this issue due to their pressure of urban life (Burton et al., 1978).

Over centuries, the coastal area as front line of city has attracted people to live and work since it provides opportunities for aesthetic, economic, social, environmental benefits (Crossland,

2005; Schmidt, 2012). It is not surprising to find the concentration of people along or near coasts that covers on just 10% of the earth’s land surface. As of 2002, over 23% of global population concentrate in the “near coastal zone” (Nicholls, 2002). This concentration of people brings the economies of agglomeration benefits for production, exchange and consumption and creates a positive multiplier effect (Beaverstock, Faulconbridge, & Hoyle, 2011; Bogardi, 2008).

The development of coastal zones has significantly increased during the recent decades thereby causing these zones to face immense socio-economic and environmental changes and pressures, and this trend that is expected to continue in future. These changes will reduce the environment carrying capacity and degrade the natural coastal environmental protection that contribute to the increasing exposure to natural disasters (Adger, Hughes, Folke, Carpenter, &

Rockström, 2005; Burroughs, 2011; Rees, 1996). And tsunami is viewed as one of the prominent threat to these coastal areas (Degg, 1992). It is estimated that in 2007, 19 million people live in tsunami-prone area or correspond to about 40,000 people hit per year on average globally

(Lovholt et al., 2012). Many of these vulnerable people are living in the coastal cities. For instance, there are about 5.402.239 people are living tsunami prone in Indonesia’s urban area making it as the most affected globally (Badan Nasional Penanggulangan Bencana, 2012). The massive damages and losses include human loss; damage to valuable properties and coastal structure; traffic hindrance; destruction to public infrastructure, fishery, commerce, industry, agriculture, forest, fire, oil spill, and topography change (Gakkai, 1991). The health issues, such

as famine; and epidemic disease is another problem after disaster (Reilly, 2009). It is estimated that the total amount of revenue for tsunami-prone cities is about 186 billion US dollars, with average losses of 392 million US dollars per year (Lovholt et al., 2012). Given these consequences, studying drivers that increase the tsunami impact vulnerability is crucial to be recognized in the reducing impact programs.

The vulnerability of tsunami particularly in developing countries increases with the rapid uncontrolled urbanization (El-Masri & Tipple, 2002), the concentration of industry (Kasarda &

Crenshaw, 1991), growth of slums and informal settlements (Oberai, 1993), the population structure (Kreimer, Arnold, & Carlin, 2003), and the city government’s capacity (Solway, 2004).

The urbanization augments vulnerability through the concentration of people and assets. The pressure development of housing, industrial parks and other supporting facilities in the tsunami prone areas accelerate the pace of vulnerability. In developing countries, cities often house the bulk of the industrial production. The population concentration in the city usually is adjacent to the concentration of industry area due to low cost transportation for employers. Slums and squatter settlements are a common phenomenon especially in developing countries. These informal settlements make up a large portion of cities, doubling every 5 – 7 years. This rises density up to 150,000 people per km2 and this trend may continue without a proper intervention

(Davis, 1987). When the tsunami strikes these informal areas, the loss of lives and social costs may be greater as a significant percentage of the population is less protected.

The number of causalities and losses can rise significantly in the informal settlements located within megacities area (Uitto, 1998). Since these informal settlements are usually considered illegitimate, officials typically do not involve them in urban planning process. As the result, the resources are allocated disproportionally that increase the risk of life, damage and loss

to them (Oberai, 1993; Pelling, 2003). The people living in these informal settlements usually lack political rights which puts them in a disadvantage condition and making urban planning formidable in these informal settlement areas where existing social, economic, political, and technical limitations exist (Davis, 1987).

Urbanization also makes the city larger than its original size and that causes the problems for city government. In developing countries, due to the lack of capacity for managing rapid city growth, unplanned development occurs without controlling that increase the disaster vulnerability like tsunami (Solway, 2004). Typically, women and children compromise over 50 percent of the urban population in developing countries, indicating a high vulnerability to these groups as they are most likely to be victims of tsunami (Frankenberg et al., 2011). They are more vulnerable since these groups only have access to fewer support systems following a tsunami, are less likely to participate in mitigation and prevention efforts; and have not been acknowledged as important stakeholders in terms of tsunami prevention, management, and assistance

(Frankenberg et al., 2011; Kreimer et al., 2003; MacDonald, 2005).

The tsunami impact characteristic of cities in developed countries and developing countries need to be addressed. Typically, cities in developing countries are the most suffered in the loss of life due to unsustainable development (D. S. Mileti et al., 1995), poverty condition (P.

R. Berke, 1995), low community resilience (Pelling, 2003), and poor economy conditions

(Aleskerov et al., 2005). In contrast, the cities in developed countries may have a great effect on economic sectors because cities become the center of service, financial and high-density infrastructure (Cochrane, 2004; Kazama & Noda, 2012; Kreimer, 2001). These high losses and damages can be better absorbed due to a strong economy (Cochrane, 2004). For comparison,

although Indonesia and Japan represent together for more than 50% of global exposure to tsunami in absolute term (Lovholt et al., 2012), the level of effect differs greatly (Table 2-5).

Table 2-5. Summary of Comparison Impact of the 2004 Indian Ocean tsunami and the 2011 Great East Japan tsunami Item 2004 Indian Ocean 2011 Great East Japan Earthquake magnitude 9.3 9 Earthquake magnitude 9.3 9 Earthquake magnitude 9.3 9 Size of rupture (km2) 1,000 * 150 500 * 200 Max. tsunami height (m) 50.9 40.5 No. of deaths 126,732 15,891 No. of missing 93,662 20,000 No. of displaced 500,000 250,000 Total damages US$ 4.45 billion US $300 billion Source: As modified from the Parwanto, N.B. and Oyama, T. (2014). A Statistical Analysis and Comparison of Historical Earthquake and Tsunami Disasters in Japan and Indonesia. International Journal of Disaster Risk Reduction, 7.

From Table 2-5, the significant difference is in the number of deaths from the 2004

Indian Ocean in Indonesia and the total damages for 2011 Great East Japan. Since the level of damages and losses can be influenced by many factors such as social, economic, political, and environment conditions, the tsunami will cause interruptions to social and economic activities leading to unsustainable condition. Therefore, the effort to reduce the impact is needed through disaster management application.

Theoretical Aspects of Disaster Management

Natural disasters have greatly affected humans through human history. The increasing incidence of natural disasters has been a global concern (Harrison & Williams, 2016). Cities as the place of population have begun to be aware that natural disasters are no longer occurring infrequently, but they repeat in a short time. Since urbanization shows the rising trend in the recent years, the disaster-prone areas in coastal cities are facing pressure for development to accommodate social and economic needs. To respond the difficulties, societies and governments in the coastal areas have managed many endeavors to reduce impacts by developing measures in

disaster management. It aids urban stakeholders to assess the natural disaster risks to prioritize program and resources for mitigation (D. Mileti, 1999).

Disaster management is the response of societies and government to minimize the disaster impact to life, asset, and the environment through developing measures to address impacts, post-disaster response and recovery efforts (D. R. Godschalk, 1999). The International

Federation of Red Cross and Red Crescent Societies defines the disaster management as “the organization and management of resources and responsibilities for dealing with all humanitarian aspects of emergencies, preparedness, response and recovery in order to reduce the impact of disasters” (International Federation of Red Cross and Red Crescent Societies, IFRC, 2010).

Coppola (2015) describes the aspects of comprehensive disaster management comprises of four components: mitigation, preparedness, response, and recovery that described as follow (Figure 2-

22):

1. Mitigation. Reduce or eliminating the likelihood or the consequences of a hazard, or both. Mitigation pursues to “treat” the hazard such that it impacts society to a lesser degree.

2. Preparedness. Engaging to equip people that impacted by a disaster or who may be able to help those impacted with the tools to rise their chance of survival and to minimize their financial and other losses.

3. Response. Action to reduce or eliminate the impact of disasters that have occurred or are currently occurring, in order to prevent further suffering, financial loss, or a combination of both. Relief, a term commonly used in international disaster management, is one component of response.

4. Recovery. Engaging to return victims’ lives back to a normal condition after the disaster. The recovery phase begins after the immediate response has completed over some periods.

Figure 2-22. The disaster management cycle (Source: Coppola, 2015. Introduction to International Disaster Management)

Over the years, a systemic responding to natural disasters are developed globally, such as the Yokohama Strategy and Plan of Action for a Safer World that provide the guidelines for prevention, preparedness and mitigation efforts for international community. The community should have a willingness to invest in improving the capacity and carrying out mitigation policies and programs adopted. There are many elements to a community’s capacity to involve in mitigation efforts including fiscal capability; technical capability; legal capability; institutional capacity; and political capacity (A. K. Schwab & Brower, 2008). The occurrence of natural disaster cannot be avoided; yet, impacts can be reduced and minimized through proactive and appropriate planning for instance hazard mitigation planning (Coppola, 2015). Before to explore the interplay between mitigation and tsunami, the general concept of mitigation would be introduced.

The definition of mitigation has a range of perspective. FEMA defines mitigation as

“sustained action to reduce or eliminate long-term risk to human life and property from natural, human caused, and technological hazard” (Federal Emergency Management Agency, FEMA,

2003). Schneider (2002) describes mitigation as “hazard mitigation takes the form of advance

action designed to eliminate or reduce the long‐term risk to human life and property from natural and man‐made hazards” (Schneider, 2002). Coppola, D.P. (2011) views mitigation as the

“cornerstone of disaster management to reduce the likelihood or impactss of hazard risk before a disaster struck.

The mitigation measures employed to accomplish the goals, generally can grouped into two main categories: structural and nonstructural (Coppola, 2015; Gad-el-Hak, 2008). Coppola

(2015) defines structural mitigation as a risk reduction effort performed through the construction or altering of the physical environment through the application of engineered solutions. While nonstructural mitigation is defined as a measure that reduces risk through modification in human behavior or natural process without requiring the use of engineered structures (Coppola, 2015).

The Mitigation program are always costly, disruptive, time-consuming, facing community and political resistance due to socio-cultural and risk perception and interest (Coppola, 2015). To overcome this condition, three approaches can be taken: recognizing the hazards, perceiving correctly the likelihood and impact of natural disaster, rising awareness that the impact can be mitigated and reduced, and incorporating mitigation into reconstruction programs (Coppola,

2015; P. Winchester, 2000)

Despite the rising trend of natural disaster vulnerability, only few studies concentrate on the use of principles of disaster management to the city scale (Murao, 2008; Wilkie & Leon,

2014). Because urban areas are currently accommodate to slightly over 54 per cent of the world’s population, a number that is expected to grow to 66 per cent by 2050 (Wilkie & Leon,

2014), concerns over their safety have led to call for more sensible urban development to ensure the community safety (Kammerbauer, 2013; United Nations. Dept. of Economic and Social

Affairs, 2014). Because tsunami affected cities will have a tremendous destruction and damages,

it is important to prepare and mitigate the impact these urban areas through integrating mitigation and urban planning policy.

Interdisciplinary Approach for Tsunami Mitigation

The trend of natural disaster impacting coastal cities has highlighted the fragility of urban systems to handle disaster like tsunami. The effort of tsunami impact mitigation needs the comprehensive approaches to reduce a negative effect to people. Over the years, there are many institutions and interdisciplinary scholars and practitioners with stakes in the wide range of mitigation approaches, particularly emergency management, civil engineering, and public health.

However, planning is viewed can play main a role in the process, and its absence can make the mitigation process is less comprehensive (J. Schwab & American Planning Association, 2010).

Therefore, it is important that planning take their role in this mitigation area and use their approach to maximize the output of community safety. Nevertheless, it is important to understand that involvement of public during the mitigation policy process is a must in order to reach the sustainability.

Spatial and Physical Planning in Indonesia

The history of Indonesia’s urban planning, like other main Southeast Asian cities, had been influenced by long period of colonialization particularly by the Dutch (C. Silver, 2008).

The modern history of planning especially in urban areas can be tracked from the beginning of twentieth century or around the 1910s. During this time, some Dutch colonial towns particularly in coastal area as the concentration of political and economy faced a rapid urbanization, hence the planning employment was demanded (Wignjosoebroto, 2004). The Dutch colonial more concentrate the planning on the physicality’s aspects like aesthetic (Passchier, 2016) and separation of classes and races through space allocation (C. Silver, 2008) with centralistic and structure approach (Hudalah, 2010).

Throughout 1920s, the colonial city authorities acknowledged the demand for public and private development to be regulated not only for aesthetic and space allocation for segregation policy. In 1925, the colonial government adopted the policy to allow private companies/ naamloze vennootschappen to involve in housing business. In 1926, other guidelines were enacted to regulate urban extensions and housing, urban rights on land and the nuisance ordinance, permission and zoning systems for industrial development in urban area (Niessen,

1999). The funding allocation up to fifty percent to improve kampong was implemented in 1928

(Rückert, 1930).

As the cities growing, a Town Planning Committee/ Stadsvormings commissie was established in Batavia (Jakarta) (Roosmalen, 2005). In 1938, the committee proposed a draft of city planning ordinance/ Stadsvormings-ordonnantie or SVO to The People's Council/ Volksraad.

It is recognized as the turning point to practice planning comprehensively focusing on urban housing conditions in the cities in Java that were facing rapid urbanization at that time (Niessen,

1999; Roosmalen, 2005). Nevertheless, the implementation of city planning ordinance/ SVO was postponed to 1949 due to outbreak of WWII. After independence in 1945, planning practice faced the power transition from the ‘European elite’ to ‘indigeneous urban elite’ (C. Silver,

2008). The planning process reflectively a hierarchy structure sustained western values and concentrated on wealthy businessman and professionals; bureaucrats; and military (C. Silver,

2008). The transition of power also changed the physical structure of Indonesian’s cities including the location of major economic functions, cultural institutions and housing patterns (C.

Silver, 2008). As a result of the immense war, large parts of major cities were destroyed, so reconstruction and rebuilding became the focus of planning. The Department for Public Works and Reconstruction and the Planning Bureau to carry out this huge task. However, some major

obstacles needed to be addressed at the time including the absence of professionals, establishing organizational infrastructure, and creating a regulation framework (Roosmalen, 2005).

The inherited colonial planning law continued to be criticized for its inappropriateness as it accommodated the colonial interest and strong Java-centric paradigm. The closure of many of the centralized pre-war institutions provide an opportunity to adjust the methodology, organization, and regulations in urban planning (Roosmalen, 2005). The centralization and Java- centric development and planning still become the paradigm in post-independence era and more robust in the New Order era that began in 1966 as Suharto came to power replacing Soekarno’s

Old Order. The planning practices in these two-political eras for centralization development in urban areas creating the problem (Akil, 2003). It makes the gap of demographic and economic distribution inducing the rapid urbanization (Deni, 2003).

Between 1976 and 1992, several particular legal frameworks for planning were adopted including regulation of the Greater Jakarta as metropolitan area in 1976; Batam Island as free trade zone in 1973; Puncak Area as national tourist area in 1983; urban and regional policy to supporting agriculture sector in 1980, industrial estate to boost economy in 1989, national tourism and housing policy in 1985 (Moeliono, 2011). These legal were under presidential orders. The Ministry of Home Affairs in 1982 enacted Permendagri 2/1987 and the Ministry of

Public Works in 1986 adopted the decree of Permen PU 640/1986 which are similarly guiding the urban planning process and becoming references for planners in Indonesia (Moeliono, 2011).

The growth of cities was the result of rapid urbanization for economic motives while the increasing demanding for managing the natural resources lead to enactment of the first comprehensive planning law “The Spatial Planning Law 24 of 1992”. The law defines planning comprising three key processes; the plan-making process, plan policy implementation, and plan

controlling in national, provincial and local governments level (Rukmana, 2015). The law guides the planning must meet the principles of integrity, sustainability, effectiveness, compatibility, equality, justice and legal concern, as well as public participation while integrate important issues including social, economic and environmental aspect, geographical representatives, demographics, culture, and physical characteristics (Rukmana, 2015).

The planning law 24/1992 is the first comprehensive law integrating the planning process and institutions in modern history of Indonesia that requiring the hierarchical system. The system consists of the national spatial plan (RTRW Nasional), the provincial spatial plans (RTRW

Propinsi) and the district spatial plans (RTRW Kabupaten and RTRW Kotamadya) (Rukmana,

2015). However, the law only provided general guidance for planning process at the national, provincial and local levels while detailed guidelines became the responsibility of government agencies and respective ministries. One of detailed guideline completed is the Government

Regulation/ Peraturan Pemerintah 69 of 1996 regulating the public participation, rights and obligations. While other guidelines were being developed, the Asian financial and economic crisis of 1997–1998 hit Indonesia that change the political system from dictator and centralized system to democratic and decentralized system or called as the reformation era.

The transition of power in the reformation era in 1998 also impacted the Spatial Planning

Law 24/1992 since it was not relevant to the spirit of decentralization and the new institution structure. The Indonesia parliament adopted the new law of Spatial Planning 26/2007 to replace the Spatial Planning Law 24/1992 to harmonize with the other decentralization laws. The Spatial

Planning Law 26/2007 distributes more power to the provincial/ states governments and districts/regencies/ cities governments in planning, particularly in coordination between provinces/ states or districts/regencies/ cities. The Spatial Planning Law 26/2007 adds new

principle including the accountability with reflecting the value of more transparency and accountable system of government, the standard of basic services, the metropolitan and megapolitan issues, open spaces in urban areas, urban development control, incentive and disincentive, sanctions, as well as public participation improvement (Republic of Indonesia,

2007).

The Indonesian planning system that was guided by the planning laws of 1992 and 2007 adopts an integrated-comprehensive method that is different from the colonial planning model

(Hudalah, 2010). This approach manages a planning system through a systematic and hierarchy structure from the national to the local level focusing more on spatial coordination for social and environmental sustainability than economic development (Europen Union, 2001). The

Indonesian system adopts hierarchical structure. This system demands spatial plans are made at the national, provincial (state) and local (city/regency) governmental tiers. Each level is required to develop specific plans using different scales from general spatial plan (RTRW), detailed spatial plan (RDTR) to detailed engineering design (RTR Kawasan). At the city level, physical planning is accommodated in the urban detailed spatial plan (URDTR). It is a translation of the general spatial plan (RTRW) into the plan regulating the use of which structural and non- structural dimensions are managed in a spatial urban area. It mediates the complexity between the spatial policy in a general spatial plan (RTRW) and detailed engineering design (RTR

Kawasan) (Figure 2-23).

Figure 2-23. Spatial Planning system in Indonesia (source: Hudalah, 2007). Spatial Planning System in Transitional Indonesia 12 (3) (p.294, Figure 1)

Moreover, it is interesting to see how the North American planning system are adopted in the Spatial Planning Law 26/2007 (Cowherd, 2005; Hudalah, 2010). Hudalah et al. (2007) argues that the ideas of decentralization as originated from the United States planning system, should be employed to advance a more effective planning system in Indonesia (Hudalah &

Woltjer, 2007). Though, decentralization in the spatial plan process have not been fully implemented from central, provincial, and local authorities in Indonesia while in contrast to US spatial plan system, it is just the responsibility of the local authorities. Booth (2005) explains that this adoption phenomenon is normal as a planning system is dependent as a ‘product of cultural forces’ (Booth, 2005). This phenomenon is not an isolated process but an active interaction simultaneously between the political system and cultural traditions as internal forces and neo- liberal globalization values as external forces to form local spatial planning system (Booth, 2005;

Healey & Williams, 1993; Vries & Broeck, 1997).

Although the progress in spatial planning policy has been improved in responding to local problems in Indonesia, there are still several issues that need to be addressed to promote urban sustainability. These issues include; deficient coordination between central, provincial, and municipalities/ cities governments; central government decrees that take precedence over existing spatial/ urban plans (Rukmana, 2015; Widianingsih & Morrell, 2007); a lack of all level government capacity and will (Hudalah, 2010; Rukmana, 2015); vested political and business interests (Winarso & Firman, 2002); unaccountability and ineffectiveness (Rukmana, 2015); and low public participation (Hudalah, 2010).

Rapid urbanization at a rate of 4.1% yearly has transformed Indonesia to an urban based economy (Deutsche Welle Business, 2016). Indonesia’s cities are home to 52 percent of total population in 2012 and it is expected that by 2025 the figure will reach to 68 percent. The total area for urban expansion has increase substantially between 2000 – 2010 from about 8,900 square kilometers to 10,000 or an average growth of 1.1% yearly making Indonesia second only to China in total amount of developed urban land in Asia (Indonesia World Bank., 2016).

Despite the impacts of urbanization, Indonesia’s cities may benefit more from this urbanization trend for higher economic growth through urban economy efficiency and productivity. The data confirms that each 1% growth in urban inhabitants strongly correlates with per capita GDP increase of 13% in India, 10% in China, and 7% in Thailand while

Indonesia only gain 4 % GDP growth (Indonesia World Bank., 2016). The low of gain can be the result of inefficiency economic activities of goods and services resulting from insufficient infrastructure, congestion, pollution, and disaster risks (Duranton, 2014; Indonesia World Bank.,

2016); ineffective urban management; uncontrolled spatial planning, and commitment to the planning principles (Goldblum & Wong, 2000). One of issue that must be concern is the rising

natural disaster vulnerability and its impact on cities in Indonesia caused by several factors. First, rapid population growth in cities has pressured people to concentrate living in hazard prone areas, thereby increasing exposure to natural disasters. Second, decreasing of environmental quality as the result of over-exploitation of resource by population worsens the condition in natural hazard prone areas (Sunarharum, Sloan, & Susilawati, 2014). Third, most of the cities located in coastal area, along a river or in seismic areas are vulnerable to natural disaster such as tsunami. Last, there is high vulnerability to exposure to poor and marginalized group since they represent almost one third to one-half of the population living in Indonesia cities particularly in slums and informal housing (Bappnes & UNDP, 2006) All these facts must be put as priority in urban planning process along with a public participation approach. The lack of recognizing this natural hazard vulnerability foreshadows an enormous damages and losses to cities in short, middle and long effect to the impacted cities. For this reason, physical planning can be employed to reduce disaster impact like tsunami through appropriate policies.

Physical Planning

Physical planning can be viewed as one key component of planning initiatives. However, defining physical planning has no universal acceptability as every spatial planning system has its own local system. In the United Kingdom, physical planning is the power given to counties and county boroughs to prepare development plans which would map proposed uses of land within their area, and the task of “control” for post-war urban development. Physical planning is exercised by authorities under “The Town and Country Planning Act 1947 and follow-up act in

1968”. The physical planning becomes determining factor in UK’ urban development. Bruton

(1974) defines physical planning in the UK context as a physical design of something which already exists or might exist in the future and this sort of plan is the representation in a geographical or spatial sense, of an actual physical structure or elements (Bruton, 1974).

However, critics point to the scope of physical planning powers and the way it had been exercised that are viewed quite inconsistent with the interpretation due to market force; land, property, finance etc. (Pickvance, 1982), therefore requiring a reformation of spatial planning system (Hall, 1970). As the urban problem is more complex, the work of physical planning is widened covering the nation’s territory. As the consequences, the term of physical planning has been a part of wider plan of “town and country planning” in the UK system (Forbes, 1974).

In the United States, the physical planning role is marked with the discussion among scholars and practitioners to understand the forces that were shaping land-use and the infrastructure in the early birth of planning field. Various political, economic, and physical factor were debated and studied before and after the first National Conference of Planning in 1909.

Over the years, planners explicitly addressed the arrangement of physical structures such as open space civic centers, transportation corridors, and industrial zones that laid the foundation for future urban planning initiatives (Pivo, Ellis, Leaf, & Magutu, 1990).

However, these approaches neglected the social and economic underpinning of urban structures (Gans, 1963) and these plans failed to offer solutions to serve the community (Gans,

1963; Maniera-Elia M., 1979). As the responses, during the 1950-1960 the importance of social and economic factors has been extensively introduced to physical planning, such as the model of economy in explaining the distribution of land in space (Alonso, 1974) and the relationship between physical structure and class structure (N. J. Johnston, 1966). In this era, the new physical planning view focused on politics, social issues, public participation and the planning process rather than the production of physical plans (Gans, 1969; Perin, 1967). During the 1970s, environmental issues became extremely important in the physical planning arena (McHarg,

1969). Physical planning continues to include certain factors to work with to improve the

understanding of the forces that shape land-use and the infrastructure that supports it. However, the term, meaning and scope of physical planning has also been modified (Pivo et al., 1990)

Physical planning in Indonesia relates to the land use management to accommodate the growing population in cities due to urbanization (Tarigan, 2015). From about 1960 to 2000, the planning policy for physical configuration in urban areas was aimed not only for accommodating the growing population but also to accelerate the economic interest of central government or centralization system (Tarigan, 2015; Yunus, 2000). The physical planning policies were prioritized for cities located in Java Island (Java centrist development)(Hudalah & Woltjer,

2007) such as infrastructure, industrialization, urban facilities, urban poor eradication, and slum upgrading. The physical planning for cities outside Java Island was not considered an important part of national planning and development, therefore the wide development gap exists in these cities for instance the lack of infrastructure, facilities, high rate of poor group, slum area.

Although physical planning was appropriately adopted in cities located outside Java island, but it was aimed to improve the infrastructure to facilitate the movement of goods such as minerals, plantation crops, fishery product to cities in Java Island as the center of economic (Tarigan,

2015; Yunus, 2000). In short physical planning was intended to serve the interest of central government.

In the reformation era from 2000 onward, the physical planning has been more decentralized. As a result, urban development in cities outside Java Island enjoy acceleration of development (Tarigan, 2015). The physical planning echoes the interest of people through public participation process (Rukmana, 2015). The physical planning is not only focuses on physical element to boost economic growth and accommodate growing population but also to

incorporating social aspects such as affordable housing scheme, and urban poverty eradication

(Hudalah & Woltjer, 2007; Rukmana, 2015).

To strengthen the function of physical planning in Indonesia’s spatial system, physical planning is formally accommodated in Detail Spatial Plan/ Rencana Detail Tata Ruang Kota

/RDTR (Republic of Indonesia, 2007). RDTR directs the strategy of spatial use in order to maintain the integrity, balance and harmony of the urban development to meet the harmony among social, physical, economy and environmental aspects to improve the inhabitant’s life quality. The RDTR includes managing of urban structure plan, block functioning plan, the transportation system, public facilities, housing strategies and design, the social role and public participation, economic structure to support the community, and social interventions to improve the community conditions (Arszandi et al., 2015). Two majors distinctive of physical planning in

Indonesia after the reformation era is the decentralization and public participation involvement.

These factors greatly influence the substantive and output of physical planning in Indonesia despite some areas that still need to be improved.

Despite the difference of definition, meaning and function, some studies believe that the physical planning might be inherently the same concept. Physical planning can be viewed concerning with the management of land-use, the character and location of public space and structures, the development of transportation systems, and all other infrastructure facilities which required to support the economic development, and the public interest (Webster, 1958). In response to urban complexity and problems, the physical planning field has grown to include urban design, environmental planning, economic aspect and social approach (Branch, 1985; Pivo et al., 1990). It enhances the efficient functioning of the urban system through effective coordination of the various urban land, provision infrastructure and services making cities are

economically viable while being environmentally sound, socially cohesive and progressive

(Folmer & Risselada, 2012; Neutze, 1985; Newman, Kenworthy, & Vintila, 1995). As Crook

(1974) adds that the task of physical planning is to prevent, control and promote the changes which have, which are and which may occur within physical environment (Crook, 1974).

The concept and function of physical planning can be different in developing countries comparing to developed ones. In the developing countries, physical planning is having only limited role in directing the urban development while it is commonly intended to serve the elite interests with wider-spread neglect of urban poor (Chadwick, 1986; Mbogua, 1994). The community is usually excluded in the physical planning process. Furthermore, responsibility of physical planning for urban development only is shared between government and private sectors

(Chadwick, 1986; Etoju, 2002; Mbogua, 1994). The planning policy also generally lacks facilitating and providing basic infrastructure for people (Mbogua, 1994). It can be argued that these phenomena are the result of a rapid urbanization, lack of resources and technology, insufficient public infrastructure, ineffective development control, social and political instability at the same time (Brueckner & Lall, 2014; Cohen, 2004; Olajuyigbe & Rotowa, 2011).

As the cities in developing countries contribute significantly to national development, physical planning needs to be acknowledged with these approaches; the need to adopt the planning more flexible and adopt with new development under economic and social interest; physical planning must consider the local values, context and system and not to adopt the western-type planning completely (Chadwick, 1986) ; involving important factors comprehensively in physical planning policy including social, environment, and economics

(Basiago, 1999; Haar, Rodwin, & Higgins, 2007); increasing awareness and participation of public (Wilson, Hannington, & Stephen, 2015); employment of technology in the physical

planning process (Chadwick, 1986); and improvement of human capacity and resources

(Olajuyigbe & Rotowa, 2011). Given this complexity of issues in developing nation cities, it can be concluded that the role of physical planning is important to manage and guide the cities through zoning, regulations and permission for uses especially in disaster prone coastal area

(Chmutina, Ganor, & Bosher, 2014; El-Masri & Tipple, 2002; Manda, 2014). However, it is important also to question how far and how effective the physical planning adopted has met the aims, goals and expectation of urban stakeholders. In line with this concern, use of an assessment system can be an appropriate strategy.

Evaluating Physical Planning

The theoretical and application of evaluation aspects of planning have attracted considerable attention from scholars since the 1960s. Evaluation is viewed as the main part of the rational-comprehensive system in urban planning process (Oliveira & Pinho, 2010). The current planning schema requires for employing evaluation as key for measuring the impacts of planning for community (Guyadeen & Seasons, 2016). Particularly, planning’s evaluation using the indicators and value methods on society, environment, and economy has gained recognition

(Oliveira & Pinho, 2010). However, defining, categorizing and understanding principles of evaluation especially in physical planning might be complex since it can include many perspectives.

The definition and application of the evaluation in planning have brought many approaches since it is complex based on a range of variety views (E. Alexander, 1998). Weiss

(1998) describes evaluation in planning as the systematic assessment of the operations and outputs comparing to a set of standards to improve the plan (Weiss, 1998). This definition focuses on program effectiveness and the process to deliver the program. It can be also defined as a set of activities oriented to the appropriate group of the information needed to make a

choice, therefore each stakeholder involved can take a balanced decision in decision making

(Nijkamp et al., 1990). This definition sees the organization of data for effective output as the aim of evaluation.

Generally, the types of evaluation can be categorized into three categories: ex ante (a priori), ongoing, and ex post (Guyadeen & Seasons, 2016). Talen (1996) also develops the types of evaluations for application and methodologies in the following:

1. Evaluation s prior to plan implementation including evaluations of alternative plans and analysis of planning documents; 2. Evaluation of planning practice including studies of planning behavior and description of the impacts of planning and plans; 3. Policy implementation analysis; 4. Evaluation of the implementation of plans including nonquantitative and quantitative.

These types strongly relate to the type different stages of planning; preparation, implementation, and plan revision. Other scholars also classify two main types of program evaluation; formative and summative. A formative approach focuses on improving the performance and increasing the effectiveness of program by providing feedbacks for immediate decision (McDavid & Hawthorn, 2006). The summative method focuses on outcomes of the program and only occurs after completion or substantially completion of program or plan

(Shadish, Thomas, & Laura, 1991). The planning field generally categorizes evaluation into two types; plan evaluation (i.e. plan quality evaluation, plan implementation evaluation, and plan outcomes evaluations) and planning evaluation (i.e., the evaluation of planning processes and of planning practice) (Guyadeen & Seasons, 2016). While evaluating planning aims to determine whether the process of planning was effective, evaluating plans assesses the quality of the plan, the success of implementation, and the accomplishment of plan goals and objectives. Although in practical, they are both separate and independent, but some scholar argue that they are

inseparable concepts (Khakee, 1998) and that linking them stronger will increase the quality of plan (Oliveira & Pinho, 2009).

The evaluation plan prior to implementation is a crucial step to develop the causal link between plan inputs; plan goals and objectives; and plan output and outcomes. These linkages are important since they allow the stakeholders to identify the specific role of plan, the impact of the plan and predictive effectiveness measure while considering all future constraints (Talen,

1996). In line with this situation, Laurian et al. (2010) recommends that the employment of method of control groups, quasi experiments, and statistical analysis can be useful to identify the independent effects of plans. Laurien (2010) notes that in order to evaluation to be successful and effective, the use of extensive empirical evidence is required, including the selection of indicators linking plan goals and objective to outcome.

Indicators are main component to evaluate all stages of planning. Indicators may help to describe the scope of necessary information required to make judgements by stakeholders regarding a plan of effectiveness, performance, identify problems, and to improve plan in ex ante

(a priori), ongoing, and ex post phases. The development of indicators as the quantification of information can help stakeholders to communicate, negotiate, and make decisions (E. R.

Alexander, 2000; P. Berke et al., 2006). Indicators can be used to measure the performance assessment of physical planning. Beyond the evaluation program, indicators are important to rise awareness of planning and social, environmental, and economic problems while advocating sustainable agenda of cities (Talen, 1997). The employment of indicators is one way to reduce the planning failure to control the future uncertainty (Talen, 1997; Wildavsky, 1973).

The discussion of indicators in planning have emerged in the 1960s and 1970s and later was enlarged with the importance of sustainable issues in the 1980s and 1990s (Boyce, 1970;

Faludi, 2000; Seasons, 2003a; Seasons, 2003b). In the beginning, three general indicators commonly used to include social indicators, environmental indicators, and economic indicators.

These traditional indicators were usually used in exclusive framework, yet during the 1980s this approach changes with introducing of integrative approaches for instance sustainability, quality of life, healthy, public participation etc. (Hoernig & Seasons, 2004).

Although there are various evaluation methodologies developed for a plan scale, such as the Policy-Plan/Programme-Implementation-Process (E. Alexander, 1998), the Plan

Implementation Methodology (Laurian et al., 2004) this study finds that only a few has an integral method that fully integrate disaster management aspects. In most cases, these methodologies only focus on indicators of social, environment and economic aspects. Given the data that natural disaster event, losses of life and damages increase substantially, therefore there is a need to assess the gap between integration of disaster mitigation and planning process.

Theoretical Gap and Planning Implications

As has been previously discussed, natural disaster like tsunami, can affect many urban areas. The scale of destruction, damages and losses may vary depending on the geographic factors, the preparation and community resilience (Bernard, 2005). Tobin et al. study (1997) revealed that there is the recognition of tsunami mitigation measures in the physical planning process and products based on community experience and knowledge, capacity building and technologies application (Tobin & Montz, 1997). The integration of these mitigation measures and physical planning may reduce the impact to urban community while increasing the level of resilience to withstand tsunamis consequences as they share the same values (Adger et al., 2005;

P. Berke, Lyles, & Smith, 2012; J. Schwab & American Planning Association, 2010). The integration also is viewed as a comprehensive approach to reduce the impact as the number, intensity; and conflict of use in coastal area increase (Burroughs, 2011). The successful

integration needs the commitment of political leaders and key local stakeholders to sensible prioritize for mitigation efforts (J. Schwab & American Planning Association, 2010). In addition, according to J. Schwab (2010), the integration provides the benefits as follow:

1. Improved pre- and post-disaster decision making at each level; 2. Formation of partnerships between planners and emergency managers at each level; 3. Expansion of external funding opportunities for state and local governments; 4. Facilitation of the post-disaster return to normalcy for states and communities; 5. Resolution of local concerns with community-based rather than outsiders imposed solutions.

Particularly, the integration of tsunami mitigation and physical planning has three main aims (A. K. Schwab & Brower, 2008):

1. Keeping future development out of known hazard areas; 2. Keeping hazard from affecting existing developed areas; 3. Strengthening existing development to resist hazards.

To ensure physical planning met with the objectives of tsunami impact mitigation, the evaluation of indicators prior to implementation is required. Some studies have confirmed that lack of this process may cause the failure of implementation (L. A. Dengler, 1998; M. K. Lindell

& Prater, 2000; Tang, Lindell, Prater, & Brody, 2008). Yet, since the evaluation methods that are adopted by developing countries like Indonesia generally were originated in developed countries, there is some reasons to question the effectiveness of the method. Because of difference in social, economy and environment factors, a theoretical gap may exist. To pursue physical planning without regard to disaster management, especially tsunami impact mitigation, may lead to overall detrimental impacts on urban communities in developing countries. The consequences may also be exacerbated since these cities are facing the rapid urbanization that is outmatching the capacity of city government to cope with the environmental and disaster impacts (Mbogua,

1994).

The above discussion indicates that there is a need to develop the indicators for tsunami impact mitigation measures and to evaluate them in the context of local conditions while also adopted suitable measures from other case studies. Interdisciplinary knowledge and method can be used to understand the complexities in tsunami mitigation impacts in constructing an indicator framework by involving various stakeholders in the evaluation process to fill the theoretical gap.

This new evaluation approach in physical planning show a good promise therefore this method deserves careful deliberations.

For this reason, this study proposes the use of a Structural Equation Modeling (SEM) to have a comprehensive model to evaluate while confirming variables influencing tsunami impact mitigation (Byrne, 1998). Structural equation modeling can be used to analyze structural relationships with a multivariate statistical analysis technique. SEM combines factor analysis and multiple regression analysis to analyze the structural relationship between measured variables and latent constructs (Byrne, 1998)(Figure 2-24).

Figure 2-24. The combination of factor analysis, multiple regression analysis, and path analysis to measure variables and latent constructs (source: Byrne, Barbara M., 1998. Structural equation modeling with LISREL, PRELIS, and SIMPLIS: basic concepts, applications, and programming).

SEM calculates the multiple and interconnected dependence in one direct process by using two types of variables; endogenous variables and exogenous variables. Endogenous variables correspond to dependent variables and exogenous are similar to the independent variable. There are two types of models are evaluated in SEM (Kline, 2011) (Figure 2-25);

1. Measurement model: This model measures the theory that defines how measured variables linking together related to the respective theory. 2. Structural model: Represents the theory that displays how validated model constructs are linked to other validated constructs.

Figure 2-25. A logic model of SEM (source: Byrne, Barbara M., 1998. Structural equation modeling with LISREL, PRELIS, and SIMPLIS: basic concepts, applications, and programming)

The use of a Structural Equation Modeling (SEM) in research has increased in various field of disciplines and becoming of greater interest among researchers in the built environment

(Akinyode, 2016). However, there is little awareness about its application in planning. This has consequently led to difficulties encountered in the use, explanation and/or drawing appropriate interpretations from SEM analyses. Therefore, this study also attempts a new approach for using

SEM in the effort to enhance the application in planning and disaster area.

The following section discuss about tsunami impact mitigation literature and identifies some of cases studies that applicable to mitigate the impact of tsunami in physical planning for the context of Makassar City, Indonesia.

Tsunami Impact Mitigation Measures

In some parts of the world, many cities are located in tsunami prone areas (Lovholt et al., 2012). If a tsunami occurs, they will have great damages and losses due to concentration of inhabitants, infrastructure and embedded socio-economic value and assets (Pelling, 2003).

Hence, it is very important to prepare them with a suitable mitigation policy and plan. Yet, there is no suitable single method to apply for mitigation due to difference of environment, social, and economic factor of community (Farreras & Sanchez, 1991). The chosen approach will depend on the government especially in local tier and other urban stakeholders who adopt an appropriate method to suit their area. Nevertheless, there are certain common features that are extensively discussed in the tsunami impact mitigation that is the combination of structural and non- structural measures by encouraging the public participation in the physical plan process.

There are different studies that were identified as the necessary component of tsunami impact mitigation. This research develops the mitigation indicators framework to measure based on the study of US National Tsunami Hazard Mitigation Program (NTHMP) (2001), Coppola

(2015), and Schwab and American Planning Association (2010). Based on the research, most commonly aspects mentioned resources for tsunami impact mitigation are public awareness; land use and development regulation; land and property acquisition; transportation plan; environmental management plan; housing strategy; fiscal and taxation; risk transfer, sharing, and spreading; public emergency infrastructure; evacuation; emergency road network plan; coastal infrastructure; control forests; vital infrastructure and critical facilities; and warning systems. To link and harmonize with sustainable agenda and to meet the requirement of SEM for classification, this study categorizes them in groups; social, economic, environmental, and infrastructure variables. In the following section, this study explains the role and function of these measures to reduce the tsunami impact integrating in physical planning.

Public Awareness

The important approach to reducing loss of life, injuries, and damages from tsunami is widespread public awareness and education. It is viewed as the key to an effective and sustainable mean in mitigation policy and practice (Coppola, 2015; A. K. Schwab & Brower,

2008; J. Schwab & American Planning Association, 2010). This must involve as many as urban key stakeholders as possible to acknowledge the principle and actions in reducing the natural disaster impacts (J. Schwab & American Planning Association, 2010). Public awareness can also improve what people think and perceive about disasters in order to act properly to the natural disasters (Sims & Baumann, 1972; White, 1964; White, 1974).

Since the impact of tsunami cannot be prevented but only can be reduced, a tsunami impact mitigation programs to some degree will also greatly depend on public participation as the result of public awareness and education programs. Studies confirm that many communities’ tsunami prone cities have a limited knowledge to understanding the tsunami and capacity to reduce the impacts (Bird & Dominey-Howes, 2006; D. Johnston et al., 2005; Tetsushi, Akiko,

Miki, & Sisira, 2006). Raising public awareness on tsunami and its effects aims to encourage

‘‘tsunami resilient’’ coastal communities that have the following characteristics: understanding the nature of the tsunami; having the necessary tools to reduce the impacts; disseminating information and exchanging information about tsunami risk within community; and institutionalizing planning for a mitigation impact (L. Dengler, 1998). Therefore, a successful tsunami mitigation program for physical planning need to incorporate approaches to improve public awareness as follow:

1. Conducting public education & risk communication program (e.g. education and training) to reduce the community’s vulnerability (Couling, 2014; L. Dengler, 2005; Mimura, Yasuhara, Kawagoe, Yokoki, & Kazama, 2011; United Nations International Strategy for Disaster Reduction, UNISDR, 2007). The awareness of tsunami by the vulnerable community through education is one of the most effective tools in mitigation programs. Through education, individuals will have a greater understanding on how to response to a disaster event and how the mitigation program works so they also have willingness to share this knowledge to other coastal communities. 2. Conducting risk communication regularly for the community is also an important program to maintain sustainable awareness, preparedness and mitigation for resilience (Bradley, McFarland, & Clarke, 2014; Susmayadi, Sudibyakto, Kanagae, Adiyoso, &

Suryanti, 2014; United Nations International Strategy for Disaster Reduction, UNISDR, 2007). In order to rebuild and mitigate the eastern part of Sendai which was severely damaged by the tsunami, Sendai adopted "Sendai City Earthquake Disaster Reconstruction Plan" in 2012. The Plan is intended to be systematic and flexible in implementation and based close cooperation and participation process that conducted regularly for review. In October 2012, UNISDR recognized Sendai as a role model for it focus on resilient recovery and mitigation efforts. 3. The development of comprehensive tsunami hazard maps (inundation maps and evacuation maps) with public participation for raising public’s awareness (Burby, Deyle, Olshansky, & Godschalk, 2000; Cadag & Gaillard, 2012; Shigenobu & Dinar, 2010). Developing tsunami hazard maps can be considered as an effective medium for raising awareness, elevating knowledge, and communicating tsunami risks while also becoming a justification for the development of measurable tsunami mitigation for physical planning for selective land-use controls (Burby et al., 2000; Tobin & Montz, 1997). Maps are also a fundamental element in recognizing how people with, respond to, and mitigate against natural hazards (Cutter, 2001). Example of of Hilo city, Hawaii, USA shows the importance of the tsunami hazard map for public participation. Following the last two devastating tsunamis of 1946 and 1960, the Hilo Downtown Redevelopment Plan in 1974 to redevelop the city center based on previous tsunami inundation lines. This plan aims to protect area for safety based on the 1946 and 1960 tsunami and evidence from the community. It directed that all development in the safety area was subject to careful planning and design standards. The redevelopment was applied to infrastructure, city design and building, and environmental plan (National Tsunami Hazard Mitigation Program, NTHMP, 2001). The Hilo Downtown Development Plan was changed by the Downtown Hilo Redevelopment Plan under the authority of Chapter 27 about management of Flood Control based on the tsunami hazard map in 1985. 4. The direct involvement of marginalized group; the elderly, the poor, the needing special physical and mental issues, women, and minorities in planning and mitigation process (P. M. Blaikie, 1994; Tobin & Montz, 1997). In cities of developing countries like Indonesia, informal housings have always been significant issue as the result of rapid urbanization and land scarcity. In Indonesia, the term of informal housings refers to unplanned settlement areas that developed spontaneously and organically (Patton & Subanu, 1988). This informal housing usually occupies in marginal land, such as river bank, or illegal or insecure land with lack of basic infrastructure like water services and sanitation, and low housing quality and environment. People living in these informal areas are the most vulnerable to natural disaster like tsunami. This condition is exacerbated often this informal housing located in natural disaster-prone areas. Numerous strategies have been tried by cities to reduce and transform these areas. One of successfully strategies is the involvement the community living in informal housing. Other groups that must be also addressed in public participation are the elderly, the poor, the needing special physical and mental issues, women, and minorities in planning and mitigation process (P. M. Blaikie, 1994; Tobin & Montz, 1997) because they have a limited capacity to cope with tsunami event and impact. Involving these marginalized people in the decision-making process will enable them

to understand local conditions and how to deal with the tsunami impact. Their local knowledge and experience can contribute also to framing mitigation policies that are developed by government and policy makers who may be unaware of the specificities of local conditions. Most importantly, a mitigation policy that incorporates marginalized group and their needs and concerns in its process and implementation will have a better chance of success than a plan in which the marginalized groups have no say. Land Use and Development Regulation

The Land use and development regulation is critically important in mitigation hazards management. It can be the primary tool for hazard mitigation at the community level with the most straightforward, cost-effective strategy and local approaches (Burroughs, 2011; Johnson,

Samant, Frew, Samant, & American Planning Association. Planning Advisory Service, 2005;

Saunders & Kilvington, 2016; A. K. Schwab & Brower, 2008). The regulation of land use can reduce the exposure of urban residents to tsunami by controlling the amount, timing, density quality, and location of new development or redevelopment (A. K. Schwab & Brower, 2008).

However, development in disaster vulnerable area are greatly shaped by urban land use policies, and those local land use adoption, in turn, greatly influenced by federal/ national and state/provincial incentives scheme (Farber, 2010)

The development of planning policies to mitigate the impact of natural disaster like tsunami requires an assessment of the severity, extent and frequency of the hazard in order to evaluate the degree risk (Johnson et al., 2005). Therefore land-use planning for the mitigation tsunami impact should be based on criteria establishing the nature and degree of the risk present and its potential impact (Bell, 1999). The results of the assessment then can be translated into development regulations. The main practical limitations on land use planning for disaster mitigation like tsunami are as follow (Smith, 2004) :

1. Lack of knowledge about the location, recurrence interval and hazards potential of events which might affect small parts of urban areas; 2. The presence of extensive existing development;

3. The infrequency of most events and the difficulty of maintaining community awareness and the ongoing avoidance of hazard-prone land; 4. High costs of hazard mapping, including detailed inventories of land use, structures, occupancy levels, etc.; 5. The high cost of many mitigation measures, especially structural responses; 6. Political resistance to land use controls on philosophical grounds; 7. “rent-seeking” process which pass on the costs to others. Some strategies and techniques of land-use planning to mitigate tsunami impact are:

1. Adopting a zoning ordinance to limit exposure of new development in tsunami prone area (National Tsunami Hazard Mitigation Program, NTHMP, 2001). This approach is important since the coastal cities especially in developing countries are under pressure to provide housing and public infrastructure as the consequence of rapid urbanization (Kreimer et al., 2003). This strategy also can control the type of development and uses allowed to meet the mitigation standards (National Tsunami Hazard Mitigation Program, NTHMP, 2001; A. K. Schwab & Brower, 2008) (Figure 2-26).

Figure 2-26. Downtown redevelopment plan for Hilo, Hawaii using the seven key principles for incorporating tsunami risk into design (Source: Modified from National Tsunami Hazard Mitigation Program (U.S.) , 2001).Designing for tsunamis: seven principles for planning and designing for tsunami hazards (p.27)

2. A Shoreline setback to protect beaches and its natural features (e.g. dunes, mangroves, coral reef) to reducing impact (Beatley, Brower, & Schwab, 2002; Burroughs, 2011; Edward, Terazaki, & Yamaguchi, 2006; National Tsunami Hazard Mitigation Program, NTHMP, 2001). The regulation for setback aims to arrange the allocation order of land use for tsunami protection and safety while also preserve the natural features like mangrove that can reduce the tsunami energy (Figure 2-27).

Figure 2-27. The Schematic land use and design regulation of reconstruction plan for Banda Aceh City from coastal area to settlement area. Top: shore area, bottom: ring and relief road (Source: The Study on the Urgent Rehabilitation and Reconstruction Support Program for Aceh Province and Affected Areas in North Sumatra, Japan International Cooperation Agency (JICA), Badan Perencanaan Pembangunan Nasional (Bappenas), and Provincial Government of Nanggroe Aceh Darussalaam, Banda Aceh, 2005).

3. Designation of undeveloped vulnerable areas to keep development at a minimum level (D. Godschalk, 2009; National Tsunami Hazard Mitigation Program, NTHMP, 2001). This strategy is effective in areas that have not been developed and need a comprehensive regulation and assessment for adoption. 4. Plan of adequate safer areas for extended future growth to prevent the losses, damages; and potential conflict caused by tsunami (D. Godschalk, 2009; A. K. Schwab & Brower, 2008). It aims to manage the development of cities while securing the safety of community (Figure 2-28).

Figure 2-28. The Schematic land use and design to anticipate the development growth under the tsunami mitigation approach (Source: Spatial Planning of Banda Aceh city, Indonesia for 2009- 2029, 2009)

5. Protect existing development through redevelopment, retrofit, and land re-use plans to decrease impacts (National Tsunami Hazard Mitigation Program, NTHMP, 2001). The urban renewable program can be an opportunity to asses and to determine whether the existing development met with the tsunami mitigation policy. The cost is the issue that also need to be addressed. Land use can have an important role in lessening potential damages losses in areas already developed. Tsunami mitigation-based land use can seek to combine the beneficial use of known hazard-prone area with a minimum of hazards loss and expenditure (Smith, 2004). The reconstruction program also provides land re-use plan and redevelopment, for instance following the Tsunami event in February 2010, the Geo-PUC as requested by The City of Constitution, Chile, developed modeling based on last tsunami information as worst scenario integrate mitigation actions in reconstruction phase. In order to allow redevelopment based on certain degree of feasibility, a narrower is defined as high risk area (Zone 1) which restricts residential development and is subject to mitigation actions that would allowed development in zone 2 (Figure 2-29). To carry out redevelopment in Zone 2 government adopted following mitigation actions (Geo-PUC, 2010) as follow: 1. Restriction Zone 1. Avoidance and planed forest including greenbelt mitigation park. 2. Restriction Zone 2: Building codes including tsunami resistant construction. 3. Zone 1 + Zone 2. Evacuation plan including network of evacuation routes and safe Points.

Figure 2-29. Map for restriction Zones in Constitucion City, Chili (Source: adapted from MINVU, 2010)

Land and Property Acquisition

Land and property acquisition has several advantages over strictly regulatory approaches like zoning. The acquisition method ensures that the land and properties can be controlled, managed and used that are compatible with natural hazard mitigation by a government agency or nonprofit organization, and removing any law disputes over a regulatory taking (Asian

Development Bank, 2016; Burroughs, 2011; A. K. Schwab & Brower, 2008). However, the main obstacle to acquisition is high cost (A. K. Schwab & Brower, 2008). The issue of property right in local system context must be scrutinized since it contains a great deal of political weight while also having some degree of constitutional rights protection (Farber, 2010). The cost of maintenance and preservation of acquired lands also another factor that need to be considered

(A. K. Schwab & Brower, 2008). The acquisition policy can be done in some strategies as follow:

1. Acquisition of undeveloped vulnerable areas to prevent the development for mitigation (Burby et al., 2000; National Tsunami Hazard Mitigation Program, NTHMP, 2001). This method allows the government agencies or nonprofit entities applied the mitigation measure without any legal obstacles while also cheaper that acquisition of developed ones (A. K. Schwab & Brower, 2008). Public acquisition of tsunami-prone area is the most direct measure available to local government and is one of the most sustainable effective measure (Tobin & Montz, 1997). But undeveloped land acquisition is high cost and local government rarely have the resources for outright purchase. These acquired undeveloped land can be controlled to protect public safety by functioning it as open space, low-density recreational facilities, controlling development in the public interest such as leasing for low- intensity use (A. K. Schwab & Brower, 2008; Smith, 2004) 2. Relocation of existing development to safer areas to remove risks for the improvement of social, environment, and economy of residents (Menoni & Pesaro, 2008). This is the most challenge method to be taken because of expensive cost. In developing countries, other issue for relocation is the social conflict that may occur due to lack of regulation and the good governance (Doberstein & Tadgel, 2015). This approach only can be done if the assessment shows the community is in a high vulnerability condition and may have a hardship if the tsunami struck. The effective communication and public participation is key to ensuring the success of implementation especially for communities living in cities in developing countries like Indonesia. 3. Restriction of development rights for owners to develop for mitigation purpose (Burroughs, 2011; Kaplowitz, 2000). This restriction must consider the legal system in property where the properties located. For instance, in USA the concept of “bundle of sticks” for properties right may be applied for mitigation for instance the “transfer of development” right. In Indonesia system context, the restriction of development can be adopted through exercising power of local government to release the development permission.

Transportation Plan

Transportation plan and land use development plan are strongly linked; hence, therefore, the transportation element can support land use principles that reduce the community’s vulnerability to hazards like tsunami (A. K. Schwab & Brower, 2008). Yet, the basic approach for mitigating the tsunami impact through transportation planning is by adopting policies that support other mitigation measures employed. Some transportation strategies that can be adopted are as follow:

1. Transportation Plan that reduces the development expansion in tsunami prone areas (Burby et al., 2000; D. Godschalk, 2009). The connection between transportation and land use is an essential component of the transportation plan. In the tsunami

100

mitigation context, transportation policy can have a strong implication on land use policy and development in tsunami areas. 2. Transportation plan for guiding urban growth to less vulnerable areas (Burby et al., 2000; D. Godschalk, 2009). Transportation plan that allocates the resource for infrastructure development to less tsunami prone urban areas may attract other parties and the community to develop and clustering their activities within such area. 3. Transportation plan that expedites the evacuation and rehabilitation process (D. Godschalk, 2009; Stepanov & Smith, 2009). Another method to be enacted is ensuring that transportation plan includes securing the system and infrastructure to withstand the effects of tsunami so that they still function in the evacuation and rehabilitation effort.

Environmental Management Plan

The environment and disasters are inherently linked while they are interacting with the human community in complex ways. Reducing environmental quality may affect natural processes that can escalate vulnerability (International Strategy for Disaster Reduction., 2004; A.

K. Schwab & Brower, 2008). For instance, massive damage to coral reefs and degradation of mangrove forest swamps can reduce their natural capacity to absorb or cushion the kinetic energy of the tsunami surge. The environmental system also is believed having a main role to mitigate the impact of natural hazards like tsunami (Burby et al., 2000; Cochard et al., 2008).

The environmental management plan can effectively be implemented with the other mitigation measures through regulations, incentives, and acquisition for private landowners or cooperation with non-profit conservation or land trust agencies (A. K. Schwab & Brower, 2008). An effective environmental management plan to ensure that natural system may mitigate the impact can be accomplished in some of the following ways:

101

1. Environmental management plan which maintain and restore natural protective ecosystem from tsunami (D. Godschalk, 2009; A. K. Schwab & Brower, 2008). This plan ensure that urban stakeholders prioritize the environmental in urban development by minimizing the impact. The environmental plan also can maintain the sustainability program to protect the environmental for tsunami mitigation purpose for example prohibiting the mangrove forest for logging (Figure 2-30).

Figure 2-30. Graphical scheme of environmental protection and mitigation function (Source: Green Coast - the Tsunami Response project of Wetlands, 2005. Retrieved from http://southasia.wetlands.org/WhatWeDo/Allourprojects/tabid/639/mod/60 1/articleType/ArticleView/articleId/10/Green-Coast--the-Tsunami- Response.aspx)

2. Environmental management plan which provides incentives to development located outside of natural protective ecosystem areas affected by tsunami (D. Godschalk, 2009). The environmental interest and development can be seen as a trade-off effort. Therefore, environmental plan may encourage the parties for not to develop in vulnerable area through incentive as the reciprocal program for instance reducing the taxes, rebating development permit rebates, subsidizing insurances and other schemes. 3. Environmental management plan that identifies tsunami effects for environmental impact assessment in the plan, design and intensity of development (Shaw, 2006). The environmental plan can require the official agency to assess the development proposal based on the tsunami mitigation policy. It may be enacted as a requirement for development permits.

102

Housing Strategy

Housing is the important element in physical planning that need to acknowledge as they are particularly vulnerable to some natural hazards. For instance, much public and publicly subsidized affordable housing are vulnerable because the building quality and poor locational choice (A. K. Schwab & Brower, 2008). Tsunami mitigation plan for housing and settlement should be incorporated in physical planning because it manages the high concentration of people in the urban area. The Housing strategies include:

1. High-density housing policy to make easier communication, coordination, and movement under tsunami (Japan International Cooperation Agency, JICA, 2005). High density form is common in urban areas due to land scarcity. In high density housing, communities are encouraged to live close to one another (Burgess & Jenks, 2000). Communication and coordination between the inhabitants and disaster officials is easier during a disaster because of this physical concentration. In reconstruction projects for the citizen of Sendai high density is one strategy for tsunami reduction and housing reconstruction project to protect lives. As mentioned in "Sendai City Earthquake Disaster Reconstruction Plan, 2012", the strategy aims to revitalize the social condition, while recovering the economic condition using local resources like agricultural, combined with energy-saving and new energy projects for an energy supply especially for housing demands (Sendai City, 2012). Nevertheless, it is also a fact that the implications of raising density like housing occasionally bring it in conflict with other party’s objective pursued by strong vested interest. The process of planning and implementation of converting land-use to higher density may involve several powerful groups like developers, and landowners (Sendai City, 2012). 2. Housing relocation to safer areas to reduce the consequences of social, economic and environmental aspects in community regardless their economic and social status (Sendai City, 2012). It is viewed that this approach will bring the consequence of high cost and social disruption. Yet, the policy must be done based of comprehensive analysis. For example, the relocation can be done if the high-density housing located in the high-prone area with lack of mitigation infrastructure. The reconstruction phase can be an opportunity to implement this approach for example, Sendai City in the reconstruction process requires the housing relocation the safer area to increase the level of protection to public (Figure 2-31).

103

Figure 2-31. Relocation of housing to designated safety areas (Source: The Current State of Reconstruction in Sendai City, 2012）

3. Housing upgrading for mitigation in the safe informal settlement area (Mukherji, 2014; Silas, 1984). Cities in developing countries are comprised of large sections of informal housings. The community living in these areas are the most vulnerable groups, therefore the housing upgrading is required to reduce vulnerability. It is important to involve people living in these informal housing during the upgrading process. 4. Housing strategy that requires clustered building and tower plan for the evacuation function (Budiarjo, 2006). This strategy develops several buildings in cluster form and connected to an assigned high-rise building. This connected building tower functions as an evacuation area during disaster events as well as temporary housing in reconstruction phase after tsunami (Figure 2-32).

Figure 2-32. Clustered and tower building schematic for evacuation purpose (Source: Designed by Author)

104

5. Housing strategy demanding block orientation and arrangement not to obstruct or allow tsunami waves to pass (Budiarjo, 2006). Building block orientation is required to avoid blocking tsunami waves directly. This arrangement also must create the space between to allow wave pass through to minimize damage. This strategy also need to incorporate with building regulations (Figure 2-33 and 2-34).

Figure 2-33. Proposed orientation (Source: Budiarjo, A., 2006. Evacuation shelter building planning for tsunami-prone area; a case study of Meulaboh city, Indonesia)

Figure 2-34. Avoided orientation (Source: Budiarjo, A., 2006. Evacuation shelter building planning for tsunami-prone area; a case study of Meulaboh city, Indonesia)

6. Housing strategy that demand functional arrangement in the block for instance public activities in lower floor while residential in the higher level to avoid waves reaching (National Tsunami Hazard Mitigation Program, NTHMP, 2001). In multi- use building, residential spaces and other activities involving many people are planned located in the upper floors where inundation cannot reach. The ground floor can function as a parking lot and commercial use. This plan will let the waves go through the building to reduce the loss of life.

Fiscal and Taxation

Capital and budgeting planning have a great influence on the pattern of urban development (Burroughs, 2011; Coppola, 2015; A. K. Schwab & Brower, 2008). On the one hand, it can support the mitigation program, on the other hand, it can discourage it. The capital

105

and budgeting planning for spending may strengthen resilience of community when mitigation program is specifically included in comprehensive public facility and land management policy

(A. K. Schwab & Brower, 2008). For instance, the financial allocation and the chosen location in safer areas for public facilities like public school, fire stations and other public necessities can be decided concurrently. Financial regulation measures can also discourage development in hazardous areas because of the great significance of the profit motive in promoting land conversion (Smith, 2004; Tobin & Montz, 1997).

The use of financial incentives and disincentives affect development indirectly by altering the relative advantage which people may see in building in a hazard zone. For instance, any government program that provides grants, loans, tax credits, insurance or other type of financial assistance has a large profound consequence on both public and private development

(Smith, 2004; Tobin & Montz, 1997). However, research indicates that capital and budgeting improvement may be ineffective for directing development in urban area that have already over capacity for development except redevelopment scheme, or the condition where business parties like developers have a capability to develop the infrastructure necessary for their own developments (Henry, 2000).

Nevertheless, in developing countries like Indonesia, governments and politicians tend to spend infrastructure to maintain their high public standing. As the consequence, the allocation of projects is intended to rise their popularity over mitigation programs that may not deliver a benefit in the short run, such as allocation budgeting in tsunami-prone areas. In line with that, there are some strategies that can be used to push the agenda of mitigation in fiscal and taxation framework including:

1. The capital improvement planning and budgeting to limit expenditure on infrastructure to discourage development in prone areas (D. Godschalk, 2009;

106

National Tsunami Hazard Mitigation Program, NTHMP, 2001). Like transportation plan consequences, the connection among public capital allocation for infrastructure such transportation system and land use is strongly linked. Therefore, the limitation of capital and budgeting in tsunami area will discourage the development in tsunami prone areas and reduce the exposure to vulnerability of the communities. 2. Reduce taxation (incentive) for decreasing land use intensity or restriction development of lands to limit development in hazard prone areas (Burby et al., 2000; Burroughs, 2011; Coppola, 2015; A. K. Schwab & Brower, 2008). Individuals and businesses can involve into mitigation efforts that reduce impact through financial incentives like taxation reduction. This approach can alter and modify the perspective and behavior of people over the tsunami mitigation. 3. Impact taxes (disincentive) to fund the added public cost of mitigation for development in vulnerable areas (D. R. Godschalk, 1999; A. K. Schwab & Brower, 2008). An additional development impact tax can be used for new construction in tsunami prone areas. To implement this strategy, Government must carefully assess the effect on the long-term growth of the economy and use appropriate tsunami hazard maps as the tool for analyzing Public Emergency Infrastructure

Providing public emergency infrastructure is a critical point in tsunami mitigation.

Generally, it functions as an escape destination point during tsunami event. The allocation of public emergency infrastructure must be estimated carefully in order to serve the affected people proportionally. According to some studies, public emergency infrastructure includes escape buildings, escape bridges, emergency bases, evacuation towers and embankments (Japan

International Cooperation Agency, JICA, 2005; Sendai City, 2012).

1. Escape building as temporary sheltering of residents and visitors in areas where there is less evacuation time. After early warning system warns people, there will be an evacuation time. In this limited time, escape buildings or evacuation buildings (ESB) functions as temporary shelters for those failing to reach higher ground. They must be located along escape roads and within reachable distance by walking or running. Its evacuation floors must be designed higher than the estimated tsunami inundation level and can be also designed as tower building. 2. Escape bridge as temporary sheltering for residents and visitors in areas where there is fewer evacuation time. An escape bridge must be located along the relief road network and its structure raised above the tsunami inundation level as forecasted in the tsunami hazard map. The bridge crest must be designed sufficiently large enough to accommodate many people standing temporarily with strong structure withstanding tsunami forces. 3. Emergency base (e.g. open space, a building) as escape destination point, rescue main base, relief and temporary housing. Emergency base can be open space or a building functioning as escape destination point, rescue main base as well as relief and

107

temporary housing. A central park, which normally has public and recreation uses, also can be utilized as emergency base (Figure 2-35). Open space assigned as emergency base must be planned and designed with mitigation standard to accommodate and serve the affected people.

Figure 2-35. An integrated tsunami evacuation shelter system in city of Kochi-shi, Japan (Source: Clouds Architecture Office, 2012)

4. Evacuation Tower for the temporary sheltering and evacuation for residents and visitors in zones where there is less evacuation time. Similar to other vertical evacuation facilities, evacuation tower must be located along the relief road network with structure above the inundation level as predicted in the tsunami hazard map. 5. Embankment for the temporary evacuation when tsunami struck with less evacuation time. Embankment facilities not only can function to block tsunami’s surge from entering the urban area but also can be a temporary evacuation (Figure 2-36). During the great East Japan Tsunami, embankments successfully function as protection and evacuation measures.

Figure 2-36. Raised Road for embankment (Source: The Current State of Reconstruction in Sendai City, 2012)

108

Evacuation

An evacuation plan aims to educate communities how to escape safely during an emergency in limited time when a tsunami strike. Ideally, every individual should be familiar with several ways to leave the affected area and know a safe meeting place nearby them to minimize the loss of life. The method of evacuation can be categorized into two models; Horizontal evacuation and

Vertical Evacuation and they may be used solely or together in tsunami evacuation plan (Figure

2-37).

Figure 2-37. Vertical and horizontal evacuation plan in Japan (Source: Nagao I., 2005. Disaster Management in Japan, Fire and Disaster Management Agency (FDMA), Ministry of Internal Affairs and Communication, Japan.)

The implementation of these methods needs to consider the available evacuation time, land topography, infrastructure and facilities as well as wave run-up speed and inundation level

(Budiarjo, 2006; National Tsunami Hazard Mitigation Program, NTHMP, 2001):

1. Tsunami evacuation plan that is developed by municipality with full participation of residents based on the inundation scenarios for comprehensive plan and dissemination (Western States Seismic Policy Council, 2011)(Figure 2-38). When developing the evacuation plan, it would be helpful to look at a wide variety of potential evacuation routes within the vulnerable areas. Developing an evacuation plan means that an agency should do an assessment to determine what, if any, physical or social obstacles in plan that could obstruct the evacuation process. For these reasons,

109

involving the public to participate is the best way to collect the information at community level for the effectiveness while indirectly raising the awareness and knowledge of evacuation to communities.

Figure 2-38. The Hilo City’s tsunami evacuation map (Source: The Multi-Hazard Mitigation Plan, 2017. Retrived from http://apps.pdc.org/tsunami/hawaii/01_Hawaii.pdf)

2. Providing procedures for agreement with properties owner that designated for evacuation building to advance evacuation plan (National Tsunami Hazard Mitigation Program, NTHMP, 2001). In the condition where the privately-owned buildings assigned as evacuation shelter, a procedure for agreement should be established and negotiated fairly between government and these owners. The owners also must be actively involved in developing a mitigation program for physical planning. 3. The adequate procedures and systems for evacuation that notified by official warnings (National Tsunami Hazard Mitigation Program, NTHMP, 2001). The actions taken in the early minutes of a tsunami are critical. A prompt warning to people to evacuate can save lives or reduce the loss of lives. Therefore, providing adequate procedures and systems with accurate information for evacuation will help public emergency officials to issue warning to people at the right time.

110

4. The comprehensive education programs such as routine exercise to maintain awareness and to instill effective response individuals. A tsunami disaster is a rare event. However, once it strikes there will be massive scale destruction to coastal communities and infrastructure. Therefore, it requires an effort to maintain an evacuation program when the risk is perceived as infrequent (Paton 2008). Every individuals or society should know in advance what specific actions to make before an event, what to do during tsunami event, and what actions to take in evacuation process. Regular routine exercise is a good example to educate communities that can be carried out directly in public facilities like schools or hospitals. 5. The effective information means to form an effective response of evacuees (Oktari, Munadi, & Ridha, 2014). To disseminate information on a tsunami-procedures and warning, the government or other agencies can use effective media. Public officials; the media of television, radio, newspapers, social media; and other conventional communication parties can disseminate the evacuation plan effectively, responsibly, and speedily to communities. In addition, they need to be aware of evacuation procedures to do that threatens the community they serve. 6. Maintain the evacuation program over the long term through regular reviewing and revision by all city stakeholders (Paton et al., 2008). Evacuation program need to adjust with the growing urban development and community needs therefore it is a continuous process. The review may focus on how to coordinate the evacuation plan between agencies, how the evacuation decision-making process operates, how evacuation of communities can be better communicated and coordinated, what kind of information coastal communities require and how they can access such information for evacuation. The process of review need to involve the community for education and dissemination information of evacuation. A Case Study of Constitucion City, Chile have taught us the importance to review the tsunami mitigation planning particularly for evacuation plan (Figure 2-39). According to PRES report (2010), although Constitucion City has developed the tsunami countermeasure guide development, but due to a low frequency of tsunami events (last 1835 and 1906 in Constitucion), revisions were not conducted regularly by government and public therefore mitigation measures are on a constant trade off with other community’s interest like tourism, housing etc. As the consequence, The Tsunami event in February 2010 caused 60 people died and 8.239 people lost their homes. One of the finding is the limitation of evacuation due to lack of information and infrastructure problem as the consequence for not conducting regular reviewing.

111

Figure 2-39. Map of tsunami damages by Tsunami 2010. Source INE 2010. Inundated area covers 34% of urban area (Source: INE, 2010)

Emergency Road Network Plan

In the physical plan, it is necessary to plan and design emergency roads to support the mobility of evacuation and aid efforts (Budiarjo, 2006). It must be part of transportation plan and connected well with safer areas surrounding tsunami-prone areas. The emergency road network plan can be classified as escape roads and relief roads (Japan International Cooperation Agency,

JICA, 2005).

1. Escape road to accommodate people in the hazard zone to escape in a short time as possible (Budiarjo, 2006). Escape road mainly function to accommodate people in the hazard zone to escape from tsunami in a short time as possible. Escape buildings or vertical escape and signage must be provided along the escape road for the people who failed to evacuate in time (Budiarjo, 2006; Japan International Cooperation Agency, JICA, 2005) (Figure 2-40).

112

Figure 2-40. The integration emergency road with other mitigation measures (Source: Sendai City, 2011)

2. Relief roads to serve treatment effort; first-aid, evacuation, and the supply of relief materials. Relief roads serve treatment effort; first-aid, evacuation, and the supply of relief materials. It may be planned with specific construction to avoid major damages after the disaster to function immediately (Japan International Cooperation Agency, JICA, 2005). Transportation Plan

Coastal infrastructures can decrease destructive effect of the tsunamis with specific development and artificial structures. They lessen the impact by modifying the environment or by interfering with the increasing natural disaster vulnerability (A. K. Schwab & Brower, 2008).

However, development of coastal infrastructure in tsunami-prone area need to assess the local geography, topography, seismic structural performance and finance (Chu, Wardani, & Iizuka,

2013; A. K. Schwab & Brower, 2008). The types of coastal infrastructure for mitigation purpose in tsunami-prone area can include:

1. Detached breakwater to protect the adjacent coastal line from tsunami waves. It is located on offshore area to protect the coastal line by reducing incoming tsunami wave energy (Huang, Yim, & Lin, 1999). 2. Seawall to protect infrastructure, settlement and nature behind from destructive tsunami wave. Its concrete structure is built along the shoreline parallel to the beach. Seawall may protect infrastructure and settlement behind and reduce coastal line erosion (Environment Waikato Regional Council, EWRC, 2007). However, the cost is main issues especially in developing countries. 3. Floodgates to restrain wave run up from estuary in case of tsunamis flood (Edward et al., 2006). Floodgates are an adjustable system that can control tsunami flow for reducing the impact in affected cites. The floodgates also may adjust and control flooding that occur regularly in the cities in Indonesia.

113

4. Canals to dissipate the tsunami’s wave energy and reducing its impact (Nakaza, Schaab, & Rahman, 2017). Canals can aid delay the tsunami’s wave arrival time and decrease the wave’s velocity and energy; yet, another structural countermeasure must be incorporated to meet the effectiveness. In tsunami prone cities in Indonesia, canals also can function to control regular flooding even in some cities can serve as transportation system. 5. High raised road is used as a restraint measure for tsunami inundation in plain areas (Suppasri et al., 2013). The elevation of roads can be raised to serve as secondary or tertiary tsunami barriers (Figure 2-41). In the 2011 Great East Japan Tsunami, the raised road could withstand the tsunami waves before reaching inland (Sendai City, 2012). The infrastructure, zoning, and land use planning can be integrated to develop a multiple defense to minimize the tsunami impact.

Figure 2-41. Tsunami measurement for reconstruction and mitigation (Source: The Current State of Reconstruction in Sendai City, 2012）

Coastal Forest

Coastal forest can effectively reduce the tsunami’s kinetic energy (Chatenoux & Peduzzi,

2007). It can be an alternative solution to artificial structures which may affect environment change along shoreline. Success factors in coastal forest development includes; the width of forest; slope of the forest; tree density and height; presence of forest shore habitats (seagrass meadows, coral reef, dunes); distance from tectonic plate; size and speed of tsunami (estimate); and angle of tsunami incursion relative to the coastline (Alongi, 2008; Barbier, 2008; Hadi,

Latief, & Muliddin, 2003). During the December 26 tsunami in Indonesia, mangrove forest could tolerate destructive waves without showing any apparent damage and protected the settlement

114

areas behind it (Chatenoux & Peduzzi, 2007). The strategy of coastal forest for mitigation can comprise:

1. Dense coastal forests along the coasts to reduce the devastating impact of tsunamis by absorbing the waves' energy (Unnikrishnan, Singh, & Kharat, 2012) (Figure 2-42).

Figure 2-42. Ikonos imageries of pre-and post the 2006 West Java tsunami shows the role of coastal forest to reduce tsunami at the Pangandaran Beach, Indonesia (Source: CRPS 2006.Retrieved from www.crips.nus.edu.sg)

2. Roadside trees and premises forest to capture floating objects so that the secondary damage can be controlled. The type of trees need to be assessed regarding with its strength and flexibility to face the tsunami energy and debris collision (Figure 2-44). In the normal days, roadside trees and premises forest can be functioned as a wind damage prevention measure, shade creation and landscape.

Figure 2-44. A case of tsunami debris captured by premise forest (Source: Imai, K., A. Hayashi, and F. Imamura, 2012. An investigation for trapping floating objects during tsunami due to align trees, J. JSCE, Ser. B2. Coastal Engineering, 68(2).

115

Vital Infrastructure and Critical Facilities

Certain public facilities need special attention in the mitigation program for physical planning to minimize destruction. Vital infrastructures must continuously function to ensure the operation of community. Therefore, it is important that vital infrastructure is rapidly repaired following a tsunami. The failure to maintain or repair this functionality may cause more damage and loses to communities. According to NTHMP (2001), these include transportation systems and utilities as described in Table 2-6.

Table 2-6. Vital infrastructure . Roads, highways, bridges, parking lots and structures, and traffic control system . Railroads track beds, bridges, and rail and switching yards for freight and passengers . Transit system (rail, trolley, tram, and motor coach, storage and Transportation maintenance facilities, power system and substations, control systems, System bridges, tunnels, tubes . Airports and control towers . Maritime ports, and maritime traffic control system, marine terminals, loading/unloading facilities; storage facilities (including tank farms), docks, and ship moorings; piers, seawalls, and bulkheads

. Electrical generation, transmission, substations, and distribution systems . Natural gas production; processing, storage, transmission, pump, and distribution systems . Cellular systems, switching stations, antenna, and tower Utility . Land line communication systems: switching stations, trunk lines, and data lines. System . Cable system for television, radio, and data . Potable water systems; wells, water supply sources, storage, pumps, and treatment and distribution systems . Pipelines that transport oil, fuels, and other petroleum products . Storm water runoff facilities; drainage, and pipelines Source: As modified from NTHMP. (2001). Designing for tsunamis: Seven principles for planning and designing for tsunami hazards. Seattle, Wash.: National Tsunami Hazard Mitigation Program.

Critical facilities are also crucial because they function to serve inhabitants. Critical facilities can be categorized into 3 (three) classification; essential services, special occupancy structures and hazardous facilities. Table 2-7 shows in detail of critical facilities;

116

Table 2-7. Critical facilities . Police station Essential . Firehouses . Hospitals with surgery, acute care, or emergency rooms Services . Emergency operations and communications facilities and equipment . Garages and shelters for emergency vehicles and aircraft

. Standby power-generating equipment for essential services . Tanks or other containing water or other fire-suppression materials or Essential equipment required to protect essentials, hazardous, or specials Services occupancy facilities . Permanent lifeguard’s stations

. Schools . Universities and colleges Special . Residential treatment centers and nursing and convalescent homes Occupancy . Retirement communities . Large-occupancy structures Structures . Power-generating stations and other utility facilities needed for continuous operations

. Fuel docks and storage Hazardous . Spent nuclear fuel storage . Chemical storage facilities Facilities . Rail tank cars and truck with chemicals . Munitions storages, loading docks, and harbors Source: As modified from NTHMP. (2001). Designing for tsunamis: Seven principles for planning and designing for tsunami hazards. Seattle, Wash.: National Tsunami Hazard Mitigation Program.

To secure that vital infrastructure and critical facilities may operate to serve the community following tsunami, based on the NTHMP (2001) guidelines, some programs that can be adopted are:

1. Locate new vital infrastructure and critical facilities outside vulnerable areas. 2. The plan needs to examine the location outside of vulnerable area for infrastructure and critical facilities. The location should be equally efficient and accessible on a daily basis compare to locations in vulnerable areas. 3. Protect existing vital infrastructure and critical facilities in hazard prone area that incorporate with design standards (e.g. reinforced walls and columns) to protect against impact forces and scour. In cases, some existing vital infrastructure and critical facilities are located in a tsunami hazard area because alternative locations outside vulnerable areas are not efficient and inaccessible; therefore, additional protection are required to meet with safety standards.

117

4. Relocate existing infrastructure of critical facilities to safer areas. This policy only can be done if based upon on assessment these infrastructure and critical facilities may be disrupted for longer time following the tsunami or it may cause the secondary effect for example the leaking of nuclear reactor caused by collision. However, it must be noted that cost is crucial issue. 5. Prepare emergency plans to cope with the emergency situation and expedite recovery. Providing such plan aim to secure that vital infrastructure and critical facilities are easily to be fixed at the short time to function immediately for serving community. Warning Systems

Warning system aims to warn inhabitants to evacuate before the tsunami arrives (Devi,

Sunanda, Kumar, Kumar, & Kumar, 2016; United Nations International Strategy for Disaster

Reduction, UNISDR, 2007). Principally, the development of an early warning system considers the tsunami travel time and evacuation time (Budiarjo, 2006). The tsunami travel time is defined as the available time for evacuation of people in disaster prone areas (Budiarjo, 2006). After an earthquake, the automatic tsunami warning system in several minutes calculate to determine whether to alarm or not for evacuation. The remaining time to evacuate those to a safer place before the tsunami waves arrive is defined as the evacuation time (Budiarjo, 2006).

Warning systems constitute combinations of tools and processes embedded in institutional structures and coordinated by different agencies. The tsunami warning systems are composed of four components: risk knowledge, a technical monitoring and warning service, dissemination of warnings to people, and community awareness and preparation to respond

(Devi et al., 2016; Shaw, 2006; United Nations International Strategy for Disaster Reduction,

UNISDR, 2015). Warning services is the core of these systems that operate depending on predicting and forecasting on reliably 24 hours a day. The warning systems follow the standards as follow:

1. Tsunami forecasts and warning to alert and warn inhabitants to evacuate before the tsunami arrives by disaster authorities. 2. Providing apt information transmission method for evacuation process (e.g. television, radio, disaster administration wireless communications, nationwide warning system, or mobile phone)

118

Buildings Design and Construction

During the tsunami, it is strongly recommended that building and construction can protect people. The most effective way is to locate the building beyond tsunami run-up reaching.

The buildings must have the ability to withstand tsunami and earthquake force while serve as temporary housing following tsunami (National Tsunami Hazard Mitigation Program, NTHMP,

2001).

To formulate performance measurement in building design and construction, the US

NTHMP (2001) and Budiarjo (2001) recommends some specific factors: site location and the design configuration, application of structural and non-structural design codes; utilities reliability; designers qualification; and construction quality. Yet, the application of tsunami mitigation in building design and construction has a strong relation to the enforcement of building regulation standards. These standards should be applied to all new development or existing buildings which are under reconstruction, repair, rehabilitation, or alteration stage. Saatçioğlu, (2009) confirms that performance of buildings can withstand the tsunami forces if designed based on engineering stadards. (Saatçioğlu, 2009).

Conceptual Map

The literature reviewed in this research provides a framework to understand the factors

and indicators leading to and the outcomes of tsunami impact mitigation when integrated with

physical planning. Admittedly more approaches and factors contribute to a community’s

mitigation effort to reduce tsunami impacts. However, this study understands that covering all

the possible variables for measuring tsunami mitigation impact particularly in Makassar City,

Indonesia exceeds the capacity of this research. As described in mitigation measures for tsunami

impact mitigation, the general idea can be summarized as follow:

119

Table 2-8. Variables, dimensions and Indicator for tsunami impact mitigation in Makassar City, Indonesia Variables Dimension Indicators SOCIAL Public Public education & risk communication program (e.g. education and training) to reduce the Awareness community’s vulnerability.

The development of comprehensive tsunami hazard maps (inundation maps, & evacuation maps) with public participation for raising public’s awareness.

The direct involvement of marginalized group (the elderly, the young families, the poor, other needing special physical and mental attention, and ethnic minorities) in planning and mitigation process.

Evacuation Tsunami evacuation plan that is developed by municipality with full participation of residents based on the inundation scenarios for comprehensive plan and dissemination

Providing procedure for agreement with properties owner that designated for evacuation building to advance evacuation plan.

The adequate procedures and systems for evacuation that notified by official warnings

The comprehensive education programs such as routine exercise to maintain awareness and to instill effective response individuals

The effective information means to form an effective response of evacuees

Maintain the evacuation program over the long term through regular reviewing and revision by all city stakeholders.

ECONOMICS Land and Acquisition of undeveloped vulnerable areas to prevent the development for mitigation Property Acquisition Relocation of existing development to safer areas to remove risks for the improvement of social, environment, and economy of residents

Restriction of development rights for owners to develop for mitigation purpose.

120

Table 2-8. Continued Variables Dimension Indicators ECONOMICS Transportation Transportation Plan that reduce the development expansion in tsunami prone areas Plan Transportation plan that guiding urban growth to less vulnerable areas

Transportation plan that expedite the evacuation and rehabilitation process

Fiscal and The capital improvement planning and budgeting to limit expenditure on infrastructure to Taxation discourage development in prone areas.

Reduce taxation (incentive) and insurance for decreasing land use intensity or restriction development of lands to limit development in hazard prone areas

Impact taxes (disincentive) to fund the added public cost of mitigation for development in vulnerable areas

Risk Transfer, Insurance program to reduce future losses to private properties facilities, and financial Sharing, and consequences from tsunami Spreading

ENVIRONMENT Environment Environmental management plan which maintain and restore natural protective ecosystem from tsunami

Environmental management plan which provide incentives to development located outside of natural protective ecosystem areas from tsunami

Environmental management plan that identify tsunami effects in environmental impact assessment in assessing plan, design and intensity of development for mitigation interest.

INFRASTRUCTURE Public Escape building as temporary sheltering of residents and visitors in areas where there is less Emergency evacuation time Infrastructure Escape bridge as temporary sheltering for residents and visitors in areas where there is fewer evacuation time

121

Table 2-8. Continued Variables Dimension Indicators INFRASTRUCTURE Public Emergency base (e.g. open space, a building) as escape destination point, rescue main base, relief Emergency and temporary housing. Infrastructure Evacuation Tower for the temporary sheltering and evacuation for residents and visitors in zones where there is less evacuation time

Embankment for the temporary evacuation when tsunami struck with less evacuation time

Emergency Escape road to accommodate people in the hazard zone to escape in a short time as possible Road Network Plan Relief roads to serve treatment effort; first-aid, evacuation, and the supply of relief materials

Coastal Detached breakwater to protect the adjacent coastal line from tsunami waves Infrastructure Seawall to protect infrastructure, settlement and nature behind from destructive tsunami wave

Floodgates to restrain wave run up from estuary in case of tsunamis flood.

Canals to dissipate the tsunami’s wave energy in reducing impact

High raised road is applied as a restraint measure for tsunami inundation in plain areas

Control Forests Dense coastal forests along the coasts to reduce the devastating impact of tsunamis by absorbing the waves' energy

Roadside trees and premises forest to capture floating objects so that the secondary damage can be controlled.

Vital Locate for new vital infrastructure and critical facilities outside vulnerable area Infrastructure and Critical Protect existing vital infrastructure and critical facilities in hazard prone area that incorporate with Facilities design standards (e.g. reinforced walls and columns) to protect against impact forces and scour.

Relocate existing infrastructure and critical facilities in safer areas

122

Table 2-8. Continued Variables Dimension Indicators Prepare emergency plans to cope with the emergency situation and expedite recovery.

Warning Tsunami forecasts and warning to alert and warn inhabitants to evacuate before the tsunami arrives Systems by authorities Providing apt information transmission method for evacuation process (e.g. television, radio, disaster administration wireless communications, nationwide warning system, or mobile phone)

Buildings Adopt and enforce proper building codes and design standards to incorporate with tsunami impact design and construction

TSUNAMI Housing High-density housing policy to make easier communication, coordination, and movement under tsunami

Housing relocation to safer areas to reduce the consequences of social, economic and environmental aspects in community regardless their economic and social status.

Housing upgrading for mitigation in the safe informal settlement area Housing strategy that requires clustered building and tower plan for evacuation function Housing strategy demanding block orientation and arrangement not to obstruct or allow tsunami waves to pass

Housing strategy that demand functional arrangement in the block for instance public activities in lower floor while residential in the higher level to avoid waves reaching.

Land Use and A Zoning ordinance to limit exposure of new development in tsunami prone area Development Regulation A Shoreline setback to protect beaches and its natural features (e.g. dunes, mangroves, coral reef) to reducing impact

123

Table 2-8. Continued Variables Dimension Indicators TSUNAMI Land Use and Designation of undeveloped vulnerable areas to keep development at a minimum level MITIGATION Development Regulation Plan of adequate safer areas for extended future growth to prevent the losses, damages; and potential conflict caused by tsunami

Protect existing development through redevelopment, retrofit, and land re-use plans to decrease effect

124

Figure 2-46 illustrates the conceptual map and hypotheses that will lead to this research.

The model consists of five variables which are Social, Economics, Environment, Infrastructure, and Tsunami Mitigation. The model categorized in twenty-one dimensions which assumed to be influenced by fifty-three indicators. They are also associated with each other.

Figure 2-46. The conceptual map and Hypotheses (Source: Author)

Statement of the Hypotheses

This study connects various latent constructs to assess their structural relationships with each other and Tsunami Impact Mitigation Measures. In accordance with the theoretical perspective; Social, Economics, Environment, Infrastructure are the remaining four latent exogenous constructs in the model. Based on the research, theoretical and case studies, this research develops four hypotheses as follow:

1. H1: There is a positive relationship between social and tsunami impact mitigation; 2. H2: There is a positive relationship between economics; and tsunami impact mitigation; 3. H3: There is a positive relationship environment and tsunami impact mitigation; 4. H4: There is a positive relationship between infrastructure and tsunami impact mitigation.

125

CHAPTER 3 THE METHODOLOGY

This section provides the methodology that was used in conducting this research. This research employs quantitative research methods (i.e. multivariate analysis) to analyze empirical data that were collected via survey methodology (Creswell, 2009). The methodology chapter explains study variables, power analysis, sampling and sample size justification, data collection process, data analysis, and human subject issues.

Study Variables

This research uses four exogenous; social, economics, environment, infrastructure, and one endogenous latent variable; tsunami mitigation. The model is categorized in sixteen dimensions including; Public awareness; land use and development regulation; land and property acquisition; transportation plan; environmental management plan; housing strategy; fiscal and taxation; risk transfer, sharing, and spreading; public emergency infrastructure; evacuation; emergency road network plan; coastal infrastructure; control forests; vital infrastructure and critical facilities; warning systems; buildings design and construction. These sixteen dimensions are independent variables and directly predict tsunami impact mitigation measures. Fifty-four indicators are constructed to evaluate factors influence dimension factors. Study variables are developed and illustrated in Table 3-1.

126

Table 3-1. Operational Definitions of Study Variables Variables Dimensions Code Indicators Measurement Operationalization Level SOCIAL Public PA11 Public education & risk Ordinal Participants are asked communication program (e.g. to answer the (Exogenous) Awareness education and training) to reduce questions in a 5 item the community’s vulnerability. Likert scale ranges PA12 The development of from (1) Not comprehensive tsunami hazard important to (5) Very maps (inundation maps, & evacuation maps) with public important participation for raising public’s awareness. PA13 The direct involvement of marginalized group (the elderly, the young families, the poor, other needing special physical and mental attention, and ethnic minorities) in planning and mitigation process. Evacuation E101 Tsunami evacuation plan that is Ordinal Participants are asked developed by municipality with to answer the full participation of residents based questions in a 5 item on the inundation scenarios for Likert scale ranges comprehensive plan and from (1) Not dissemination important to (5) Very E102 Providing procedure for agreement with properties owner that important designated for evacuation building to advance evacuation plan. E103 The adequate procedures and systems for evacuation that notified by official warnings

127

Table 3-1. Continued Variables Dimensions Code Indicators Measurement Operationalization Level SOCIAL(Exogenous) Evacuation E104 The comprehensive education Ordinal Participants are asked programs such as routine exercise to answer the to maintain awareness and to instill questions in a 5 item effective response individuals Likert scale ranges E105 The effective information means to from (1) Not form an effective response of important to (5) Very evacuees E106 Maintain the evacuation program important over the long term through regular reviewing and revision by all city stakeholders. ECONOMICS Land and LPA31 Acquisition of undeveloped Ordinal Participants are asked Property vulnerable areas to prevent the to answer the (Exogenous) Acquisition development for mitigation questions in a 5 item LPA32 Relocation of existing development Likert scale ranges to safer areas to remove risks for from (1) Not the improvement of social, important to (5) Very environment, and economy of residents important LPA33 Restriction of development rights for owners to develop for mitigation purpose. Transportation TP41 Transportation Plan that reduce the Ordinal Participants are asked Plan development expansion in tsunami to answer the prone areas questions in a 5 item TP42 Transportation plan that guiding Likert scale ranges urban growth to less vulnerable from (1) Not areas important to (5) Very TP43 Transportation plan that expedite important the evacuation and rehabilitation process

128

Table 3-1. Continued Variables Dimensions Code Indicators Measurement Operationalization Level ECONOMICS Fiscal and FT71 The capital improvement planning Ordinal Participants are asked Taxation and budgeting to limit expenditure to answer the (Exogenous) on infrastructure to discourage questions in a 5 item development in prone areas. Likert scale ranges FT72 Reduce taxation (incentive) for from (1) Not decreasing land use intensity or important to (5) Very restriction development of lands to limit development in hazard prone important areas FT73 Impact taxes (disincentive) to fund the added public cost of mitigation for development in vulnerable areas Risk Transfer, RTS81 Insurance program to reduce future Ordinal Participants are asked Sharing, and losses to private properties, public to answer the Spreading infrastructure, critical facilities, questions in a 5 item and financial consequences from Likert scale ranges tsunami from (1) Not important to (5) Very important ENVIRONMENT Environmental EMP51 Environmental management plan Ordinal Participants are asked Management which maintain and restore natural to answer the (Exogenous) Plan protective ecosystem from tsunami questions in a 5 item EMP52 Environmental management plan Likert scale ranges which provide incentives to from (1) Not development located outside of important to (5) Very natural protective ecosystem areas from tsunami important

129

Table 3-1. Continued Variables Dimensions Code Indicators Measurement Operationalization Level ENVIRONMENT Environmental EMP53 Environmental management plan Ordinal Participants are asked Management that identify tsunami effects in to answer the (Exogenous) Plan environmental impact assessment questions in a 5 item in assessing plan, design and Likert scale ranges intensity of development for from (1) Not mitigation interest. important to (5) Very important INFRASTRUCTURE Public PE91 Escape building as temporary Ordinal Participants are asked Emergency sheltering of residents and visitors to answer the (Exogenous) Infrastructure in areas where there is less questions in a 5 item evacuation time Likert scale ranges PE92 Escape bridge as temporary from (1) Not sheltering for residents and visitors important to (5) Very in areas where there is fewer evacuation time important PE93 Emergency base (e.g. open space, a building) as escape destination point, rescue main base, relief and temporary housing. PE94 Evacuation Tower for the temporary sheltering and evacuation for residents and visitors in zones where there is less evacuation time PE95 Embankment for the temporary evacuation when tsunami struck with less evacuation time

130

Table 3-1. Continued Variables Dimensions Code Indicators Measurement Operationalization Level INFRASTRUCTURE Emergency Road EPRN111 Escape road to accommodate Ordinal Participants are asked Network Plan people in the hazard zone to escape to answer the (Exogenous) in a short time as possible questions in a 5 item Likert scale ranges from (1) Not EPRN112 Relief roads to serve treatment important to (5) Very effort; first-aid, evacuation, and the important supply of relief materials Coastal CI121 Detached breakwater to protect the Ordinal Participants are asked Infrastructure adjacent coastal line from tsunami to answer the waves questions in a 5 item CI122 Seawall to protect infrastructure, Likert scale ranges settlement and nature behind from from (1) Not destructive tsunami wave important to (5) Very CI123 Floodgates to restrain wave run up from estuary in case of tsunamis important flood. CI124 Canals to dissipate the tsunami’s wave energy in reducing impact CI125 High raised road is applied as a restraint measure for tsunami inundation in plain areas Control Forests CF131 Dense coastal forests along the Ordinal Participants are asked coasts to reduce the devastating to answer the impact of tsunamis by absorbing questions in a 5 item the waves' energy Likert scale ranges CF132 Roadside trees and premises forest from (1) Not to capture floating objects so that imortant to (5) Very the secondary damage can be controlled. important

131

Table 3-1. Continued Variables Dimensions Code Indicators Measurement Operationalization Level INFRASTRUCTURE Vital VICF141 Locate for new vital infrastructure Ordinal Participants are asked Infrastructure and and critical facilities outside to answer the (Exogenous) Critical Facilities vulnerable area questions in a 5 item Likert scale ranges from (1) Not VICF142 Protect existing vital infrastructure imortant to (5) Very and critical facilities in hazard important prone area that incorporate with design standards (e.g. reinforced walls and columns) to protect against impact forces and scour. VICF143 Relocate existing infrastructure and critical facilities in safer areas

VICF144 Prepare emergency plans to cope with the emergency situation and expedite recovery. Warning Systems WS151 Tsunami forecasts and warning to Ordinal Participants are asked alert and warn inhabitants to to answer the evacuate before the tsunami arrives questions in a 5 item by authorities Likert scale ranges WS152 Providing apt information from (1) Not im transmission method for ortant to (5) Very evacuation process (e.g. television, radio, disaster administration important wireless communications, nationwide warning system, or mobile phone) Buildings design BDC161 Adopt and enforce proper building Ordinal and construction codes and design standards to incorporate with tsunami impact

132

Table 3-1. Continued Variables Dimensions Code Indicators Measurement Operationalization Level TSUNAMI Housing Strategy HS61 High-density housing policy to Ordinal Participants are asked MITIGATION make easier communication, to answer the (Endogenous) coordination, and movement under questions in a 5 item tsunami Likert scale ranges HS62 Housing relocation to safer areas to from (1) Not im reduce the consequences of social, ortant to (5) Very economic and environmental important aspects in community regardless their economic and social status. S363 Housing upgrading for mitigation in the safe informal settlement area HS64 Housing strategy that requires clustered building and tower plan for evacuation function HS65 Housing strategy demanding block orientation and arrangement not to obstruct or allow tsunami waves to pass HS66 Housing strategy that demand functional arrangement in the block for instance public activities in lower floor while residential in the higher level to avoid waves reaching. Land Use and LUD21 A Zoning ordinance to limit Ordinal Participants are asked Development exposure of new development in to answer the questions Regulation tsunami prone area in a 5 item Likert scale LUD22 A Shoreline setback to protect ranges from (1) Not im beaches and its natural features ortant to (5) Very (e.g. dunes, mangroves, coral reef) important to reducing impact

133

Table 3-1. Continued Variables Dimensions Code Indicators Measurement Operationalization Level TSUNAMI LUD23 Designation of undeveloped Ordinal Participants are asked MITIGATION vulnerable areas to keep to answer the (Endogenous) development at a minimum level questions in a 5 item Likert scale ranges LUD24 Plan of adequate safer areas for from (1) Not im extended future growth to prevent ortant to (5) Very the losses, damages; and potential conflict caused by tsunami important LUD25 Protect existing development through redevelopment, retrofit, and land re-use plans to decrease effect

134

Sampling

Research aims to assess the effectiveness of tsunami impact mitigation measures in

Makassar city, Indonesia. The assessment uses the Makassar’s residents consisting of 1.700.571 million people as the research population (Makassar Statistical Bureau, 2017) The sample frame for respondents was derived from data of the Government of Makassar of civil registration agency. Quota sampling is used to ensure that sample group represents certain characteristics of the population/ specific groups selected by the study. The respondents representing characteristic are grouped into three clusters and are identified from derived. These groups are:

1. loss experiencing stakeholders which those groups who bear the losses arising from tsunami natural hazard exposures and/or the cost arising from efforts to mitigate the effects of such exposure; residents (owner or renter), workers and public visitors, financial institutions and mortgage guarantors; 2. Mitigation-involved parties that who must either make the basic public decisions to mitigate the effects of tsunami exposures, or who must engage in the direct extension of mitigation-producing services including State and federal policy makers; local policy makers; local and state planners and building officials; scholars/practitioners of urban planning, urban design and architecture; insurers; and 3. Other parties concerning with disaster mitigation including land speculators or developers; opponent of governmental regulations; advocates of governmental economy; opponents of natural hazard programs; activist of non-government organization; and other parties.

In the study, the following criteria are used in the selection of respondents. All respondents: adults between 18 to 65; meet one of the above characteristic group; resident of

Makassar city; the balance of gender of female and male is encouraged but not required. Only individuals able to agree with the informed consent and complete the survey in Bahasa Indonesia or English are included. This study does not involve the vulnerable group as defined by the Head of Institute of Science Indonesia No. 1, 2016 including; pregnant women and fetuses, minors, prisoners, persons with diminished mental capacity, and those who are educationally or economically disadvantaged.

135

As the study aims to develop model representing the relationship between the latent variables of interest, and the relationship between the latent variables, this study uses the structural equation modeling (SEM). Determining sample size requirements for structural equation modeling (SEM) is a challenge. A study of Boomsma and Hoogland (2001) suggests that any sample size larger than 200 is good enough to minimize nonconvergence problem in an

SEM (Boomsma & Hoogland, 2001). While Kline (2005) recommends multiplying number variables by 10 in order to determine proper sample size (Kline, 2011). Bentler et al. (1987) offers a moderate way for calculating sample size (Bentler & Chou, 1987). They recommend multiplying number of parameters with 5 for an adequate sample size. Due to the difficulties in data collection process and relatively small dataset in hand, Boomsma and Hoogland’s (2001) approach is used to meet the minimum criteria at least which is 200 respondents.

Given the data that average online response would be 60% (Tourangeau & Plewes, 2013) the online questionnaires were sent to 336 respondents. The quota was distributed in proportion;

(1) 112 respondents or 33.33% for loss experiencing stakeholders group, (2) 112 respondents or

33.33% for mitigation-involved parties; and (3) 112 respondents or 33.33% for other parties concerning with disaster mitigation. In the final stage, the selected 332 respondents list is developed based on the criteria of research and data of the Government of Makassar of civil registration agency. Researchers provided a sufficient time to complete the survey for 5-7 days

(Tourangeau & Plewes, 2013).

Analysis and Sample Size Calculations

The power of statistical is the probability of rejecting the null hypothesis when it is false

(Utexas, 2017).Power analysis depends on the researchers’ judgment about how precise the results would be. This study uses the mainstream .05% alpha level to ensure the results of the

136

study are viable with a 95% confidence interval. The dataset meets the minimum criteria of 200 responses which is 255 responses.

Data Collection

This research was conducted by team of one principal researchers; Professor Christopher Silver,

Ph.D., FAICP (College of Design, Construction & Planning, Department of Urban and Regional

Planning); one Co-Investigator; Fahmyddin A Tauhid; and one local consultant; Mutmainnah,

ST, MT. From this point, the term ‘research team’ refers to a team of three people. The unit of analysis is the selected respondents that meet with requirements. The data for selected respondents are derived from the Government of Makassar City of civil registration agency.

Surveys are sent to the selected individual/respondent(s) that are verified from the data of civil registration agency.

Survey Construction

Integration of Tsunami impact mitigation measure with physical planning is a significantly broad study and several constructs were identified from the literature pertaining to disaster impact mitigation. Constructing a comprehensive survey questionnaire to address these constructs is a challenging task. A wide range of literature and previously administered surveys were used to construct a new questionnaire for measuring the structural relationship among study constructs. There were used to construct fifty-four questions for measuring the structural relationship among study constructs. The survey questionnaire is mostly developed based on previously research of Coppola (2015); National Tsunami Hazard Mitigation Program U.S.

(2001); and Schwab and American Planning Association/ APA (2010) with cross example of

Hilo City, Hawaii, USA; Sendai City, Miyagi, Japan; and Constitution City, Maule Chile. For all the questions, the respondents are asked to answer the questions on a five item Likert scale; (1)

Not Important;(2) Slightly Important;(3) Moderately Important;(4) Important; and (5) Very

137

important. After the questionnaire is completed, it goes through an internal review process by the doctoral committee members. The questionnaire will be modified based on feedbacks and be finalized for an external review. The survey then was translated into Indonesia language by local experts of UIN Alauddin University, Indonesia.

For the external review process, the survey questionnaire was sent out for expert reviews from an academics in UIN Alauddin University, Indonesia. These organizations also serve as the

Advisory Council of the research project. The expert reviews consist of approximately two lecturers. In total, the questionnaire was shared with 336 selected individuals. The main points that the expert highlighted were the length of the questionnaire and the language used. The language was simplified and the length was changed according to their feedback without any change the substantially meanings.

Survey Administration

A self-administered survey was used to gather data. Mixed mode survey method is used to increase possible response levels. After the survey is converted to online format, a link of survey is created to be sent to respondents. The survey instrument is designed and distributed heavily via email and social media using the web-based survey tool QUALTRIC to 336 selected respondents. To increase possible response levels, this study email and use social media to prospective respondents.

Totally, 255 responded to the survey. When compared to 336 selected respondents, that equals a 75.2 % response rate. There were item non-response errors in a non-significant number of responses. In these responses, respondents either started the survey and did not continue after first few basic questions, or they left too many missing values. These responses did not have missing values randomly. They pose a gap in the dataset and cannot be replaced with values using any kind of data imputation procedures. Therefore, these responses were deleted from the

138

dataset. After deleting these responses, 255 responses remained 253. The organizations that responded the demographic questions are heavily from public 112 or 44 %, while there were very limited responses from insurance 1 or 0.39% and developers or land speculators 1 or 0.39%.

The statistical report confirms that no responses from state/ province and federal/national policy makers; local policy makers; local government and plan and building officials;

Statistical Analysis

Descriptive statistics are presented by frequency tables for all variables separately to illustrate the characteristics of the data. Data normality, multicollinearity and missing values were detected in the analysis of descriptive statistics step. A detailed projection of descriptive statistics is presented in Chapter 4.

Structural Equation Model

Structural equation modeling is used to analyze structural relationships with a multivariate statistical analysis approach. It combines a factor analysis and multiple regression analysis to analyze the structural relationship between measured variables and latent constructs.

This statistical modeling uses endogenous variables and exogenous variables. There are two important models is used; a measurement model and structural model. The models will be described in the follow.

Assessment of Measurement Model

The measurement model represents the theory that specifies how measured variables altogether can represent theory (Byrne, 1998). The statistical method for analysis measurement model is Confirmatory Factor Analysis (CFA). CFA is a tool to validate measurement models for latent constructs with the requirement that study has strong theories of the underlying latent

139

variable structure (Byrne, 1998). Since latent variables in this study including Social, Economics,

Environment and Infrastructure cannot be directly measured, a measurement model is developed for each latent construct. Latent constructs are predicted by dimension that influenced by several indicators. This study employs four exogenous and one endogenous latent variables.

Evaluating the measurement model aims to determine the validity and reliability of the measured used to represent the construct of interest (Byrne, 1998). Building measurement models consist of three steps. These are checking the significance of the parameter estimates, checking the model fit, and the measurement models are assessed for validity (Byrne, 1998). For the first dimension of building measurement models, critical ratio and p values of each indicators of statistical significance from the regression weight are calculated. If the critical ratio for a regression weight is higher than +1.96 or lower than -1.96, or have a p value less than .05, it means that particular indicator has a statistically significant influence on the latent construct

(Byrne, 1998). The second dimension requires certain criteria to meet the model fit. There are several statistical indexes used for respective assessment. LISREL calculates these model fit based on in the following indexes (Table 3-2):

1. Model chi-square (χ2). The Chi-Square value measure the fitness of model and calculate the degree of discrepancy between the sample and fitted covariances matrices (L. Hu & Bentler, 1999). A good model fit must meet result at a 0.05 threshold (Barrett, 2007); 2. Root mean square error of approximation (RMSEA). According to Byre (1998), the RMSEA confirms how well the model, with unknown but optimally chosen parameter estimates fit the populations covariance matrix (Byrne, 1998). The index of RMSEA that range between 0.08 to 0.10 confirms mediocre fit while below 0.08 shows a good fit model (MacCallum, Browne, & Sugawara, 1996); 3. Goodness-of-fit statistic (GFI) and the adjusted goodness-of-fit statistic (AGFI). These measures are alternative to the Chi-Square test. They calculate the proportion of variance through the assessment of population covariance (Tabachnick & Fidell, 1989). For the GFI, an accepted an omnibus cut-off point is 0.90 (Shevlin & Miles, 1998); 4. Root mean square residual (RMR) and standardised root mean square residual (SRMR). The RMR and the SRMR are defined as the square root of the difference

140

among the residuals of the example covariance matrix and the hypothesized covariance model. Values for the SRMR is from 0 to 1.0 with fit model must have values less than .05 (Byrne, 1998); 5. Normed-fit index (NFI). Normed-fit index (NFI) calculates the measurement model through comparing the χ2 value of the model to the χ2 of the null model. Values NFI range between 0 and 1 values greater than 0.90 representing a good fit model (Bentler & Bonett, 1980); 6. CFI (Comparative fit index). This index is revised from the NFI for small sample size case (Tabachnick & Fidell, 1989). CFI assumes that all latent variables do not correlate or null model and compares the sample covariance matrix with a null model. CFI values range between 0.0 and 1.0 with values closer to 1.0 indicating good fit. Yet the value of CFI ≥ 0.95 is acknowledged as good fit model (L. Hu & Bentler, 1999).

Table 3-2. The Index of goodness of fit Fit Index Cutoff criteria Sources Fail to reject H0 Barret (2007), L Hu & Bentler Statistic Chi Square (χ2) (1999) Goodness of Fit Index Tabachnick & Fidell (1989), ≥ .0.90 (GFI) Shevlin & Miles (1998). Standardized Root Mean Square ≤ .05 Byrne (1998) Residual (SRMR) Root Mean Square Error of 0.08 to 0.10 = Approximation mediocre fit and ≥ MacCallum et al, 1996). (RMSEA) 0.08 = good fit ≥ .90 Non-Normed Fit Index (NNFI)

Normed Fit Index (NFI) ≥ .90 Bentler and Bonnet (1980) Incremental Fit Index (IFI) ≥ .90 Hu and Bentler (1999) Comparative Fit Index (CFI) ≥ 0.90

In the third dimension, the measurement models are assessed for reliability. It aims to test to what extent a measuring instrument can give the same relative output for the same cases or models. According to Byrne (1998), variance extract/ VE and construct reliability/CR often used to measure the validity of model. A good validity of indicators would provide a value of VE ≥

0.40 and value of CR ≥ 0.70 (Byrne, 1998).

141

There are four latent constructs in this research: social, economic, environment and infrastructure are the exogenous latent constructs while tsunami mitigation is the only endogenous latent construct. The questions for these constructs and indicators were developed earlier based on theories and case studies as the requirement to process in SEM Modelling. The measurement models shown below are for visualization purposes only and they are developed before running statistical analysis such as construct reliability, multicollinearity, and model fit.

The models later were generated based on the results of the preliminary analysis.

Social is the first exogenous latent variable in this study. This latent variable addresses the social elements that might support tsunami impact mitigation which is Public Awareness, and

Evacuation with nine indicators. Figure 3-1 below shows the social measurement model.

Figure 3-1. The social measurement model (Source: analysis)

Economics is the second exogenous latent variable for evaluation. This variable introduces the economic elements that might enhance tsunami impact mitigation that is Land and

Property Acquisition, Transportation Plan, Fiscal and Taxation with 9 indicators. Figure 3-2 shows the economic measurement model.

142

Figure 3-2. The economic measurement model (Source: analysis)

Third exogenous construct is the Environment. This construct consists of three questions which mostly focus on maintaining the relationships environmental protection and preservation while supporting tsunami impact mitigation. Figure 3-3 confirms the environment measurement model.

Figure 3-3. The environment measurement model (Source: analysis)

The last exogenous latent construct is Infrastructure. This construct recognizes Public

Emergency Infrastructure; Emergency Road Network Plan, Coastal Infrastructure, Control

Forests, Vital Infrastructure and Critical Facilities, and Warning Systems aspect with 21 questions or indicators. Figure 3-4 shows the infrastructure measurement model.

143

Figure 3-4. The infrastructure measurement model (Source: analysis)

Tsunami mitigation is the only endogenous variable in the SEM model. It has 8 indicators which address Housing issue. Figure 3-5 displays the infrastructure measurement model.

Figure 3-5. The tsunami mitigation measurement model (Source: analysis)

144

Assessment of Structural Model

Structure Equation Modeling is a popular tool used for examining the structural relationships between latent constructs. Measurement models that were built previously were used for forming a structural equation model. Social, Economic, Environment and Infrastructure are the exogenous latent constructs for predicting their relationship to support tsunami impact mitigation effort as the endogenous variable. Figure 3-6 shows the hypothesized Structural

Equation Model for this research.

Figure 3-6. The hypothesized Structural Equation Model (Source: analysis)

145

In evaluating Assessment of Structural Model, study focus on the substantive relationship of interest for instance the relation between the various endogenous and exogeneous latent varaibles. It aims to determine whether the theoretical relationship in conceptualization phase are strongly supported by the collected data. Two procedures to measure the structural model are required. These procedures are the assessment for model fitness and evaluation of causal relationship with Path analysis. The model fit applies the same indexes in evaluating the measurement model (please refer to the fit indexes in Measurement Model). The second step is to evaluate the model of causal relationship. The statistical test for the causal relation of the structural model with a significance level of 5% so that the critical value of t-value is ± 1.96. The estimation results of all the causal relationships of the research are categorized into two; first, the output showing the (t-values) to assess if the relationship happen and second, the output show the

“standardized solutions” values to assess the degree of relationship between variables.

Human Subject

As the research involves human subjects, Institutional Review Board (IRB) requires researchers to submit survey instruments for approval. It will ensure that the research conducted does not generate any harm to participants. Participation to this survey is voluntary, anonymous, and risk free. Individuals are asked to participate in this research with their own will. Participants can withdraw at any time without consequences of any kind. However, once responses have been submitted and anonymously recorded participants will not be able to withdraw from the study.

There is no harm if individuals participate in this survey.

To provide the confidentiality to participants, no personal information will be collected.

Any e-mail lists used to distribute the survey will not be shared with others, will be kept completely confidential, and will be destroyed prior to statistical analysis to ensure

146

confidentiality. Study will not also include any personal analysis or individual record keeping.

The result of study will be retained for at least 3 years after the completion of the research.

The record numbers or coding is used to manage the data for analysis with special measures to protect the subject that would link to personal identifiers. Data sources will be kept anonymous and storage in servers with password required, and only aggregate data are gathered, used, and reported. No names or identifying information of participant would be included in any publications or presentations based on collected respond. Participants in this study will be given the opportunity to receive research results by contacting the researchers as stated in the informed consent. The dissemination of research result also will be done to urban stakeholders includes; the Disaster Management Agencies of Indonesia, and the disaster management agencies of South

Sulawesi Province and Makassar City.

147

CHAPTER 4 FINDINGS

This chapter presents analysis of the collected survey data. In general, it shows the results of data screening and provides information about data preparation procedures that were conducted; shows the development and results of measurement models for each latent construct; and presents the results of the Structural Equation Model and tests the study hypotheses. The chapter consists of four sections. The first section presents descriptive statistics results. The second section presents the results of measurement model. The third, section includes the result of analyses of Structural Model. The last section provides the results for hypothesis testing.

Descriptive Statistics

The survey targeted 336 selected respondents in Makassar City, Indonesia. The researchers tried to reach these respondents through emails, and social media. The initial response rate for the survey 75.2 %. The data screening procedures showed that a few number of respondents did not answer more than 50% of the questions. These cases are deleted from the dataset. After this initial cleaning, the number of responses remains to 253 in total. The dataset is screened and treated for missing values once more with 253 cases. These variables are shown below in analysis of descriptive statistics for each latent construct.

Exogenous Variables

This study consists of four exogenous constructs which are Social, Economic,

Environment, and Infrastructure. Each construct has been screened for missing values and frequency distribution of responses.

148

Social

Social construct consists of 14 indicators. The percentage of valid responses for Social aspect is quite high. There are missing values in this construct but they account for less than 5% of total responses. Most of the questions have 2.6 % or less than 5% missing values. Only designation of undeveloped vulnerable areas to keep development at a minimum level and the effective information means to form an effective response of evacuees 2% while Public education & risk communication program (e.g. education and training) to reduce the community’s vulnerability; The direct involvement of marginalized group in planning and mitigation process; and Tsunami evacuation plan that is developed by municipality with full participation of residents based on the inundation scenarios for comprehensive plan and dissemination has no missing value (Table 4-1). For all of the questions, the respondents were asked to answer the questions on a five item Likert scale; 1 being strongly disagree and 5 being strongly agree. The response frequency distribution of each question pertaining to network development is shown in Table 4-2.

Table 4-1. The missing data of Social Variables Univariate Statistics

a Missing No. of Extremes N Mean Std. Deviation Count Percent Low High PA11 253 4.51 .699 0 .0 4 0 PA12 252 4.42 .706 1 .4 4 0 PA13 253 4.26 .733 0 .0 7 0 E101 253 4.43 .557 0 .0 0 0 E102 252 4.16 .667 1 .4 2 0 E103 251 4.36 .639 2 .8 1 0 E104 251 4.24 .741 2 .8 5 0 E105 248 4.43 .606 5 2.0 1 0 E106 251 4.25 .665 2 .8 2 0 a. Number of cases outside the range (Q1 - 1.5*IQR, Q3 + 1.5*IQR).

149

Table 4-2. The response frequency distribution of Social Variables Indicators (1) Freq (2) Freq (3) Freq (4) Freq (5) Freq Tot Freq Public education & risk communication program (e.g. education and training) to reduce the 1.18% 3 0.39% 1 3.54% 9 35.43% 90 59.45% 151 254 community’s vulnerability.

The development of comprehensive tsunami hazard maps (inundation maps, & evacuation 1.19% 3 0.40% 1 4.35% 11 43.48% 110 50.59% 128 253 maps) with public participation for raising public’s awareness.

The direct involvement of marginalized group (the elderly, the young families, the poor, other 0.00% 0 2.76% 7 8.66% 22 47.64% 121 40.94% 104 254 needing special physical and mental attention, and ethnic minorities) in planning and mitigation process.

Tsunami evacuation plan that is developed by municipality with full participation of residents 0.00% 0 0.00% 0 3.15% 8 50.00% 127 46.85% 119 254 based on the inundation scenarios for comprehensive plan and dissemination

Providing procedure for agreement with 13.04 0.00% 0 0.79% 2 33 55.34% 140 30.83% 78 253 properties owner that designated for evacuation % building to advance evacuation plan.

The adequate procedures and systems for 0.40% 1 0.00% 0 6.35% 16 49.21% 124 44.05% 111 252 evacuation that notified by official warnings

The comprehensive education programs such as 11.11 0.40% 1 1.59% 4 28 47.62% 120 39.29% 99 252 routine exercise to maintain awareness and to % instill effective response individuals

150

Table 4-2. Continued Indicators (1) Freq (2) Freq (3) Freq (4) Freq (5) Freq Tot Freq The effective information means to form an 0.40% 1 0.00% 0 3.61% 9 47.79% 119 48.19% 120 249 effective response of evacuees

Maintain the evacuation program over the long 0.40% 1 0.40% 1 9.13% 23 54.37% 137 35.71% 90 252 term through regular reviewing and revision by all city stakeholders.

151

Economics

Economics construct consists of 9 indicators. Most of the indicators have 0.6 % or less than 5% missing values which makes then ignorable, however data were treated with missing treatment. Restriction of development rights for owners to develop for mitigation purpose indicators has a missing value at 1.6 % with average 0.4% per indicator responses (Table 4-3).

The response frequency distribution of each question pertaining to network development is shown in Table 4-4.

Table 4-3. The missing data of Economic variables

Univariate Statistics a Missing No. of Extremes N Mean Std. Deviation Count Percent Low High

LPA31 252 3.85 .961 1 .4 0 0

LPA32 251 4.15 .796 2 .8 9 0 LPA33 249 4.14 .857 4 1.6 12 0 TP41 252 3.11 1.116 1 .4 0 0 TP42 252 4.15 .777 1 .4 11 0 TP43 252 4.62 .577 1 .4 1 0 FT71 252 3.94 .811 1 .4 0 0 FT72 251 3.55 .996 2 .8 7 0 FT73 251 3.99 .967 2 .8 0 0 RTS81 252 4.08 .891 1 .4 13 0 a. Number of cases outside the range (Q1 - 1.5*IQR, Q3 + 1.5*IQR).

152

Table 4-4. The response frequency distribution of Economic Variables Indicators (1) Freq (2) Freq (3) Freq (4) Freq (5) Freq Tot Freq Acquisition of undeveloped vulnerable areas to prevent the development for mitigation 1.58% 4 8.30% 21 19.76% 50 43.48% 110 26.88% 68 253

Relocation of existing development to safer areas to remove risks for the improvement of social, 0.00% 0 3.57% 9 14.29% 36 45.24% 114 36.90% 93 252 environment, and economy of residents

Restriction of development rights for owners to develop for mitigation purpose. 0.80% 2 4.00% 10 13.60% 34 43.20% 108 38.40% 96 250

Transportation Plan that reduce the development expansion in tsunami prone areas 9.09% 23 19.76% 50 32.81% 83 28.06% 71 10.28% 26 253

Transportation plan that guiding urban growth to less vulnerable areas 0.40% 1 3.95% 10 9.49% 24 52.57% 133 33.60% 85 253

Transportation plan that expedite the evacuation and rehabilitation process 0.00% 0 0.40% 1 3.56% 9 30.04% 76 66.01% 167 253

The capital improvement planning and budgeting to limit expenditure on infrastructure to 0.00% 0 5.14% 13 20.95% 53 49.41% 125 24.51% 62 253 discourage development in prone areas.

Reduce taxation (incentive) for decreasing land use intensity or restriction development of lands 2.78% 7 11.51% 29 31.75% 80 36.51% 92 17.46% 44 252 to limit development in hazard prone areas

Insurance program to reduce future losses to private properties and financial consequences 0.79% 2 4.35% 11 17.79% 45 39.53% 100 37.55% 95 253 from tsunami

153

Environment

Environment is the third latent exogenous construct. Environment consists of 3 indicators each which were measured with a question with five item Likert scale ranging from 1 to 5; 1 being strongly disagree and 5 being strongly agree. The missing values in the 3 questions of environment are mostly less than 0.8 % with all these have the equal proportion of missing value

(Table 4-5). The response frequency distribution of each question pertaining to network development is shown in Table 4-6.

Table 4-5. The missing data of Environment Variables Univariate Statistics

a Missing No. of Extremes N Mean Std. Deviation Count Percent Low High EMP51 251 4.55 .627 2 .8 2 0 EMP52 251 4.31 .687 2 .8 3 0 EMP53 251 4.18 .770 2 .8 7 0 a. Number of cases outside the range (Q1 - 1.5*IQR, Q3 + 1.5*IQR).

154

Table 4-6. The response frequency distribution of Environment Variables

Indicators (1) Freq (2) Freq (3) Freq (4) Freq (5) Freq Tot Freq Environmental management plan which maintain and restore natural protective ecosystem from 0.40% 1 0.40% 1 3.57% 9 34.92% 88 60.71% 153 252 tsunami

Environmental management plan which provide incentives to development located outside of 0.00% 0 1.19% 3 9.13% 23 46.43% 117 43.25% 109 252 natural protective ecosystem areas from tsunami

Environmental management plan that identify tsunami effects in environmental impact 0.40% 1 2.38% 6 12.70% 32 48.41% 122 36.11% 91 252 assessment in assessing plan, design and intensity of development for mitigation interest.

155

Infrastructure

The last exogenous latent variable is the Infrastructure. There are 21 indicators of this construct. Number of missing values for the indicators of organizational capacity is 1.8 %.

Detached breakwater to protect the adjacent coastal line from tsunami waves have the highest percentage of missing values 1.6 % (Table 4-7). Table 4-8 presents the frequency and percentage distribution of all the items for Infrastructure.

Table 4-7. The missing data of Infrastructure Variables Univariate Statistics

a Missing No. of Extremes N Mean Std. Deviation Count Percent Low High PE91 251 4.35 .745 2 .8 6 0 PE92 251 4.27 .800 2 .8 10 0 PE93 251 4.42 .752 2 .8 7 0 PE94 251 4.20 .834 2 .8 13 0 PE95 251 4.22 .840 2 .8 10 0 EPRN111 250 4.38 .631 3 1.2 2 0 EPRN112 251 4.33 .703 2 .8 5 0 CI121 249 4.39 .785 4 1.6 7 0 CI122 252 4.34 .748 1 .4 7 0 CI123 251 4.29 .765 2 .8 8 0 CI124 251 4.34 .671 2 .8 3 0 CI125 250 4.07 .852 3 1.2 13 0 CF131 252 4.47 .621 1 .4 3 0 CF132 250 4.38 .720 3 1.2 3 0 VICF141 251 4.33 .662 2 .8 2 0 VICF142 250 4.30 .654 3 1.2 1 0 VICF143 251 3.90 .856 2 .8 1 0 VICF144 250 4.37 .640 3 1.2 1 0 WS151 252 4.64 .606 1 .4 2 0 WS152 251 4.71 .522 2 .8 1 0 BDC161 252 4.49 .628 1 .4 1 0 a. Number of cases outside the range (Q1 - 1.5*IQR, Q3 + 1.5*IQR).

156

Table 4-8. The response frequency distribution of Infrastructure Variables

Indicators (1) Freq (2) Freq (3) Freq (4) Freq (5) Freq Tot Freq Escape building as temporary sheltering of residents and visitors in areas where there is less 0.00% 0 2.38% 6 9.13% 23 39.68% 100 48.81% 123 252 evacuation time

Escape bridge as temporary sheltering for residents and visitors in areas where there is fewer 0.00% 0 3.97% 10 9.92% 25 40.48% 102 45.63% 115 252 evacuation time

Emergency base (e.g. open space, a building) as escape destination point, rescue main base, relief 0.40% 1 2.38% 6 6.35% 16 36.11% 91 54.76% 138 252 and temporary housing.

Evacuation Tower for the temporary sheltering and evacuation for residents and visitors in zones 0.00% 0 5.16% 13 11.11% 28 42.06% 106 41.67% 105 252 where there is less evacuation time

Embankment for the temporary evacuation when tsunami struck with less evacuation time 0.40% 1 3.57% 9 13.49% 34 38.89% 98 43.65% 110 252

Escape road to accommodate people in the hazard zone to escape in a short time as possible 0.00% 0 0.80% 2 5.58% 14 47.81% 120 45.82% 115 251

Relief roads to serve treatment effort; first-aid, evacuation, and the supply of relief materials 0.40% 1 1.59% 4 6.35% 16 47.62% 120 44.05% 111 252

Detached breakwater to protect the adjacent coastal line from tsunami waves 0.80% 2 2.00% 5 8.00% 20 36.00% 90 53.20% 133 250

Seawall to protect infrastructure, settlement and nature behind from destructive tsunami wave 0.00% 0 2.77% 7 8.30% 21 41.11% 104 47.83% 121 253

157

Table 4-8. Continued Indicators (1) Freq (2) Freq (3) Freq (4) Freq (5) Freq Tot Freq Floodgates to restrain wave run up from estuary in case of tsunamis flood. 0.40% 1 2.78% 7 7.94% 20 44.44% 112 44.44% 112 252

Canals to dissipate the tsunami’s wave energy in reducing impact 0.00% 0 1.19% 3 7.54% 19 46.83% 118 44.44% 112 252

High raised road is applied as a restraint measure for tsunami inundation in plain areas 0.40% 1 4.78% 12 15.94% 40 45.02% 113 33.86% 85 251

Dense coastal forests along the coasts to reduce the devastating impact of tsunamis by absorbing 0.00% 0 1.19% 3 3.16% 8 43.08% 109 52.57% 133 253 the waves' energy

Roadside trees and premises forest to capture floating objects so that the secondary damage can 0.40% 1 0.80% 2 9.16% 23 39.04% 98 50.60% 127 251 be controlled.

Locate for new vital infrastructure and critical facilities outside vulnerable area 0.00% 0 0.79% 2 8.33% 21 47.62% 120 43.25% 109 252

Protect existing vital infrastructure and critical facilities in hazard prone area that incorporate with design standards (e.g. reinforced walls and 0.00% 0 0.40% 1 9.56% 24 49.40% 124 40.64% 102 251 columns) to protect against impact forces and scour.

Relocate existing infrastructure and critical facilities in safer areas 0.40% 1 5.95% 15 21.83% 55 47.22% 119 24.60% 62 252

Prepare emergency plans to cope with the 0.00% 0 0.40% 1 7.57% 19 46.61% 117 45.42% 114 251 emergency situation and expedite recovery.

158

Table 4-8. Continued Indicators (1) Freq (2) Freq (3) Freq (4) Freq (5) Freq Tot Freq Tsunami forecasts and warning to alert and warn inhabitants to evacuate before the tsunami arrives 0.79% 2 0.00% 0 1.98% 5 28.85% 73 68.38% 173 253 by authorities

Providing apt information transmission method for evacuation process (e.g. television, radio, disaster administration wireless communications, 0.40% 1 0.00% 0 0.79% 2 26.19% 66 72.62% 183 252 nationwide warning system, or mobile phone)

Adopt and enforce proper building codes and design standards to incorporate with tsunami 0.00% 0 0.40% 1 5.93% 15 37.55% 95 56.13% 142 253 impact

159

Endogenous Variable

There is only one endogenous variable in this study which is tsunami mitigation. Tsunami mitigation construct has 7 indicators. These indicators address housing and land use issues. Land use and regulation strategies of designation of undeveloped vulnerable areas to keep development at a minimum level has the highest missing value at 2.0 % (Table 4-9). Table 4-10 presents the frequency and percentage distribution of the items in tsunami mitigation variable.

The findings presented here are present only pre-imputation results of the data.

Table 4-9. The missing data of Tsunami Mitigation Variables Univariate Statistics

b Missing No. of Extremes N Mean Std. Deviation Count Percent Low High LUD21 252 4.42 .654 1 .4 1 0 LUD22 250 4.49 .707 3 1.2 6 0 LUD23 248 4.44 .723 5 2.0 6 0 LUD24 250 4.43 .638 3 1.2 1 0 LUD25 249 4.23 .747 4 1.6 7 0 HS61 253 4.02 .821 0 .0 16 0 HS62 251 4.00 .851 2 .8 0 0 HS63 253 3.99 .936 0 .0 0 0 HS64 253 3.68 .875 0 .0 2 0 HS65 250 3.97 .760 3 1.2 . . HS66 250 3.81 .866 3 1.2 4 0 a. Indicates that the inter-quartile range (IQR) is zero. b. Number of cases outside the range (Q1 - 1.5*IQR, Q3 + 1.5*IQR).

160

Table 4-10. The response frequency distribution of Tsunami Variables Indicators (1) Freq (2) Freq (3) Freq (4) Freq (5) Freq Tot Freq High-density housing policy to make easier communication, coordination, and movement 0.00% 0 0.00% 0 3.15% 8 50.00% 127 46.85% 119 254 under tsunami

Housing relocation to safer areas to reduce the consequences of social, economic and environmental aspects in community regardless 0.00% 0 0.79% 2 13.04% 33 55.34% 140 30.83% 78 253 their economic and social status.

Housing upgrading for mitigation in the safe informal settlement area 0.40% 1 0.00% 0 6.35% 16 49.21% 124 44.05% 111 252

Housing strategy that requires clustered building and tower plan for evacuation function 0.40% 1 1.59% 4 11.11% 28 47.62% 120 39.29% 99 252

Housing strategy demanding block orientation and arrangement not to obstruct or allow tsunami 0.40% 1 0.00% 0 3.61% 9 47.79% 119 48.19% 120 249 waves to pass

Housing strategy that demand functional arrangement in the block for instance public activities in lower floor while residential in the 0.40% 1 0.40% 1 9.13% 23 54.37% 137 35.71% 90 252 higher level to avoid waves reaching.

A Zoning ordinance to limit exposure of new development in tsunami prone area 0.00% 0 0.40% 1 7.91% 20 41.11% 104 50.59% 128 253

A Shoreline setback to protect beaches and its natural features (e.g. dunes, mangroves, coral 0.40% 1 1.99% 5 3.98% 10 35.06% 88 58.57% 147 251 reef) to reducing impact

161

Table 4-10. Continued Indicators (1) Freq (2) Freq (3) Freq (4) Freq (5) Freq Tot Freq Designation of undeveloped vulnerable areas to keep development at a minimum level 0.00% 0 2.41% 6 6.43% 16 36.14% 90 55.02% 137 249

Plan of adequate safer areas for extended future growth to prevent the losses, damages; and 0.00% 0 0.40% 1 6.77% 17 41.83% 105 51.00% 128 251 potential conflict caused by tsunami

Protect existing development through redevelopment, retrofit, and land re-use plans to 0.80% 2 2.00% 5 8.00% 20 51.60% 129 37.60% 94 250 decrease effect

162

Missing Value Analysis

Analyzing the missing values in a data set has three aims. First, missing value analysis

(MVA) identifies and describes the patterns of missing data. It addresses whether the data is missing at random or not, where they are located, how many values are missing etc (IBM, 2011).

Second, MVA estimates means, standard deviations, covariances, and correlations for different missing value methods: list wise, pairwise, regression, or expectation-maximization (IBM,

2011). Third, it calculates results for missing values to fill (impute) them based on EM or regression methods (IBM, 2011).

Missing values are common in databases and affect how study summarize and analyze dataset. This is a very important procedure that study prepare for dataset. There are several methods for eliminating missing values in a dataset as provided by SPSS software. Considering the efficiency and time constraint without break statistical rule we use the method of replace missing values. This study used method of linear interpolation. It replaced the missing value by using the linear interpolation between the value before and after the missing value. The result of replacing value is show in the Table 4-11.

163

Table 4-11. Data treatment Result Variables Case Number of Non-Missing N of Replaced Values N of Valid Result Variable Missing Values First Last Cases Creating Function 1 PA11_1 0 1 253 253 SMEAN(PA11) 2 PA12_1 1 1 253 253 SMEAN(PA12) 3 PA13_1 0 1 253 253 SMEAN(PA13) 4 LUD21_1 1 1 253 253 SMEAN(LUD21) 5 LUD22_1 3 1 253 253 SMEAN(LUD22) 6 LUD23_1 5 1 253 253 SMEAN(LUD23) 7 LUD24_1 3 1 253 253 SMEAN(LUD24) 8 LUD25_1 4 1 253 253 SMEAN(LUD25) 9 LPA31_1 1 1 253 253 SMEAN(LPA31) 10 LPA32_1 2 1 253 253 SMEAN(LPA32) 11 LPA33_1 4 1 253 253 SMEAN(LPA33) 12 TP41_1 1 1 253 253 SMEAN(TP41) 13 TP42_1 1 1 253 253 SMEAN(TP42) 14 TP43_1 1 1 253 253 SMEAN(TP43) 15 EMP51_1 2 1 253 253 SMEAN(EMP51) 16 EMP52_1 2 1 253 253 SMEAN(EMP52) 17 EMP53_1 2 1 253 253 SMEAN(EMP53) 18 HS61_1 0 1 253 253 SMEAN(HS61) 19 HS62_1 2 1 253 253 SMEAN(HS62) 20 HS63_1 0 1 253 253 SMEAN(HS63) 21 HS64_1 0 1 253 253 SMEAN(HS64) 22 HS65_1 3 1 253 253 SMEAN(HS65) 23 HS66_1 3 1 253 253 SMEAN(HS66) 24 FT71_1 1 1 253 253 SMEAN(FT71) 25 FT72_1 2 1 253 253 SMEAN(FT72) 26 FT73_1 2 1 253 253 SMEAN(FT73) 27 RTS81_1 1 1 253 253 SMEAN(RTS81) 28 PE91_1 2 1 253 253 SMEAN(PE91) 29 PE92_1 2 1 253 253 SMEAN(PE92) 30 PE93_1 2 1 253 253 SMEAN(PE93) 31 PE94_1 2 1 253 253 SMEAN(PE94) 32 PE95_1 2 1 253 253 SMEAN(PE95) 33 E101_1 0 1 253 253 SMEAN(E101) 34 E102_1 1 1 253 253 SMEAN(E102) 35 E103_1 2 1 253 253 SMEAN(E103)

164

Table 4-11. Continued Case Number of Non-Missing N of Replaced Values N of Valid Missing Values First Last Cases Creating Function 36 E104_1 2 1 253 253 SMEAN(E104) 37 E105_1 5 1 253 253 SMEAN(E105) 38 E106_1 2 1 253 253 SMEAN(E106) 39 EPRN111_1 3 1 253 253 SMEAN(EPRN111) 40 EPRN112_1 2 1 253 253 SMEAN(EPRN112) 41 CI121_1 4 1 253 253 SMEAN(CI121) 42 CI122_1 1 1 253 253 SMEAN(CI122) 43 CI123_1 2 1 253 253 SMEAN(CI123) 44 CI124_1 2 1 253 253 SMEAN(CI124) 45 CI125_1 3 1 253 253 SMEAN(CI125) 46 CF131_1 1 1 253 253 SMEAN(CF131) 47 CF132_1 3 1 253 253 SMEAN(CF132) 48 VICF141_1 2 1 253 253 SMEAN(VICF141) 49 VICF142_1 3 1 253 253 SMEAN(VICF142) 50 VICF143_1 2 1 253 253 SMEAN(VICF143) 51 VICF144_1 3 1 253 253 SMEAN(VICF144) 52 WS151_1 1 1 253 253 SMEAN(WS151) 53 WS152_1 2 1 253 253 SMEAN(WS152) 54 BDC161_1 1 1 253 253 SMEAN(BDC161) Removing Duplicates

Removing duplicates is another important procedure in data preparation because it can affect the calculation of the dataset. Removing duplicates is also an essential task to ensure researcher do not waste time screening the data multiple times. To check the duplication of data set, this study applied the “Identify Duplicates Cases” and the result is shown in the Table 4-12.

Table 4-12. The result of dataset duplicate Indicator of each last matching case as Primary

Frequency Percent Valid Percent Cumulative Percent Valid Primary Case 254 100.0 100.0 100.0

165

Assessment of Measurement Model

Confirmatory Factor Analysis

Confirmatory factor analysis (CFA) is used for assessing the validity of a latent construct like measurement model. Basically, it is testing whether the indicators of a factor sort themselves in the same with the researcher has hypothesized (Garson, 2012). For CFA, three step methods is used. First step addresses the significance of estimates of the factor loadings (λ) of each construct. Significance is determined by checking whether critical value of a λ falls within

+1.96/-1.96 range (i.e. α=.05). Factor that are not statistically significant will be removed from the measurement models. Second step is the model specification and testing. In this step, the model is tested whether it is fit or not by checking model fit statistics. Third step is the measurement models are assessed for reliability using construct reliability and variance extracted to confirm that measurement is reliable.

Social

Social is the first latent construct or variables of measurement model. The first step of

CFA is to develop a measurement model based on nine indicators. Then the model fit is tested with model fit statistics that were provided in methods section. Finally, the model is checked for reliability.

166

a. The significance of the parameter

Figure 4-1. Path of Social (t-value) (Source: Output LISREL 8.80 by researcher)

Based on LISREL output of Figure 4.1., the measurement equation for social coefficients

of each indicator has t-value ≥ 1.96 which means that all indicators are valid and

statistically significant with a significance level of 5% therefore no indicators to be

removed from the model. b. The model fit

Table 4-13. The result of model fit of Social Latent Fit Index Generic Model Fitness

Statistic Chi Square (χ2) 30.75 Good Fit Goodness of Fit Index 0.97 Good Fit (GFI) Standardized Root Mean Square Residual 0.017 Good Fit (SRMR) Root Mean Square Error of 0.037 Good Fit Approximation (RMSEA) Non-Normed Fit Index (NNFI) 0.99 Good Fit Normed Fit Index (NFI) 0.99 Good Fit Incremental Fit Index (IFI) 1.00 Good Fit Comparative Fit Index (CFI) 1.00 Good Fit

167

The Table 4-13 output shows that of GFI is 0.97. GFI cutoff value to be “good fit” ≥

0.90, it means the measurement model can be categorized as good fit. The value of

SRMR is 0.017 which is less than 0.05 confirming the model is “good fit”. Chi Square

values fall into the category of “good fit” because the value is in the range of threshold.

NNFI, NFI, IFI, and CFI values are ≥ 0.90, this means these indexes can be categorized

as good, despite RMSEA has value less than 0.08. Thus, it can be concluded that the

measured model indicates “a good fit”.

c. The model reliability

Table 4-14. The result of model reliability of Social Latent Indicators SLF Error Construct Reliability SLF SLF)2 SLF2) error CR VE Social PA11 0,65 0,42 PA12 0,63 0,40 PA13 0,63 0,40 LUD21 0,69 0,48 LUD22 0,63 0,40 LUD23 0,72 0,52 LUD24 0,7 0,49 6,11 37,332 4,164 4,16 0,900 0,500 LUD25 0,71 0,50 E101 0,75 0,56 E102 0,65 0,42 E103 0,63 0,40 E104 0,63 0,40 E105 0,69 0,48 E106 0,63 0,40

According to Hair (1998), the model can be categorized as “a good reliability” if it has a value of construct reliability ≥ 0.70. From the calculation, the value of the overall construct reliability of social is 0.90 ≥ 0.70 and variance extracted value of 0.50 ≥ 0.40. This confirms that the reliability of this measurement model is “good” and the social construct is supported by the data collected.

168

Economics

Economic is the second latent construct or variables with 9 indicators to be measured.

The same procedure is employed in the previous one; the significance of indicators to model are assessed, then the fitness of model is checked; and the last the model is calculated for reliability.

a. The significance of the parameter

Figure 4-2. Path of Economics (t-value) (Source: Output LISREL 8.80 by researcher)

Based on the output, the measurement equation for economics coefficients of each

indicator has t-value ≥ 1.96 that confirms all indicators are valid and statistically

significant with a significance level of 5% then all indicator can be used for the model.

169

b. The model fit

Table 4-15. The result of model fit of Economics Latent Generic Fit Index Fitness Model Statistic Chi Square (χ2) 43,62 Good Fit Goodness of Fit Index 0.97 Good Fit (GFI) Standardized Root Mean Square 0.031 Good Fit Residual (SRMR) Root Mean Square Error of Approximation 0.038 Good Fit (RMSEA) Non-Normed Fit Index (NNFI) 0.99 Good Fit Normed Fit Index (NFI) 0.98 Good Fit Relative Fit Index (RFI) 0.97 Good Fit Incremental Fit Index (IFI) 0.99 Good Fit Comparative Fit Index (CFI) 0.99 Good Fit

Based on the Table 4-15, the value of GFI is 0.97 that can be classified as “good fit” as

the value is more than 0.90. The value of SRMR is 0.031 that is less than 0.05 approving

a “good fit” result. Chi Square values indicates the “good fit” since it fall within category.

RMSEA value less than 0.038 that shows “no fitness”; yet all of NNFI, NFI, IFI, and CFI

values are ≥ 0.90, as the result the measured model can be categorized as “a good fit”.

c. The model reliability

Table 4-16. The result of model reliability of Environment Latent

IndicatorsIndicators SLF Error Construct Reliability 2 2 SLF SLF)2 SLF2) error CR VE EconomicsEconomics LPA31LPA31 0,64 0,59 LPA32LPA32 0,66 0,56 LPA33LPA33 0,72 0,48 6,61 43,692 4,389 5,61 0,909 0,439 TP41TP41 0,62 0,62 TP42TP42 0,75 0,44 TP43TP43 0,66 0,56

170

Table 4-16. Continued Indicators SLF Error Construct Reliability SLF SLF)2 SLF2) error CR VE Economics FT71 0,69 0,52 FT72 0,6 0,64 6,61 43,692 4,389 5,61 0,909 0,439 FT73 0,63 0,60

Table 4-16 shows that the value of construct reliability as a whole in economics is 0.909 ≥

0.70 and variance extracted value of 0.439 ≥ 0.40. This shows that the reliability of this

measurement model is “good” and the Economics construct is supported by the data

obtained.

Environment

Environment is the third latent construct or variables with 3 indicators for assessment. The similar procedure is used including the significance of indicators, the fitness of model; and the reliability.

a. The significance of the parameter

Figure 4-3. Path of Environment (t-value) (Source: Output LISREL 8.80 by researcher)

171

The figure 4.3 shows that all the calculation result for every indicator of t-value ≥ 1.96.

Hence, it can be concluded that all the indicators of environment are valid to be used for

model with significant for level of 5%. b. The model fit

Table 4-17. The result of model fit of Economics Latent

Degrees of Freedom = 0 Minimum Fit Function Chi-Square = 0.00 (P = 1.00) Normal Theory Weighted Least Squares Chi-Square = 0.00 (P = 1.00)

The Model is Saturated, the Fit is Perfect !

(Source: Output LISREL 8.80 by researcher)

Based on the Table 4-17, it can be inferred that the model produces “a perfect Fit”, that

means all goodness of fit measures has perfect value at every limit. Overall, it can be

emphasized that the measured model confirms a perfect fit.

c. The model reliability

Table 4-18. The result of model reliability of Environment Latent Indicators SLF Error Construct Reliability SLF SLF)2 SLF2) error CR VE Environment EMP51 0,64 0,59 EMP52 0,85 0,28 2,13 4,54 1,54 1,46 0,76 0,51 EMP53 0,64 0,59

Table 4-18 shows that the total value of construct reliability in environment is 0.76 ≥ 0.70

and variance extracted value of 0,51 ≥ 0,40. These results validate the reliability of

measurement model is “good” and the economics construct is supported by the data.

172

Infrastructure

Infrastructure is the last exogenous latent construct or variables with 17 indicators for assessment. The similar procedure is applied including the significance of indicators, the fitness of model; and the reliability.

a. The significance of the parameter

Figure 4-4. Path of Infrastructure (t-value) (Source: Output LISREL 8.80 by researcher)

173

The figure 4-4. confirms that every indicator of t-value ≥ 1.96 with significant for level of

5%. Therefore, all the indicators of environment are valid for model structural process.

b. The model fit

Table 4-19. The result of model reliability of Infrastructure Latent Generic Fit Index Fitness Model Statistic Chi Square (χ2) 385.88 Not Fit Goodness of Fit Index 0.87 Marginal Fit (GFI) Standardized Root Mean Square 0.030 Good Fit Residual (SRMR) Root Mean Square Error of Approximation 0.071 Good Fit (RMSEA) Non-Normed Fit Index (NNFI) 0.98 Good Fit Normed Fit Index (NFI) 0.97 Good Fit Incremental Fit Index (IFI) 0.98 Good Fit Comparative Fit Index (CFI) 0.98 Good Fit

The value of GFI is 0.87 that falls into “good fit” because the value is more than 0.90.

The value of SRMR is 0.030 that is less than 0.05 confirming a “good fit” category. Chi

Square values indicates the “good fit” since it fall within category. RMSEA value less

than 0.038 that shows “no fitness” model; however, all of NNFI, NFI, IFI, and CFI values

are ≥ 0.90, as the result the measured model is viewed as “a good fit”.

c. The model reliability

Table 4-20. The result of model reliability of Infrastructure Latent

Indicators SLF Error Construct Reliability SLF SLF)2 SLF2) error CR VE Infrastructure     PE91 0,64 0,41 14,43 208,22 9,99 9,99 0,95 0,50 PE92 0,65 0,42    

174

Table 4-20. Continued Indicators SLF Error Construct Reliability SLF SLF)2 SLF2) error CR VE Infrastructure     PE91 0,64 0,41

PE92 0,65 0,42

PE93 0,66 0,44 PE94 0,69 0,48

PE95 0,73 0,53 EPRN111 0,75 0,56 EPRN112 0,75 0,56

CI121 0,67 0,45 CI122 0,72 0,52 14,43 208,22 9,99 9,99 0,95 0,50 CI123 0,76 0,58 CI124 0,76 0,58 CI125 0,71 0,50 CF131 0,71 0,50 CF132 0,66 0,44 VICF141 0,74 0,55 VICF142 0,68 0,46 VICF143 0,57 0,32 VICF144 0,73 0,53 WS151 0,54 0,29 WS152 0,66 0,44 BDC161 0,65 0,42

Table 4-20 above shows that the value of construct reliability as a whole in Infrastructure

is 0.95 ≥ 0.70 and variance extracted value of 0.50 ≥ 0.40. These results confirm that the

reliability of this measurement model is “good” and the infrastructure latent is supported

by the data.

Tsunami Mitigation

Tsunami Mitigation is the only endogenous variable variables with 8 indicators for assessment. The similar procedure is employed including the significance of indicators, the fitness of model; and the reliability.

175

a. The significance of the parameter

Figure 4-5. Path of Tsunami Mitigation (t-value) (Source: Output LISREL 8.80 by researcher)

The figure 4-5 shows us that all the calculation result for every indicator of t-value ≥

1.96. As the results, all of indicators all are valid to be used for model with significant for

level of 5%. b. The model fit

Table 4-21. The result of model fit of Tsunami Mitigation Latent

Fit Index Generic Model Fitness Statistic Chi Square (χ2) 65.06 Good Fit Goodness of Fit Index (GFI) 0.96 Good Fit Standardized Root Mean Square 0.043 Good Fit Residual (SRMR) Root Mean Square Error of 0.072 Good Fit Approximation (RMSEA) Non-Normed Fit Index (NNFI) 0.98 Good Fit Normed Fit Index (NFI) 0.98 Good Fit Incremental Fit Index (IFI) 0.99 Good Fit Comparative Fit Index (CFI) 0.99 Good Fit

176

Based on the table 4-21 the value of GFI is 0.96 that can be categorized as “good fit”

because the value is more than 0.90. The value of SRMR is 0.043 that is less than 0.05

confirming a “good fit” model. Chi Square values shows the “good fit” because it is

within category range. RMSEA value less than 0.038 that confirms “no fitness” model;

nevertheless, all of NNFI, NFI, IFI, and CFI values are ≥ 0.90, meaning that a measured

model is categorized as “a good fit”.

c. The model reliability

Table 4-22. The result of model reliability of Tsunami Mitigation Latent

Indicator SLF Error Construct Reliability SLF SLF)2 SLF2) error CR VE Mitigation LUD21 0,72 0,52 LUD22 0,77 0,59 LUD23 0,74 0,55 LUD24 0,76 0,58 7,39 54,61 5,03 5,03 0,916 0,500 LUD25 0,73 0,53 HS61 0,72 0,52 HS62 0,57 0,32 HS63 0,57 0,32 HS64 0,57 0,32 HS65 0,66 0,44

Table 4-22 shows the value of construct reliability for tsunami mitigation is 0.916 ≥ 0.70

and Variance extracted value is 0.50 ≥ 0,40. These results validates the reliability of

measurement model is “good” and the tsunami mitigation is supported by the data.

Assessment of Structural Model

After validation of measurement models for each variable, structural equation model is developed to test the hypotheses addressing their relationships through structural model. A structural equation model with latent variables requires at least 200 sample sizes. The steps taken

177

for processing the structural model are the fitness of model; and evaluation of causal relationship with Path analysis.

a. The model fit

Table 4-23. The result of model fitness Generic Fit Index Fitness Model Statistic Chi Square (χ2) 281.19 Not Fit Standardized Root Mean Square Residual 0.060 Marginal Fit (SRMR) Root Mean Square Error of 0.065 Good Fit Approximation (RMSEA) Non-Normed Fit Index (NNFI) 0.96 Good Fit Normed Fit Index (NFI) 0.93 Good Fit Incremental Fit Index (IFI) 0.97 Good Fit Comparative Fit Index (CFI) 0.97 Good Fit The Table output to asses the model fit shows the SRMR value at 0.60. Based on the the

cutoff value criteria this value fall as “ Marginal fit”. The values of RMSEA, NFI, and

NNFI, IFI, and CFI also are categorized as “good “. Then, it can be concluded that the

model is “good fit” for the path analysis.

b. The model of causal relationship

The statistical test for the causal relation of the structural model was carried out with a

significance level of 5% so that the critical value of t-value is ± 1.96. The estimation results

of all the causal relationships of the research are categorized into two; first, the output show

the (t-values) to assess if the relationship exist (Figure 4-5) and second; the output show the

“standardized solutions” values to assess the degree of relationship between variable (Figure

4-6).

178

Figure 4-5. The Structural Model Output (t-value) (Source: Output LISREL 8.80 by researcher)

179

Figure 4-6. The Structural Model Output (standardized solutions) (Source: Output LISREL 8.80 by researcher)

180

From the output of structural model of standardized solutions (Figure 4-6), this study

calculates the determination of coefficient (R2). R2 value shows how much exogenous /

independent variable is able to explain the endogenous/ dependent variable.

The calculation of determination can be seen as follow:

Structural Equations

TSUMITG = 0.10*SOCIAL + 0.22*INFRA + 0.54*ECO + 0.046*ENVI, Errorvar.= 0.41 , R² = 0.59 (0.063) (0.071) (0.079) (0.067) 0.073) 1.59 3.10 6.82 0.69 5.61

The sum of calculation shows R² = 0.59. It can be interpreted that the social, economics,

infrastructure, and environment variables can explain 59 % of the variant of the tsunami

mitigation as the endogenous/ dependent variable while the remainders are explained by

other factors beyond this study.

Hypotheses Testing

The analyses and calculation from the structural model output (t-value) (Figure 4-5) provide necessary information about the relationship between exogenous variables and endogenous variable. The result shows whether or not there is statistically significant any relationship between Social, Economics, Infrastructure, and Environment, and Tsunami

Mitigation. Hypothesis testing is calculated with significance level 5%, so the critical t-value equal to ± 1.96. The hypothesis is accepted if t-value obtained is ≥ 1.96, while the hypothesis is not supported or rejected if t-value is <1.96.

Table 4-24. Hypotheses Testing H1 – H4 Loading Hypotheses Statement T-value T-Table Result Factor There is a positive relationship H1 between social factors and tsunami 1.59 0.10 Not Supported impact mitigation 1.96 There is a positive relationship H2 between economics; and tsunami 6.82 0.54 Supported impact mitigation

181

Table 4-24. Continued Loading Hypotheses Statement T-value T-Table Result Factor There is a positive relationship H3 between environment and tsunami 0.69 0,05 Not Supported impact mitigation; 1.96 There is a positive relationship H4 between infrastructure and tsunami 3.10 0,22 Supported impact mitigation

H1: There is a positive relationship between social and tsunami impact mitigation.

The first hypothesis in this study proposes that there is a positive relationship between social variable and tsunami impact mitigation. The hypothesized relationship is directional and social variable predicts tsunami mitigation. The results show that t-value between social factors and tsunami impact mitigation is 1.59. This shows a very weak and statistically nonsignificant relationship between two variables since the t-value less than or equal to 1.96. Therefore, it is not possible accept the hypothesis.

H2: There is a positive relationship between economics and tsunami impact mitigation.

Second hypothesis addresses relationship between economics and tsunami impact mitigation. It proposes a positive association between these two variables. The result shows that there is a positive relationship between economics and tsunami impact mitigation with t-value

6.82. The relationship between these two variables is directional and that means tsunami impact mitigation with higher economic aspect make a positive impact on mitigation. Therefore, second hypothesis is accepted.

H3: There is a positive relationship between environment and tsunami impact mitigation.

Hypothesis 3 proposes that there is a positive relationship between environment and tsunami impact mitigation. Study confirm that there is a less positive association between environment and tsunami impact mitigation since t values shows only 0.69. In other words, there

182

is not a statistically significant positive relationship between environment and tsunami impact mitigation. Therefore, third hypothesis is rejected.

H4: There is a positive relationship between infrastructure and tsunami impact mitigation.

Hypothesis 4 addresses the association between infrastructure and tsunami impact mitigation. The hypothesized relationship between two variables is directional. The finding approves that there is a positive relationship between infrastructure and tsunami impact mitigation since t-value is 3.10. Therefore, it is safe to state that there is a statistically significant relationship between infrastructure and tsunami impact mitigation or fourth hypothesis is accepted.

183

CHAPTER 5 DISCUSSIONS, IMPLICATIONS AND LIMITATIONS

This chapter presents a detailed discussion for the results of hypothesis testing.

Additionally, theoretical, methodological, and policy implications of the research findings are mentioned. The chapter acknowledges the limitations of the research and provides directions for future research.

Discussions

Social

Social variable is one of the interesting aspects of tsunami mitigation literature since it is viewed as the most fundamental factor to ensure the success of mitigation effort. Social aspect is operationalized with 9 questions pertaining to level of connectedness with other variables;

1. the Public education & risk communication program (e.g. education and training) to reduce the community’s vulnerability; 2. The development of comprehensive tsunami hazard maps (inundation maps, & evacuation maps) with public participation for raising public’s awareness; 3. The direct involvement of marginalized group (the elderly, the young families, the poor, other needing special physical and mental attention, and ethnic minorities) in planning and mitigation process; 4. Tsunami evacuation plan that is developed by municipality with full participation of residents based on the inundation scenarios for comprehensive plan and dissemination; 5. Providing procedure for agreement with properties owner that designated for evacuation building to advance evacuation plan; 6. The adequate procedures and systems for evacuation that notified by official warnings; 7. The comprehensive education programs such as routine exercise to maintain awareness and to instill effective response individuals; 8. The effective information means to form an effective response of evacuees; and 9. Maintain the evacuation program over the long term through regular reviewing and revision by all city stakeholders.

Social Latent’ indicators are valid and statistically significant with a significance level of

5% therefore no indicators need to be removed from the measurement model. The model fitness also shows that the measurement model is “a good fit” as confirmed with the most of indexes

184

value above the cutoff values. The last, the model reliability is calculated with the positive result to confirm that the measurement model for social is reliable. Hypothesized model shows a very weak and statistically nonsignificant relationship between social factors and tsunami impact mitigation variables since the t-value less than or equal to 1.96.

From the study, social variable was not a successful construct to tsunami mitigation. This is contrast with theoretical and methodological perspective explaining that social factor is the core for the success of mitigation effort. This study believes that such result may show the low level of public participation in mitigation plan for physical planning in Makassar City and it may be the remaining of up-bottom approach of dictatorship era, therefore the government agencies need to introduce more a comprehensive public participation in the respective program.

Additionally, in the context of study, a better social measurement model needs to be built using tsunami mitigation characteristics

Economics

Economic construct is another important aspect in the tsunami impact mitigation model.

It originally had 10 indicators which pertain to topics:

1. Acquisition of undeveloped vulnerable areas to prevent the development for mitigation 2. Relocation of existing development to safer areas to remove risks for the improvement of social, environment, and economy of residents 3. Restriction of development rights for owners to develop for mitigation purpose. 4. Transportation Plan that reduce the development expansion in tsunami prone areas 5. Transportation plan that guiding urban growth to less vulnerable areas 6. Transportation plan that expedite the evacuation and rehabilitation process 7. The capital improvement planning and budgeting to limit expenditure on infrastructure to discourage development in prone areas. 8. Reduce taxation (incentive) for decreasing land use intensity or restriction development of lands to limit development in hazard prone areas 9. Impact taxes (disincentive) to fund the added public cost of mitigation for development in vulnerable areas 10. Insurance program to reduce future losses to private properties, public infrastructure, critical facilities, and financial consequences from tsunami

185

Using these indicators, a measurement model was built to test whether the hypothesized model fits with observed model. The measurement model did have a model fit with all valid indicators, the fitness of model confirmed with indexes value greater that cutoff value and the measurement model is reliable with the value of construct reliability and variance extracted meet the threshold values.

In the hypothesized model, the results show that there is a positive relationship between economics and tsunami impact mitigation with t-value is 6.82. This study assumes that the high contribution of economic to mitigation program is influenced by the perspective of public that the improvement of budget policy with high allocation can directly benefit to public. Although economic construct had a considerably good model fit with keeping most of the indicators, it had somewhat practically problematic aspect. The main reason lies on competition between sector for financing while the capacity of government agencies to manage the economic sector still need to be improved. For Indonesia context, the key to solve this economic resource competition is to raise the awareness to public and government agencies that disaster mitigation is an integral part of social and economic programs, and is vital for community security and sustainability.

Environment

Environment is another critical important aspect of tsunami mitigation effectiveness at the community level. This construct addresses the indicators;

1. Environmental management plan which maintain and restore natural protective ecosystem from tsunami; 2. Environmental management plan which provide incentives to development located outside of natural protective ecosystem areas from tsunami; 3. Environmental management plan that identify tsunami effects in environmental impact assessment in assessing plan, design and intensity of development for mitigation interest. From the calculation, the measurement did have a fit with the data, therefore there is no any modifications. The significance of the all indicators are valid to be employed for model with

186

significant for level of 5%. The Environment measurement model confirms “a perfect Fit” with the reliability of measurement supported by the data collected. However, in the hypothesized testing concludes that there is a less relationship between environment and tsunami impact mitigation because t-value is 0.69 which is less than 1.96. It can be argued that the environment for the public is not viewed as main element for supporting tsunami mitigation effort. This study believes that the awareness and education on environmental issue have not fully reached since the community put the economic as the priority agenda.

Infrastructure

Infrastructure covers physical potential for supporting tsunami mitigation effort. The variable consists of 21 questions pertaining to:

1. Escape building as temporary sheltering of residents and visitors in areas where there is less evacuation time 2. Escape bridge as temporary sheltering for residents and visitors in areas where there is fewer evacuation time 3. Emergency base (e.g. open space, a building) as escape destination point, rescue main base, relief and temporary housing. 4. Evacuation Tower for the temporary sheltering and evacuation for residents and visitors in zones where there is less evacuation time 5. Embankment for the temporary evacuation when tsunami struck with less evacuation time 6. Escape road to accommodate people in the hazard zone to escape in a short time as possible 7. Relief roads to serve treatment effort; first-aid, evacuation, and the supply of relief materials 8. Detached breakwater to protect the adjacent coastal line from tsunami waves 9. Seawall to protect infrastructure, settlement and nature behind from destructive tsunami wave 10. Floodgates to restrain wave run up from estuary in case of tsunamis flood. 11. Canals to dissipate the tsunami’s wave energy in reducing impact 12. High raised road is applied as a restraint measure for tsunami inundation in plain areas 13. Dense coastal forests along the coasts to reduce the devastating impact of tsunamis by absorbing the waves' energy 14. Roadside trees and premises forest to capture floating objects so that the secondary damage can be controlled. 15. Locate for new vital infrastructure and critical facilities outside vulnerable area

187

16. Protect existing vital infrastructure and critical facilities in hazard prone area that incorporate with design standards (e.g. reinforced walls and columns) to protect against impact forces and scour. 17. Relocate existing infrastructure and critical facilities in safer areas 18. Prepare emergency plans to cope with the emergency situation and expedite recovery. 19. Tsunami forecasts and warning to alert and warn inhabitants to evacuate before the tsunami arrives by authorities 20. Providing apt information transmission method for evacuation process (e.g. television, radio, disaster administration wireless communications, nationwide warning system, or mobile phone) 21. Adopt and enforce proper building codes and design standards to incorporate with tsunami impact

The Infrastructure measurement model fall into “a fit condition” without any adjustment for data. The significance of the all indicators are valid to be employed for model with significant for level of 5%. The model passes to some important indexes and reliable for measurement as confirmed by the result meet the “fit criteria”. In the hypothesized testing, there is a strong relationship between infrastructure and tsunami impact mitigation with t-value is 3.10 that is greater than 1.96. This result shows us that public perceives that mitigation only can be reduced effectively through infrastructure development since it provides direct advantage to public.

Tsunami Mitigation.

Tsunami Mitigation is the only endogenous latent construct or variables with 11 indicators for housing assessment and land use and development regulation as follow;

1. High-density housing policy to make easier communication, coordination, and movement under tsunami 2. Housing relocation to safer areas to reduce the consequences of social, economic and environmental aspects in community regardless their economic and social status. 3. Housing upgrading for mitigation in the safe informal settlement area 4. Housing strategy that requires clustered building and tower plan for evacuation function 5. Housing strategy demanding block orientation and arrangement not to obstruct or allow tsunami waves to pass 6. Housing strategy that demand functional arrangement in the block for instance public activities in lower floor while residential in the higher level to avoid waves reaching. 7. A Zoning ordinance to limit exposure of new development in tsunami prone area

188

8. A Shoreline setback to protect beaches and its natural features (e.g. dunes, mangroves, coral reef) to reducing impact 9. Designation of undeveloped vulnerable areas to keep development at a minimum level 10. Plan of adequate safer areas for extended future growth to prevent the losses, damages; and potential conflict caused by tsunami 11. Protect existing development through redevelopment, retrofit, and land re-use plans to decrease effect The significance of the parameter confirms us that these indicators are valid for measurement as t-value ≥ 1.96 with significance of 5%. The model fit of tsunami mitigation latent is in also “a perfect Fit” with good reliability.

Implications

Theoretical

Theoretical implications concentrate on the validity of the study constructs. The result of

CFA and SEM show that social, environment, economic and infrastructure area acceptable variables in tsunami impact mitigation in physical planning process. It is confirmed because hypothesized models worked with the data even if they were modified. However, hypothesizing a multidimensional construct regarding social and environment requires a deeper scrutiny and theoretical discussions prior to operationalization since they are complex systems. Possibly, additional indicators might be added to these constructs; yet that kind of an addition requires significant theoretical discussions and justifications. It must also consider the variance of perception and awareness of issues in different locations like Indonesia. The priority to fulfill daily life needs and level of education may strongly influence the perception in tsunami impact mitigation which is reflected on “social” variable responses in this research. Therefore, it should be a topic of future research.

Methodological

Methodological implication focuses on the operationalization of the variables and survey administration. In terms of operationalization, the questions were measured with a consistent

189

scale that reduces measurement problems. No significant problem was detected with social, environment, economic, infrastructure, and tsunami mitigation constructs, therefore there is no clue of problem with their operationalization. Therefore, first methodological implication, it can be claimed that that theoretically and methodologically, social, environment, economic, infrastructure, and tsunami mitigation construct are operationalized correctly.

Second methodological implication addresses survey administration. There are high responses for questionnaire. There may be reasons for this result. First, it echoes the willing of people to participate in the issues that related to their personal and public safety. In this sense, the government or agencies can use this finding as the chance to involve more public in policy development especially in the disaster policy and plan. Additionally, the tsunami mitigation is a new issue for public’s discussion, particularly in Makassar City. Lastly, the penetration of social medias area greatly influences the level of responses. In the future, the social media can be powerful tools for survey distribution especially in Indonesia. As one of the top five social- media markets globally, Indonesia has over 79 million active social media users in 2016 represents 27.9% of the total population (E-marketer, 2016). According to E-marketer (2016) this trend is expected to grow over 31.5% / year along with Facebook as the most popular application. Social media can provide more spaces for communication and networking especially for “millennials generation” and making it as part of their lifestyle. For instance, besides sending questionnaires through email, this study also used Facebook as the platform to inform and monitor the questionaries’ responses.

Policy

This research aims to identify the relationship between social, environment, economic and infrastructure, and tsunami mitigation impact. The importance of the findings is twofold.

First, National Disaster Relief Agency of Indonesia have addressed mitigation as the priority in

190

disaster management. However, the raising issue is the lack of a metric for measuring mitigation especially in city that have its own local problem. This study presents a metric to disaster mitigation from a tsunami impact mitigation standpoint. Although it is not a comprehensive measurement, it embraces the most critical issues of effectiveness of mitigation programs in urban areas.

Second, another issue is the role of public in mitigation policy process. This study finds that despite the discussion in the academic field about how the social variable becomes the key factor in mitigation effort, yet public perception views it as not priority in disaster policy.

Although this issue needs more discussion to solve, this study argues that the level public participation and awareness still need to be improved by governments, agencies and other

Makassar’s stakeholders.

Because these two findings are important to improve the planning process, particularly in tsunami impact mitigation programs, this study aims to disseminate the findings to key urban stakeholders including the Disaster Management Agencies of Indonesia, Disaster Management

Agencies of South Sulawesi province and Makassar City Government. It intends to provide evidences to inform and empower decisions makers for good urban planning making and program efforts under limited resources. This study believes that disseminating findings to respondents, public and government is a research ethical obligation. Nevertheless, in dissemination process, researchers considers factors such as perception of findings by public, government or practitioners; local value and culture; and the communication means to reduce misperception and unnecessary conflicts.

Limitations

There are several limitations of this study. First limitation, the study population is limited with Makassar City, Indonesia. That weakens the external validity of the study results. Although

191

the study results can be generalized to other cities with similar characteristics (e.g. urban character, exposure to hazard, vulnerabilities etc.) in Indonesia, it is not possible to generalize them to other cities.

Second limitation is the demographic data for respondents. The study only limits age between eighteen and sixty-five years old without using the age categorization. The categorizing can result a different finding because it is assumed that every category of generation can have different perception on beliefs, experiences or values.

Third limitation of the study is the data collection method. The research uses a self- administered survey which makes it questionable. People might tend not to present their actual thoughts, experience and knowledge. Additionally, some of the questions in the survey could not be answered based on respondent’s knowledge. That may cause selection bias in responding to survey. In other words, respondents may choose more favorable response for themselves than the actual one. That situation causes may skewness in data.

Fourth limitation of the survey is that it is a cross-sectional study. Constructs such as social, economic, environment, infrastructure, and mitigation measures may imply a process rather than an outcome. Therefore, this study requires a comprehensive research designs and diversity experts in in the number study and observation rather than one-time observation with limited resources.

Fifth limitation is the variation of response from group of respondents. Given the report of responses, the big gap among groups shows that specific viewpoints of some key parties like government agencies cannot be included. As the result, it may influence the result in finding the research questions and hypnotizes.

192

Future Research

This study is first step of future research in tsunami mitigation field especially in the developing countries like Indonesia that have their local context and issues. Future research should focus on measuring tsunami impact mitigation, replicating the study, and include a more comprehensive perspective to mitigation efforts.

193

APPENDIX A INFORMED CONSENT FORM

DESIGNING CITIES FOR TSUNAMI IMPACT MITIGATION: EVALUATING PHYSICAL PLANNING USING STRUCTURAL EQUATION MODELS IN MAKASSAR CITY, INDONESIA Fahmyddin Araaf Tauhid Department of Urban and Regional Planning College of Design, Construction and Planning, University of Florida, USA

Dear Respondent,

I am a doctoral student in the field in the Department of Urban and Regional Planning College of Design, Construction and Planning, University of Florida, USA. As part of my dissertation for completing the program, I am conducting research under supervision of Prof. Christopher Silver, Ph.D., FAICP, and kindly I am inviting you to participate in our research.

The purpose of research is to evaluate the effectiveness of developed indicators prior to implementation of physical planning for tsunami impact mitigation in Makassar City, Indonesia. Structural equation modeling method is applied to develop and to evaluate variables in the physical planning program for tsunami impact mitigation based on the collected responds via online questionnaire.

Your participation in this survey is voluntary, and without compensation. You are free to withdraw your consent to participate and may discontinue your participation in the survey at any time without consequence. The questionnaire will take approximately 15 minutes to complete. Returning a completed survey will be taken as consent to include your information and response in study and will not be able to withdraw from the study.

Participation in the study provides an educational benefit by helping you understand how to mitigate the tsunami impact. Your respond highly contributes to the improvement of social, environment and economic conditions of inhabitants of the city of Makassar, Indonesia.

We anticipate that this study poses no potential risk other than those encountered in day-to-day life. You don’t have to answer any question you do not wish to answer. This study has been confirmed by Faculty of Science and Technology, UIN Alauddin University, Indonesia and The Government of province of South Sulawesi, Indonesia.

Any information that is obtained from you will remain confidential. No personal information will be collected. All data used to distribute the survey will be destroyed prior to statistical analysis to ensure confidentiality. Your respond will be kept in researcher’s computer and University of Florida cloud servers with username and password required. Your answers will be sent over QUALTRICS that requires a username and password. QUALTRICS does not collect identifying information (name, email address, or IP address), then your responses will remain anonymous. The result of study will be retained for at least 3 years after the completion of the research and will be available upon your request.

If you have questions this research protocol, please contact me at 352-745-9092 or via email: [email protected] or my faculty supervisor, Professor. Christopher Silver, Ph.D., FAICP at 352-294- 1435 or via email: [email protected]. Concerns about your rights as a research participant rights may

194

be directed to IRB02 office, University of Florida, Box 112250, Gainesville, FL 32611, (352) 392-0433 or via https://www.reportlineweb.com/Welcome.aspx?Client=UF

Please sign and return this copy of the letter and email to me. A second copy is provided for your records. By signing this letter, you give me permission to report your responses anonymously in the final manuscript to be submitted to my faculty supervisor as part of my dissertation work.

Thank you very much for your help and participation

Regards,

Fahmyddin A Tauhid

I have read the procedure described above for the tsunami impact mitigation survey assignment. I voluntarily agree to participate and I have received a copy of this description.

______

Signature of participant Date

ELECTRONIC CONSENT Please select your choice below. You may print a copy of this consent form for your records. Clicking on the “Agree” button indicates that

 You have read the above information  You voluntarily agree to participate  You are 18 years of age or older  You give permission to report your responses anonymously as part of research

 Agree  Disagree

195

Indonesia Version

Persetujuan menjadi Responden

Kepada Yth. Bapak/Ibu (Responden Penelitian)

Dengan Hormat, Perkenankan saya memperkenalkan diri, saya Fahmydin A Tauhid, mahasiswa program doktoral pada Jurusan Perencanaan Wilayah dan Kota, Universitas Florida, Amerika Serikat. Sebagai bagian dari penyelesaian program studi, maka saya bermaksud melaksanakan penelitian tentang mitigasi dampak bencana tsunami kota Makassar, Indonesia. Adapun judul penelitian termaksud/ Disertasi yaitu “DESIGNING CITIES FOR TSUNAMI IMPACT MITIGATION: EVALUATING PHYSICAL PLANNING USING STRUCTURAL EQUATION MODELS IN MAKASSAR CITY, INDONESIA”.

Penelitian tugas akhir ini dibawah supervisi Prof. Christopher Silver, Ph.D., FAICP, dosen pada Jurusan Perencanaan Wilayah dan Kota, Universitas Florida, Amerika Serikat. Untuk keperluan tersebut kami mohon kesediaan Bapak/ Ibu untuk menjadi responden dalam penelitian termaksud.

Tujuan penelitian ini adalah untuk mengevaluasi standar standar mitigasi untuk mengurangi dampak bencana tsunami terkhusus di kota Makassar Indonesia. Penelitian ini akan membuat standar standar tersebut dan akan diberi masukan oleh Bapak/ Ibu (responden) dalam bentuk kuisoner online. Hasil masukan Bapak/ Ibu akan dianalisa statistik dalam bentuk pemodelan berbasis “Structural equation modeling”. Pemodelan ini akan menentukan seberapa efektif standar standar mitigasi yang telah dibuat berdasarkan masukan Bapak/ Ibu.

Partisipasi Bapak/Ibu dalam penelitian ini bersifat sukarela. Bapak/ Ibu bebas untuk mengundurkan diri setiap saat tanpa ada sanksi apapun sekiranya dalam proses penyelesaian kuisoner ada hal yang menurut Bapak/ Ibu akan menyebabkan ketidaknyamanan atau konsekuensi. Untuk hal hal yang berpotensi menimbulkan konsekuensi maka Bapak/ Ibu dapat menghubungi kontak kami seperti yang tertera dalam surat ini. Bila Bapak/ Ibu telah mengirimkan respond jawaban, maka hal tersebut bersifat final. Penelitian ini telah mendapatkan ijin dari Fakultas Sains dan Teknologi, Universitas Islam Negeri Alauddin Makassar dan Pemerintah provinsi Sulawesi Selatan Indoensia.

Penelitian ini berharap Bapak/ Ibu dapat mendapatkan wawasan baru tentang usaha mengurangi dampak bencana di Kota Makassar khususnya dan Indoensia umumnya. Kontribusi bapak/ Ibu dalam penelitian ini sangatlah penting dan berharga dalam memperbaiki kondisi social, ekonomi dan lingkungan kota bagi masyarakat dari dampak bencana tsunami. Hasil penelitian ini dapat Bapak/ Ibu dapatkan dengan mengontak peneliti seperti yang termuat dalam surat ini.

Semua informasi yang Bapak/ Ibu berikan terjamin keamanan dan kerahasiaannya. Standar yang kami adalah sebagai berikut: (1) Tidak ada informasi pribadi berupa nama., email, umur, alamat, no telepon dll yang dikumpulkan. (2) semua data penelitian ditempatkan pada computer peneliti dan server universita Florida yang membutuhkan username dan password untuk mengaksesnya, (3) Survei/ kuisoner akan dikirimkan dan disediakan oleh QUALTRIC, dimana aplikasi ersebut tidak akan mengumpulkan informasi spesifik seperti email atau IP address Bapak/ Ibu, sehingga responden

196

bersifat anomin/ tanpa identitas, (4) seluruh data akan dihapus setelah hasil penelitian diterima oleh komite penguji doktoral kami. Adapun hasil penelitian akan tersimpan selama 3 tahun.

Sekiranya dalam penelitian ini, ada hal yang secara yang kurang jelas, mohon Bapak/ Ibu dapat menghubungi kami di: Prof. Christopher Silver, Ph.D., FAICP via email: [email protected] atau Fahmyddin A Tauhid via [email protected]. Bila dalam pelksanaan penelitian ini, terdapat hal yang tidak berjalan sperti yang dijelaskan dalam lembar persetujuan ini mengakibatkan kerugian, maka sdapat dihubungi langsung: University of Florida IRB Compliance Hotline at (352) 294-5549 atau The University of Florida's Web Reporting System on https://www.reportlineweb.com/Welcome.aspx?Client=UF

Setelah Ibu membaca maksud dan kegiatan penelitian diatas Selanjutnya, kami mohon kesediaan bersedia berpartisipasi dalam penelitian kami. Jika Bapak/Ibu bersedia maka mohon mengkonfirmasi tanda “ACCEPT” pada bagian akhir surat ini sebagai bukti kesediaan bapak/ ibu. Bukti konfirmasi juga menunjukkan bahwa Bapak/ Ibu telah memahami maksud dan tujuan penelitian, berpartisipasi secara sukarela, berumur 18 tahun keatas dan setuju mengijinkan responnya untuk digunakan sebagai bagian dari penelitian. Atas Bantuan dan partisipasi Bapak/ Ibu saudara dalam penelitian ini, kami mengucapkan banyak terima kasih.

Hormat Kami, Tim peneliti

197

APPENDIX B QUESTIONNAIRE TO RESPONDENTS

DESIGNING CITIES FOR TSUNAMI IMPACT MITIGATION: EVALUATING PHYSICAL PLANNING USING STRUCTURAL EQUATION MODELS IN MAKASSAR CITY, INDONESIA

This survey helps to evaluate the effectiveness of developed indicators prior to implementation of physical planning for tsunami impact mitigation in Makassar city, Indonesia. The result will contribute to the improvement of policy regarding to tsunami impact mitigation from federal, state to local level in Indonesia and the advancement of future similar research.

The survey takes about 15 minutes to complete. Your responses are confidential, and will not be revealed without your consent; only aggregate results will be made available. We would be happy to make a copy of results available upon your request.

Thank you very much for your cooperation

Contact: Professor Christopher Silver, Ph.D., FAICP Department of Urban and Regional Planning, College of Design, Construction and Planning, University of Florida, USA P.O. Box 115701 office: 331 ARCH e-mail: [email protected] phone: 352-294-1405

198

Please inform us about yourself: In which profession or position that you like to be described? (please check one apply) [ ] residents (owner or renter) in the watefront area of Makassar [ ] workers or public visitors in the watefront area of Makassar [ ] financial institutions and mortgage guarantors (Bank) [ ] state or federal or local policy makers [ ] state planners [ ] local planners [ ] building officials [ ] scholar/ practitioner of urban planning [ ] scholar/practitioner of urban design [ ] scholar/practitioner of architecture [ ] insurers or reinsurers [ ] land speculators or developers [ ] opponent of governmental regulations [ ] advocates of governmental economy [ ] opponents of natural hazard programs [ ] activist of non-government organization [ ] others

Please indicate by check ONLY ONE that apply with your level of agreement of each in the following statements using the scale: (1) Not Important;(2) Slightly Important;(3) Moderately Important;(4) Important; and (5) Very important

Tsunami Mitigation Measures (1) (2) (3) (4) (5) Not Slightly Moderately Important Very Important Important Important important 1. Public Awareness Public education & risk communication program (e.g. education and training) to reduce the community’s vulnerability. The development of comprehensive tsunami hazard maps (inundation maps, & evacuation maps) with public participation for raising public’s awareness. 2. Land Use and Development Regulation A Zoning ordinance to limit exposure of new development in tsunami prone area A Shoreline setback to protect beaches and its natural features (e.g. dunes, mangroves, coral reef) to reducing impact

199

Table Continued (1) (2) (3) (4) (5) Not Slightly Moderately Important Very Important Important Important important Designation of undeveloped vulnerable areas to keep development at a minimum level Plan of adequate safer areas for extended future growth to prevent the losses, damages; and potential conflict caused by tsunami Protect existing development through redevelopment, retrofit, and land re-use plans to decrease effect 3. Land and Property Acquisition Acquisition of undeveloped vulnerable areas to prevent the development for mitigation Relocation of existing development to safer areas to remove risks for the improvement of social, environment, and economy of residents Restriction of development rights for owners to develop for mitigation purpose. 4. Transportation Plan Transportation Plan that reduce the development expansion in tsunami prone areas Transportation plan that guiding urban growth to less vulnerable areas Transportation plan that expedite the evacuation and rehabilitation process 5. Environmental Management Plan Environmental management plan which maintain and restore natural protective ecosystem from tsunami Environmental management plan which provide incentives to development located outside of natural protective ecosystem areas from tsunami Environmental management plan that identify tsunami effects in environmental impact assessment in assessing plan, design and intensity of development for mitigation interest. 6. Housing Strategy High-density housing policy to make easier communication, coordination, and movement under tsunami Housing relocation to safer areas to reduce the consequences of social, economic and environmental aspects in community regardless their economic and social status. Housing strategy that requires clustered building and tower plan for evacuation function

200

Table Continued (1) (2) (3) (4) (5) Not Slightly Moderately Important Very Important Important Important important Housing strategy demanding block orientation and arrangement not to obstruct or allow tsunami waves to pass Housing strategy that demand functional arrangement in the block for instance public activities in lower floor while residential in the higher level to avoid waves reaching. 7. Fiscal and Taxation The capital improvement planning and budgeting to limit expenditure on infrastructure to discourage development in prone areas. Reduce taxation (incentive) for decreasing land use intensity or restriction development of lands to limit development in hazard prone areas Impact taxes (disincentive) to fund the added public cost of mitigation for development in vulnerable areas 8. Risk Transfer, Sharing, and Spreading Insurance program to reduce future losses to private properties, public infrastructure, critical facilities, and financial consequences from tsunami 9. Public emergency infrastructure Escape building as temporary sheltering of residents and visitors in areas where there is less evacuation time Escape bridge as temporary sheltering for residents and visitors in areas where there is fewer evacuation time Emergency base (e.g. open space, a building) as escape destination point, rescue main base, relief and temporary housing. Evacuation Tower for the temporary sheltering and evacuation for residents and visitors in zones where there is less evacuation time Embankment for the temporary evacuation when tsunami struck with less evacuation time 10. Evacuation Tsunami evacuation plan that is developed by municipality with full participation of residents based on the inundation scenarios for comprehensive plan and dissemination Providing procedure for agreement with properties owner that designated for evacuation building to advance evacuation plan.

201

Table Continued (1) (2) (3) (4) (5) Not Slightly Moderately Important Very Important Important Important important The adequate procedures and systems for evacuation that notified by official warnings The comprehensive education programs such as routine exercise to maintain awareness and to instill effective response individuals The effective information means to form an effective response of evacuees Maintain the evacuation program over the long term through regular reviewing and revision by all city stakeholders. 11. Emergency Road Network Plan Escape road to accommodate people in the hazard zone to escape in a short time as possible Relief roads to serve treatment effort; first-aid, evacuation, and the supply of relief materials 12. Coastal infrastructure Detached breakwater to protect the adjacent coastal line from tsunami waves Seawall to protect infrastructure, settlement and nature behind from destructive tsunami wave Floodgates to restrain wave run up from estuary in case of tsunamis flood. Canals to dissipate the tsunami’s wave energy in reducing impact High raised road is applied as a restraint measure for tsunami inundation in plain areas 13.Control Forests Dense coastal forests along the coasts to reduce the devastating impact of tsunamis by absorbing the waves' energy Roadside trees and premises forest to capture floating objects so that the secondary damage can be controlled. 14. Vital infrastructure and critical facilities Locate for new vital infrastructure and critical facilities outside vulnerable area Protect existing vital infrastructure and critical facilities in hazard prone area that incorporate with design standards (e.g. reinforced walls and columns) to protect against impact forces and scour. Relocate existing infrastructure and critical facilities in safer areas

202

Table Continued

(1) (2) (3) (4) (5) Not Slightly Moderately Important Very Important Important Important important Prepare emergency plans to cope with the emergency situation and expedite recovery. 15. Warning Systems Tsunami forecasts and warning to alert and warn inhabitants to evacuate before the tsunami arrives by authorities Providing apt information transmission method for evacuation process (e.g. television, radio, disaster administration wireless communications, nationwide warning system, or mobile phone) 16. Buildings design and construction Adopt and enforce proper building codes and design standards to incorporate with tsunami impact

Thank you very much for your valuable time and participation.

203

Indonesian Version

Mohon pilih salah satu profesi Bapak/Ibu [ ] Pemilik property pada kawasan pantai Makassar [ ] Pekerja/ Pengunjung pada kawasan Pantai Makassar [ ] Perbankan [ ] Legislator Nasional atau Daerah [ ] Perencana Nasional [ ] Perencana Daerah [ ] Pemerintah Kota bagian Manajeman Kota dan Gedung. [ ] Akademisi atau Praktisi Perencana Kota [ ] Akademisi atau Praktisi Perancangan Kota [ ] Akademisi atau Praktisi Arsitektur [ ] Asuransi [ ] Developer atau pengusaha Lahan [ ] Penggiat pemberdayaan pemerintah [ ] Penggiat pemberdayaan ekonomi masyarakat [ ] Penggiat masyarakat tahan bencana [ ] Penggiat Lembaga Swadaya Masayarakat [ ] Lain Lain

Mohon memilih SATU tanda pada jawaban yang sesuai pendapat anda dengan ketentuan: (1) Sangat Tidak Penting;(2) Tidak Penting;(3) Antara Penting dan Tidak Penting;(4) Penting; and (5) Sangat Penting

Usaha Mengurangi/Mitigasi Dampak Tsunami (1) (2) (3) (4) (5) Sangat Tidak Antara Sangat Tidak Penting Penting dan Penting Penting Penting Tidak Penting 1. Penyadaran masyarakat tentang Tsunami Pelaksanaan pendidikan dan pelatihan kepada masyarakat tentang dampak tsunami guna mengurangi resiko korban jiwa dan kerugian material Penyediaan peta potensi tsunami yang dibuat bersama antara pemerintah kota dan masyarakat

204

Table Continued (1) (2) (3) (4) (5) Sangat Tidak Antara Sangat Tidak Penting Penting dan Penting Penting Penting Tidak Penting Keterlibatan aktif masyarakat terpinggirkan (usia lanjut, keluarga miskin, berkebutuhan khusus/disabilitas dan minoritas) dalam rencana penanggulangan tsunami 2. Tata Guna Lahan dan Peraturan Fungsi Lahan Tersedianya peraturan untuk mengurangi pembangunan baru dan pembangunan kembali pada area rawan tsunami Tersedianya peraturan pelarangan pembangunan dalam jarak tertentu pada area pantai (sempadan pantai) guna mengurangi dampak tsunami Tersedianya Peraturan untuk mengurangi pembangunan pada lahan terbuka yang berada pada kawasan rawan tsunami terdapat Rencana kota yang mempertimbangkan kerawanan tsunami guna mengurangi dampak kerugian pada masyarakat Perlindungan area kota yang telah terbangun dari tsunami melalui penataan ulang kawasan dan fungsi lahan 3. Akusisi/ Pembelian lahan dan property oleh Pemerintah Pembelian lahan terbuka yang berada pada kawasan rawan tsunami oleh pemerintah untuk mengurangi dampak bencana Pemindahan kawasan terbangun ke area yang lebih aman dari tsunami guna meningkatkan kualitas hidup, ekonomi dan lingkungan masyarakat Pembatasan izin hak guna lahan untuk kepentingan pengurangan dampak tsunami 4. Perencanaan Transportasi Rencana transportasi yang tidak mendukung pengembangan pembangunan pada area rawan tsunami Rencana transportasi yang mendukung pengembangan pembangunan pada area aman dari tsunami Rencana transportasi yang menyediakan jalur evakuasi (penyelamatan) selama tsunami dan rehabilitasi (pembangunan kembali) setelah tsunami 5. Perencanan Manajemen Lingkungan Rencana manajemen lingkungan yang memelihara dan memperbaiki lingkungan seperti hutan bakau guna mengurangi dampak tsunami

205

Table Continued (1) (2) (3) (4) (5) Sangat Tidak Antara Sangat Tidak Penting Penting dan Penting Penting Penting Tidak Penting Tersedianya rencana manajemen lingkungan yang memberikan insentif bagi pembangunan ramah lingkungan guna mengurangi dampak tsunami Tersedianya rencana manajemen lingkungan yang dapat mengevaluasi proposal pembangunan guna mengurangi dampak tsunami 6. Kebijakan Perumahan Kota Kebijakan yang mewajibkan perumahan kota dengan kepadatan tinggi guna memudahkan koordinasi dan evakuasi selama tsunami Pemindahan (relokasi) perumahan kota yang berada pada kawasan rawan tsunami ke area aman dari tsunami Perbaikan permukiman kumuh kota guna mengurangi dampak tsunami Kebijakan perumahan yang mewajibkan pembangunan berbentuk blok (terkumpul) dan bangunan tinggi untuk memudahkan evakuasi Kebijakan perumahan yang mewajibkan arah dan pengaturan fisik perumahan yang dapat mengurangi dampak tsunami. Peraturan yang mewajibkan pembagian fungsi pada bangunan tinggi perumahan contoh lantai satu untuk fungsi umum dan lantai berikutnya untuk tempat tinggal untuk menghindari terpaan gelombang tsunami 7. Kebijakan Keuangan dan Pajak Kebijakan keuangan Kota yang membatasi pembangunan infrastruktur publik pada kawasan rawan terkena tsunami Kebijakan pengurangan pajak bagi pemilik lahan atau developer yang mengurangi pembangunan pada kawasan rawan tsunami Tersedianya kebijakan penambahan pajak bagi pemilik lahan atau developer yang membangun pada kawasana rawan tsunami 8. Pembagian Resiko Bencana Tersedianya program asuransi pemerintah atau swasta untuk mengurangi dampak kerugian akibat tsunami

206

Table Continued (1) (2) (3) (4) (5) Sangat Tidak Antara Sangat Tidak Penting Penting dan Penting Penting Penting Tidak Penting 9. Fasilitas Keadaan Darurat (Emergency) Pembangunan "Bangunan Evakuasi" bagi penduduk pada daerah rawan tsunami Tersedianya "Jembatan Evakuasi" bagi penduduk pada daerah rawan tsunami Continued Pembangunan "Area Darurat" contoh taman kota sebagai area kumpul evakuasi ketika tsunami, dan tempat pengungsian setelah tsunami Tersedianya "Menara Evakuasi" sebagai tempat evakuasi dan pengungsian sementara Peninggian "Tanggul" sebagai tempat evakuasi sementara ketika tsunami 10. Jalur Penyelamatan Tersedianya rencana evakuasi yang dibuat bersama oleh pemerintah kota dan masyarakat Prosedur kerjasama antara pemerintah kota dan swasta guna memfungsikan bangunan swasta sebagai tempat evakuasi tsunami. Tersedianya prosedur evakuasi yang dikeluarkan oleh pihak otoritas penanggulangan bencana Pelaksanaan pendidikan berkelanjutan guna meningkatkan pemahaman evakuasi bagi setiap penduduk kota Sosialisasi kepada masyarakat tentang proses evakuasi yang aman dan efektif Evaluasi oleh pemerintah kota dan masyarakat terhadap program pendidikan evakuasi untuk masyarakat 11. Rencana Insfrastuktur Jalur Evakuasi dan Darurat (Emergency) Pembangunan jalan untuk jalur evakuasi pada area rawan tsunami Pembagunan jalan untuk memfasilitasi proses bantuan dan pemulihan korban serta pembangunan kembali fasilitas umum 12. Infrastruktur Kawasan Pantai Pembangunan "Pemecah Ombak" guna mengurangi dampak gelombang tsunami Pembangunan "Tanggul Pantai" guna melindungi penduduk dari dampak tsunami Tersedianya “Pintu Pengatur Air” guna mengurangi luapan banjir tsunami Pembangunan "Saluran Kanal" guna mengurangi hempasan gelombang tsunami

207

Table Continued (1) (2) (3) (4) (5) Sangat Tidak Antara Sangat Tidak Penting Penting dan Penting Penting Penting Tidak Penting Peninggian "Jalan" yang terletak pada kawasan pantai guna menahan gelombang tsunami 13.Control Forests/ Hutan Pantai Tersedianya hutan bakau dengan kepadatan tinggi guna mengurangi terpaan gelombang tsunami Penanaman pohon pada sisi sisi jalan utama sebagai penahan puing puing yang terbawa tsunami untuk mengurangi dampak kerugian yang lebih parah. 14. Fasilitas Prasarana dan Sarana Penempatan Fasilitas "Prasarana" (Transportasi,Jaringan Air dan Listrik) dan "Sarana" (Pemadam Kebakaran, Rumah Sakit,Pembangkit Listrik dan Air, Tangki BBM) pada kawasan aman tsunami Perbaikan sistem perlindungan Fasilitas "Prasarana" dan "Sarana" yang telah terbangun pada kawasan rawan tsunami Pemindahan (relokasi) fasilitas "Prasarana" dan "sarana" yang telah terbangun pada kawasan aman tsunami Tersedianya rencana gawat darurat (Emergency) dan pemulihan fasilitas "Prasarana dan Sarana" secara cepat & efisien 15. Sistem peringatan Dini Tersedianya sistem prakiraan bencana dan peringatan dini bagi penduduk sebelum terjadinya tsunami Tersedianya saluran yang efektif (televisi, radio, telepon genggam) untuk menyebarkan peringatan evakuasi tsunami 16. Desain dan Konstuksi Gedung Tersedianya peraturan standar bangunan gedung yang dapat mereduksi dampak tsunami

Thank you very much for your valuable time and participation.

208

LIST OF REFERENCES

References

Adger, W. N., Hughes, T. P., Folke, C., Carpenter, S. R., & Rockström, J. (2005). Social- ecological resilience to coastal disasters. Science, 309(5737), 1036-1039. doi:10.1126/science.1112122

Adikari, Y., & Yoshitani, J. (2009). Global trends in water- related disasters: An insight for policymakers. (pp. 28-28)

Akil, S. (2003). Penataan ruang dan pengembangan wilayah. sejarah penataan ruang indonesia/ spatial planning and regional development. history of planning in indonesia. Departemen Permukiman dan Prasarana Wilayah (KIMPRASWIL) - Direktorat Jenderal Penataan Ruang.

Alcántara-Ayala, I. (2002). Geomorphology, natural hazards, vulnerability and prevention of natural disasters in developing countries. Geomorphology, 47(2), 107-124. doi:10.1016/S0169-555X(02)00083-1

Aldrich, D., & Sawada, Y. (2015). The physical and social determinants of mortality in the 3.11 tsunami. Social Science & Medicine, 124, 66-75. doi:10.1016/j.socscimed.2014.11.025

Aleskerov, F., Say, A. I., Toker, A., Akin, H. L., & Altay, G. (2005). A cluster‐based decision support system for estimating earthquake damage and casualties. Disasters, 29(3), 255- 276. doi:10.1111/j.0361-3666.2005.00290.x

Alexander, D. (1991). Natural disaster-A framework for research and teaching. Disasters, 15(3), 209-226.

Alexander, D. (1993). Natural disasters. London: UCL Press.

Alexander, D. (2000). Confronting catastrophe: New perspectives on natural disasters. New York: Oxford University Press.

Alexander, E. (1998). Where do we go from here: Evaluation in spatial planning in the post- modern future. In L. Nathaniel, B. Angela, B. Dino, K. Abdul & P. Anna (Eds.), In evaluation in planning: Facing the challenge of complexity (pp. 355-74). Dordrecht, Netherlands: Kluwer.

Alexander, E. R. (2000). Rationality revisited: Planning paradigms in a post-postmodernist perspective. Journal of Planning Education and Research, 19(3), 242-256. doi:10.1177/0739456X0001900303

Alongi, D. M. (2008). Mangrove forests: Resilience, protection from tsunamis, and responses to global climate change. Estuarine, Coastal and Shelf Science, 76(1), 1-13. doi:10.1016/j.ecss.2007.08.024

209

Alonso, W. (1974). Location and land use: Toward a general theory of land rent. Cambridge: Harvard University Press.

Arszandi, P., Bayu, W., Dinar, M., Soly, I., Santoso., Galuh, S., & Ayu, B. (2015). Menata kota melalui rencana detail tata ruang (RDTR). urban management throuh the detail spatial plan in indoensia. Yogyakarta: AndiPublisher.

Asian Development Bank. (2016). Reducing disaster risk by managing urban land use: Guidance notes for planners. Mandaluyong City, Philippines: Asian Development Bank.

Attanapola, C., Brun, C., & Lund, R. (2013). Working gender after crisis: Partnerships and disconnections in sri lanka after the indian ocean tsunami. Gender Place and Culture, 20(1), 70-86. doi:10.1080/0966369X.2011.625080

Badan Nasional Penanggulangan Bencana, I. (2012). Masterplan pengurangan risiko bencana tsunami. Jakarta, BNPB,

Badan Penanggulangan Bencana Daerah Palu, Palu. (2009). Rencana penanggulangan bencanakota palu/ disaster reduction plan of palu city, indonesia.

Badan Perencanaan Pembangunan Nasional, Bappenas. (2005). Master plan for the rehabilitation and reconstruction of the regions and communities of the province of nanggroe aceh darussalam and the island of nias, province of north sumatera. (). Jakarta: BAPPENAS.

Baeda, Y. (2011). Seismic and tsunami hazard potential in sulawesi island, indonesia. Journal of International Development and Cooperation, 17(1), 17-30. doi:http://doi.org/10.15027/31339

Bappnes, & UNDP, I. (2006). National action plan for disaster reduction 2006-2009 UNDP and GOI.

Barbier, E. B. (2008). In the wake of tsunami: Lessons learned from the household decision to replant mangroves in thailand. Resource and Energy Economics, 30(2), 229-249. doi:10.1016/j.reseneeco.2007.08.002

Barrett, P. (2007). Structural equation modelling: Adjudging model fit. Personality and Individual Differences, 42(5), 815-824. doi:10.1016/j.paid.2006.09.018

Basiago, A. (1999). Economic, social, and environmental sustainability in development theory and urban planning practice. Environmentalist, 19(2), 145-145.

Beatley, T., Brower, D. J., & Schwab, A. K. (2002). An introduction to coastal zone management (2nd ed.). Washington, DC: Island Press.

Beaverstock, J. V., Faulconbridge, J. R., & Hoyle, M. (2011). Globalisation and the city. in the SAGE handbook of economic geography . In A. Leyshon, R. Lee, L. McDowell & P. Sunley (Eds.), (). London: SAGE.

210

Bell, F. G. (1999). Geological hazards : Their assessment, avoidance, and mitigation. London, ; New York: E & FN Spon.

Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588-606. doi:10.1037/0033- 2909.88.3.588

Bentler, P. M., & Chou, C. (1987). Practical issues in structural modeling. Sociological Methods & Research, 16(1), 78-117. doi:10.1177/0049124187016001004

Beppenas, I. (2006). Preliminary damage and loss assessment. the 15th meeting of the consultative group on indonesia jakarta, june 14, 2006 yogyakarta and central java natural disaster. jakarta.http://Siteresources.worldbank.org/INTINDONESIA/resources/226271- 1150196584718/PackageJune13_HIRES_FINAL.pdf.

Berke, P., & Smith, G. (2009). Hazard mitigation, planning, and disaster resiliency: Challenges and strategic choices for the 21st century. In J. Uitto I., & R. Shaw (Eds.), (). Amersterdam: IOS Press.

Berke, P., Backhurst, M., Day, M., Ericksen, N., Laurian, L., Crawford, J., & Dixon, J. (2006). What makes plan implementation successful? an evaluation of local plans and implementation practices in new zealand. Environment and Planning B-Planning & Design, 33(4), 581-600. doi:10.1068/b31166

Berke, P. R. (1995). Natural-hazard reduction and sustainable development: A global assessment. Journal of Planning Literature, 9(4), 370-382. doi:10.1177/088541229500900404

Berke, P., Lyles, W., & Smith, G. (2012). Planning for resiliency: Evaluation of state hazard mitigation plans under the disaster mitigation act. Natural Hazards Review, 13(2), 139- 149. doi:10.1061/(ASCE)NH.1527-6996.0000063

Bernard, E. N. (2005). Developing tsunami-resilient communities: The national tsunami hazard mitigation program. Dordrecht; Norwell, MA: Springer. doi:10.1007/1-4020-3607-8

Bird, D., & Dominey-Howes, D. (2006). Tsunami risk mitigation and the issue of public awareness. Australian Journal of Emergency Management, The, 21(4), 29-35.

Birkmann, J., & Fernando, N. (2008). Measuring revealed and emergent vulnerabilities of coastal communities to tsunami in sri lanka. Disasters, 32(1), 82-105. doi:10.1111/j.0361- 3666.2007.01028.x

Blaikie, P., Cannon, T., Davis, I., & Wisner, B. (2004). At risk: Natural hazards, people's vulnerability, and disasters (2nd ed.). New York; London: Routledge.

Blaikie, P. M. (1994). At risk: Natural hazards, people's vulnerability, and disasters. New York; London: Routledge.

211

Bogardi, J. J. (2008). Foreword, in bohle, H.-G. and warner, K., (eds)., megacities: Resilience and social vulnerability . Bonn: UNU-EHS. doi:http://eprints.manipal.edu/146865/1/Dr.Nanda%20Kishor-UNU- EHS-SOURCE.pdf

Boomsma, A., & Hoogland, J. J. (Eds.). (2001). The robustness of LISREL modeling revisited. Lincolnwood, IL: Scientific Software International.

Booth, P. (2005). The nature of difference: Traditions of law and government and their effects on planning in britain and france. In B. Sanyal (Ed.), Comparative planning cultures (). London: Routledge.

Boyce, D. E. (1970). Toward a framework for defining and applying urban indicators in plan- making. Urban Affairs Review, 6(2), 145-171. doi:10.1177/107808747000600202

Bradley, D. T., McFarland, M., & Clarke, M. (2014). The effectiveness of disaster risk communication: A systematic review of intervention studies. PLOS Currents Disasters, 1 doi:0.1371/currents.dis.349062e0db1048bb9fc3a3fa67d8a4f8.

Branch, M. C. (1985). Comprehensive city planning: Introduction & explanation. Chicago, Ill: Planners Press, American Planning Association.

Brassard, C. (2009). Measuring aid governance in developing countries: An application to post- tsunami aceh, indonesia. International Review of Administrative Sciences, 75(4), 629- 648. doi:10.1177/0020852309351450

Brody, S. D. (2003). Are we learning to make better plans?: A longitudinal analysis of plan quality associated with natural hazards. Journal of Planning Education and Research, 23(2), 191-201. doi:10.1177/0739456X03258635

Brueckner, J. K., & Lall, S. V. (2014). Cities in developing countries: Fueled by rural-urban migration, lacking in tenure security, and short of affordable housing. In Duranton, Henderson & Strange (Eds.), Handbook of regional and urban economics () Elsevier B.V.

Bruton, M. (1974). Transport planning. In M. Bruton (Ed.), The spirit and purpose of planning (). London: Hutchiston.

Bryant, E. (2014). Tsunami: The underrated hazard (Third; 3; 3rd; 3rd 2014 ed.). Cham: Springer. doi:10.1007/978-3-319-06133-7

Budiarjo, A. (2006). Evacuation shelter building planning for tusnami-prone area: A case study of meulaboh city, indonesia

Burby, R. J., Deyle, R. E., Olshansky, R. B., & Godschalk, D. R. (2000). Creating hazard resilient communities through land-use planning. Natural Hazards Review, 1(2), 99-106. doi:10.1061/(ASCE)1527-6988(2000)1:2(99)

212

Burgess, R., & Jenks, M. (2000). Compact cities: Sustainable urban forms for developing countries. New York; London: E. & F.N. Spon.

Burroughs, R. (2011). Coastal governance. Washington, DC: Island Press.

Burton, I., White, G. F., Kates, R. W., White, G. F., Kates, R. W., White, G. F., . . . Kates, R. W. (1978). The environment as hazard. New York: Oxford University Press.

Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. Mahwah, N.J: L. Erlbaum Associates.

Cadag, J. R. D., & Gaillard, J. (2012). Integrating knowledge and actions in disaster risk reduction: The contribution of participatory mapping. Area, 44(1), 100-109. doi:10.1111/j.1475-4762.2011.01065.x

Cannon, T., & Schipper, L. (2014). World disasters report: Focus on culture and risk. genf: International federation of red cross and red crescent societies. available at http://Www.ifrc.org/global/documents/secretariat/201410/WDR%202014.pdf.

Cater, N. (1998). World disasters report, 1998. ()

Center for Reserach on the Eidemology of Disasters, CRED. (2015). The human cost of natural disasters 2015: A global perspective. (). Brussel: CRED.

Chadwick, G. F. (1986). Models of urban and regional systems in developing countries : Some theories and their application in physical planning (1st ed. ed.). Oxford ; New York: Pergamon.

Chatenoux, B., & Peduzzi, P. (2007). Impacts from the 2004 indian ocean tsunami: Analysing the potential protecting role of environmental features. Natural Hazards, 40(2), 289-304. doi:10.1007/s11069-006-0015-9

Chmutina, K., Ganor, T., & Bosher, L. (2014). Role of urban design and planning in disaster risk reduction. Proceedings of the Institution of Civil Engineers.Urban Design and Planning, 167(3), 125-135. doi:10.1680/udap.13.00011

Chu, J., Wardani, S. P. R., & Iizuka, A. (2013). Geotechnical predictions and practice in dealing with geohazards (1st ed.). Dordrecht; New York: Springer.

Cochard, R., Ranamukhaarachchi, S. L., Shivakoti, G. P., Shipin, O. V., Edwards, P. J., & Seeland, K. T. (2008). The 2004 tsunami in aceh and southern thailand: A review on coastal ecosystems, wave hazards and vulnerability. Perspectives in Plant Ecology, Evolution and Systematics, 10(1), 3-40. doi:10.1016/j.ppees.2007.11.001

Cochrane, H. (2004). Economic loss: Myth and measurement. Disaster Prevention and Management: An International Journal, 13(4), 290-296. doi:10.1108/09653560410556500

213

Cohen, B. (2004). Urban growth in developing countries: A review of current trends and a caution regarding existing forecasts. World Development, 32(1), 23-51. doi:10.1016/j.worlddev.2003.04.008

Coppola, D. P. (2015). Introduction to international disaster management (Third ed.). Kidlington, Oxford, U.K: Butterworth-Heinemann is an imprint of Elsevier.

Costanza, R., d'Arge, R., de Groot, R., Farber, S., Grasso, M., Hannon, B., . . . van den Belt, M. (1998). The value of the world's ecosystem services and natural capital. Ecological Economics, 25(1), 3-15. doi:10.1016/S0921-8009(98)00020-2

Couling, M. (2014). Tsunami risk perception and preparedness on the east coast of new zealand during the 2009 samoan tsunami warning. Natural Hazards, 71(1), 973-986. doi:10.1007/s11069-013-0945-y

Cowherd, R. (2005). Does planning culture matter? dutch and american models in indonesian urban transformations. In S. Bishwapriya (Ed.), Comparative planning culture (pp. 165- 192). New York: Routledge.

Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks, Calif: Sage Publications.

Crook, G. R. (1974). Physical planning. In Michael J. Bruton (Ed.), The spirit and purpose of planning (). London: Hutchiston.

Crossland, C. J. (2005). Coastal fluxes in the anthropocene. Berlin: Springer.

Cutter, S. L. (2001). American hazardscapes: The regionalization of hazards and disasters. Washington, D.C: Joseph Henry Press.

Dahuri, R. (2007). Pre-and post-tsunami coastal planning and land-use policies and issues in indonesia.FAO.

Davis, I. (1987). SAFE SHELTER WITHIN UNSAFE CITIES: Disaster vulnerability and rapid urbanisation. Open House International: The Journal of an Association of Institutes and Individuals Concerned with Housing, Design and Development in the Built Environment, 12(3), 5.

Degg, M. (1992). Natural disasters - recent trends and future-prospects. Geography, 77(336), 198-209.

Dengler, L. (1998). Strategic implementation plan for tsunami mitigation projects, approved by the mitigation subcommittee of the national tsunami hazard mitigation program, april 14, 1998. technical report NOAA tech. memo. ERL PMEL-113 (PB99-115552). ( No. ERL PMEL-113 (PB99-115552)).

Dengler, L. (2005). The role of education in the national tsunami hazard mitigation program. Natural Hazards, 35(1), 141-153. doi:10.1007/s11069-004-2409-x

214

Dengler, L. A. (1998). Strategic implementation plan for tsunami mitigation projects. ( No. no. 2030.; 113). Seattle, Wash; Springfield, VA: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Pacific Marine Environmental Laboratory.

Deni, R. (2003). Pendekatan perencanaan pengembangan wilayah di indonesia. sejarah penataan ruang indonesia. . Jakarta: Departemen Permukiman dan Prasarana Wilayah (KIMPRASWIL) - Direktorat Jenderal Penataan Ruang.

Department of Public Works of Indonesia. (2010). Provinces, regions and cities: Data and fact. Jakarta: Department of Public Works of Indonesia.

Deutsche Welle Business. (2016). Indonesia's historic shift to an urban economy. Chatham: Newstex.

Devi, E. U., Sunanda, M., Kumar, B. A., Kumar, C. P., & Kumar, T. S. (2016). Real-time earthquake monitoring at the indian tsunami early warning system for tsunami advisories in the indian ocean. The International Journal of Ocean and Climate Systems, 7(1), 20- 26. doi:10.1177/1759313115623164

Doberstein, B., & Tadgel, A. (2015). Guidance for 'managed' relocation

Doocy, S., Daniels, A., Dick, A., & Kirsch, T. D. (2013). The human impact of tsunamis: A historical review of events 1900-2009 and systematic literature review. PLoS Currents, 5

Dunbar, P. K., Weaver, C. S., National Geophysical Data Center, Geological Survey (U.S.), & National Tsunami Hazard Mitigation Program (U.S.). (2008). U.S. states and territories national tsunami hazard assessment: Historical record and sources for waves. Reston, Va.; Silver Spring, Md.: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration.

Duranton, G. (2014). Growing through cities in developing countries

Earthquake Engineering Research Institute, EERI. (2005). Special earthquake report — august 2005: Learning from earthquakes the northern sumatra earthquake of march 28, 2005.

Edward, P., Terazaki, M., & Yamaguchi, M. (2006). The impact of tsunami in coastal areas: Coastal protection and disaster prevention measures—Experiences from japanese coasts. Coastal Marine Science, 30(2), 414–424.

Eldeen, M. T. (1980). Predisaster physical planning: Integration of disaster risk analysis into physical planning - a case study in tunisia. Disasters, 4(2), 211.

El-Masri, S., & Tipple, G. (2002). Natural disaster, mitigation and sustainability: The case of developing countries. International Planning Studies, 7(2), 157-175. doi:10.1080/13563470220132236

215

E-marketer. (2016). In indonesia, facebook remains the most popular social site about 70% also say they use instagram. Retrieved from https://www.emarketer.com/Article/Indonesia-Facebook-Remains-Most-Popular-Social- Site/1014126

Emdad, H., & Ian, B. (2005). Adaptation options strategies for hazards and vulnerability mitigation: An international perspective in mitigation of natural hazards and disasters:International perspectives by C. EMDAD HAQUE (ed).

Environment Waikato Regional Council, EWRC. (2007). Natural hazard of waikato New Zealand Government.

Escaleras, M., Anbarci, N., & Register, C. A. (2007). Public sector corruption and major earthquakes: A potentially deadly interaction. Public Choice, 132(1/2), 209-230. doi:10.1007/s11127-007-9148-y

Etoju, O. A. (2002). Physical planning and the quality of urban development in lira municipality, in lira district. Kampala, Uganda: NURRU Publications.

Europen Union. (2001). The EU compendium of spatial planning systems and policies: Luxembourg. Luxemburg: Office for official publication of the European Communities.

Faludi, A. (2000). The performance of spatial planning. Planning Practice & Research, 15(4), 299-318. doi:10.1080/713691907

Farber, D. A. (2010). Disaster law and policy (2nd ed.). Austin; Frederick, MD: Aspen Publishers.

Farreras, S. F., & Sanchez, A. J. (1991). The tsunami threat on the mexican west coast: A historical analysis and recommendations for hazard mitigation. Natural Hazards, 4(2-3), 301-316. doi:10.1007/BF00162795

Federal Emergency Management Agency, FEMA. (1995). National mitigation strategy: Partnerships for building safer communities

Federal Emergency Management Agency, FEMA. (2003). Integrating manmade hazards into mitigation planning (Version 2.0. ed.). Washington, D.C.: FEMA, U.S. Dept. of Homeland Security.

Federal Emergency Management Agency, F. (1986). Making mitigation work: A handbook for state officials. washington DC: Author.

Fiskaa, H. (2005). Past and future for public participation in norwegian physical planning. European Planning Studies, 13(1), 157-174. doi:10.1080/0965431042000312451

Folmer, E., & Risselada, A. H. (2012). Planning the neighbourhood economy: Land-use plans and the economic potential of urban residential neighbourhoods in the netherlands. European Planning Studies, online first

216

Forbes, J. (1974). Studies in social science and planning. Scotland; United Kingdom:

Frankenberg, E., Gillespie, T., Preston, S., Sikoki, B., & Thomas, D. (2011). Mortality, the family and the indian ocean tsunami. The Economic Journal, 121(554), F162-F182. doi:10.1111/j.1468-0297.2011.02446.x

Fumihiko, I., Noritake, N., & Yasuo, S. (2005). Tsunami countermeasure in japan -education, awareness, and tsunami warning education. Science council of asia.

Gad-el-Hak, M. (2008). Large-scale disasters: Prediction, control, and mitigation. Cambridge; New York: Cambridge University Press.

Gaina, C., & Müller, D. (2007). Cenozoic tectonic and depth/age evolution of the indonesian gateway and associated back-arc basins. Earth Science Reviews, 83(3), 177-203. doi:10.1016/j.earscirev.2007.04.004

Gakkai, D. (1991). International symposium on natural disaster reduction and civil engineering : September 18, 1991, kansai university, osaka, japan. Osaka: Japan Society of Civil Engineers, Kansai Chapter.

Gans, H. J. (1963). Social and physical planning for the elimination of urban poverty. Washington University Law Quarterly, 1963(1), 2-18.

Gans, H. J. (1969). Planning for people, not buildings. Environment and Planning, Vol.1, no.1, 1969, P 33-46, 8 Ref,

Geo-PUC. (2010). Final report on definition of tsunami risk areas. localities of constitución, dichato, talcahuano, llico y tubul. santiago, chile. ().

Give2Asia. (2009). Disaster vulnerability & donor opportunities in south & southeast asia. ().

Godschalk, D. R. (1999). Natural hazard mitigation: Recasting disaster policy and planning. Washington, D.C: Island Press.

Godschalk, D. R. (2003). Urban hazard mitigation: Creating resilient cities. Natural Hazards Review, 4(3), 136-143. doi:10.1061/(ASCE)1527-6988(2003)4:3(136)

Godschalk, D. (2009). Safe growth audits American Planning Association. doi:https://planning- org-uploaded- media.s3.amazonaws.com/legacy_resources/zoningpractice/open/pdf/oct09.pdf

Goldblum, C., & Wong, T. (2000). Growth, crisis and spatial change: A study of haphazard urbanisation in jakarta, indonesia. Land use Policy, 17(1), 29-37. doi:10.1016/S0264- 8377(99)00043-5

GuhaSapir, D., Parry, L. V., Degomme, O., Joshi, P. C., & Saulina Arnold, J. P. (2006). Risk factors for mortality and injury: Post-tsunami epidemiological findings from tamil nadu. (). Brussels: UNISDR.

217

Guyadeen, D., & Seasons, M. (2016). Evaluation theory and practice: Comparing program evaluation and evaluation in planning. Journal of Planning Education and Research, , 739456. doi:10.1177/0739456X16675930

Haar, C. M., Rodwin, L., & Higgins, B. (2007). Economic and physical planning :Coordination in developing areas. American Institute of Planners.Journal, 24(3), 167-173.

Habitat, U. (1995). Chapter 2. the role of physical planning in flood disaster mitigation in guidelines for settlement planning in areas prone to flood disasters. .

Hadi, S. (2008). Government of indonesia policy in mainstreaming disaster risk reduction and disaster management into the planning and budgeting. Pacific Regional Disaster Risk Management Meeting in Fiji.,

Hadi, S., Latief, H., & Muliddin. (2003). Analysis of surface wave attenuation in mangrove forests. ITB Journal of Engineering Science, 35(2), 89-108. doi:10.5614/itbj.eng.sci.2003.35.2.1

Hall, P. (1970). The relationship between physical and economic planning. The Geographical Journal, 136(1), 12-15. doi:10.2307/1795678

Hamzah, L., Puspito, N. T., & Imamura, F. (2000). Tsunami catalog and zones in indonesia. Journal of Natural Disaster Science, 22(1), 25-43. doi:10.2328/jnds.22.25

Harris, R. J., Jonathan. (2016). Waves of destruction in the east indies: The wichmann catalogue of earthquakes and tsunami in the indonesian region from 1538 to 1877. doi:. https://dx.doi.org/10.6084/m9.figshare.c.2860405.v1

Harrison, C., & Williams, P. (2016). A systems approach to natural disaster resilience. Simulation Modelling Practice and Theory, 65, 11-31. doi:10.1016/j.simpat.2016.02.008

Healey, P., & Williams, R. (1993). European urban-planning systems - diversity and convergence. Urban Studies, 30(4-5), 701-720.

Henry, A., Joseph. (2000). Managing land use to build resilience. In Raymond J. Burby (Ed.), Cooperating with nature: Confronting natural hazards with land-use planning for sustainable communities (pp. 167-202) National Academies Press.

Hiraishi, T., & Kawai, H. (1998). Integration of disaster management technologies: Tsunami risk and its reduction and countermeasure to tsunami in coastal area. Paper presented at the 222-225.

Hoernig, H., & Seasons, M. (2004). Monitoring of indicators in local and regional planning practice: Concepts and issues. Planning Practice & Research, 19(1), 81-99. doi:10.1080/0269745042000246595

218

Horspool, N., Pranantyo, I., Griffin, J., Latief, H., Natawidjaja, D. H., Kongko, W., . . . Thio, H. K. (2014). A probabilistic tsunami hazard assessment for indonesia. Natural Hazards and Earth System Sciences, 14(11), 3105-3122. doi:10.5194/nhess-14-3105-2014

Horspool, N., Pranantyo, I., Griffin, J., Latief, H., Natawidjaja, D., Kongko, W., . . . Thio, H. (2013). A probabilistic tsunami hazard assessment for indonesia. (). Australia: The Creative Commons Attribution.

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. doi:10.1080/10705519909540118

Hu, R. (2013). Urban design plans for downtown san francisco: A paradigm shift? Journal of Urban Design, 18(4), 517-533. doi:10.1080/13574809.2013.824366

Huang, W., Yim, J., & Lin, J. (1999). Effect of detached breakwater on wave directionality: Example of BDZ harbour. (pp. 724-729)

Hudalah, D. (2010). Peri-urban planning in indonesia: Context, approaches and institutional capacity

Hudalah, D., & Woltjer, J. (2007). Spatial planning system in transitional indonesia. International Planning Studies, 12(3), 291-303. doi:10.1080/13563470701640176

IBM. (2011). IBM SPSS missing values

Indonesia World Bank. (2016). Indonesia's urban story. (). Jakarta: The World Bank.

Indonesian National Board for Disaster Management. (2007). UNDANG- UNDANG REPUBLIK INDONESIA NOMOR 24 TAHUN 2007 TENTANG MENEJEMEN BENCANA. act of 24, 2007 on disaster management. doi:available at http://www.bnpb.go.id/uploads/migration/pubs/1.pdf

International Federation of Red Cross and Red Crescent Societies, IFRC. (2010). Disaster- management. Retrieved from http://www.ifrc.org/en/what-we-do/disaster- management/about-disaster-management.

International Strategy for Disaster Reduction. (2004). Living with risk: A global review of disaster reduction initiatives (2004 ver. ed.). Geneva; New York: United Nations.

James, E. (2008). Getting ahead of the next disaster: Recent preparedness efforts in indonesia. Development in Practice, 18(3), 424-429. doi:10.1080/09614520802030607

Japan International Cooperation Agency, JICA. (2005). The study on the urgent rehabilitation and reconstruction support program for AcehProvince and affected areas in north sumatra. (). Jakarta: Japan International Cooperation Agency (JICA), Badan Perencanaan Pembangunan Nasional (Bappenas), and Provincial Government of Nanggroe Aceh Darussalaam, Banda Aceh.

219

Jeffrey, S. E. (1982). The creation of vulnerability to natural disaster; case studies from the dominician republic. . Disasters, 6(1) doi:10.1111/j.1467-7717.1982.tb00742.x/pdf

Jenks, M., & Dempsey, N. (2005). Future forms and design for sustainable cities. Amsterdam; Boston: Architectural Press.

Johnson, L., Samant, L., Frew, S., Samant, L. D., & American Planning Association. Planning Advisory Service. (2005). Planning for the unexpected: Land-use development and risk. Chicago, IL: American Planning Association.

Johnston, D., Paton, D., Crawford, G. L., Ronan, K., Houghton, B., & Bürgelt, P. (2005). Measuring tsunami preparedness in coastal washington, united states. Natural Hazards, 35(1), 173-184. doi:10.1007/s11069-004-2419-8

Johnston, N. J. (1966). The caste and class of the urban form of historic philadelphia. American Institute of Planners.Journal, 32(6), 334-349.

Kammerbauer, M. (2013). ‘Schismo‐urbanism’: Cities, natural disaster, and urban sociology. Disasters, 37(3), 401-419. doi:10.1111/disa.12005

Kaplowitz, M. D. (2000). Property rights, economics, and the environment. Stamford, Conn: JAI Press.

Kasarda, J. D., & Crenshaw, E. M. (1991). Third world urbanization: Dimensions, theories, and determinants. Annual Review of Sociology, 17(1), 467-501. doi:10.1146/annurev.so.17.080191.002343

Katili, J. (1978). Past and present geotectonic position of sulawesi, indonesia. Tectonophysics 45, 45, 289–322.

Kazama, M., & Noda, T. (2012). Damage statistics (summary of the 2011 off the pacific coast of tohoku earthquake damage). Soils and Foundations, 52(5), 780-792. doi:10.1016/j.sandf.2012.11.003

Kellenberg, D., & Mobarak, A. (2011). The economics of natural disasters. (pp. 297-312). PALO ALTO: ANNUAL REVIEWS. doi:10.1146/annurev-resource-073009-104211

Khakee, A. (1998). Evaluation and planning: Inseparable concepts. Town Planning Review, 69(4), 359-374.

Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York: Guilford Press.

Kodoatie, R., J. (2006). Pengelolaan bencana terpadu (comprhensive disaster management in indoesia). Indonesia:

Kreimer, A. (2001). Social and economic impacts of natural disasters. International Geology Review, 43(5), 401-405. doi:10.1080/00206810109465021

220

Kreimer, A., Arnold, M., & Carlin, A. (2003). Building safer cities: The future of disaster risk. Washington, D.C: World Bank. doi:10.1596/0-8213-5497-3

Kubba, S. (2012). Handbook of green building design and construction: LEED, BREEAM, and green globes. Amsterdam; Boston: Elsevier/Butterworth-Heinemann.

Kuroiwa, J. (1988). Physical planning for multi-hazard mitigation julio kuroiwa in M. I. el-sabh, T. S. murty (eds), natural and man-made hazards : Proceedings of the international symposium held at rimouski, quebec, canada, 3-9 august, 1986. Netherlands:

Laurian, L., Day, M., Backhurst, M., Berke, P., Ericksen, N., Crawford, J., . . . Chapman, S. (2004). What drives plan implementation? plans, planning agencies and developers. Journal of Environmental Planning and Management, 47(4), 555-577. doi:10.1080/0964056042000243230

Lee, T., & Lawver, L. A. (1995). Cenozoic plate reconstruction of southeast asia. Tectonophysics, 251(1), 85-138. doi:10.1016/0040-1951(95)00023-2

Lindell, M., Prater, C., & Perry, R. (2006). Fundamentals of emergency management. Emmitsburg, MD: Federal Emergency Management Agency Emergency Management Institute. doi:www.training.fema.gov/EMIWeb

Lindell, M. K. (2013). Disaster studies. Current Sociology, 61(5-6), 797-825. doi:10.1177/0011392113484456

Lindell, M. K., & Prater, C. S. (2000). Politics of hazard mitigation. Natural Hazards Review, 1(2), 73-82. doi:10.1061/(ASCE)1527-6988(2000)1:2(73)

Lindell, M. K., & Prater, C. S. (2003). Assessing community impacts of natural disasters. Natural Hazards Review, 4(4), 176-185. doi:10.1061/(ASCE)1527-6988(2003)4:4(176)

Lindsay, J. R. (1993). Exploring the interface of urban planning and disaster management: Establishing the connection between the fields

Lockridge, P. A. (1988). Historical tsunamis in the pacific basin. In M. I. El-Sabh, & T. S. Murty (Eds.), Natural and man-made hazards (pp. 171-181). Netherlands: Springer.

Lovholt, F., Glimsdal, S., Harbitz, C., Zamora, N., Nadim, F., Peduzzi, P., . . . Smebye, H. (2012). Tsunami hazard and exposure on the global scale. Earth-Science Reviews, 110(1- 4), 58-73. doi:10.1016/j.earscirev.2011.10.002

Lovholt, F., Setiadi, N., Birkmann, J., Harbitz, C., Bach, C., Fernando, N., . . . Nadim, F. (2014). Tsunami risk reduction - are we better prepared today than in 2004? International Journal of Disaster Risk Reduction, 10, 127-142. doi:10.1016/j.ijdrr.2014.07.008

MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130-149. doi:10.1037/1082-989X.1.2.130

221

MacDonald, R. (2005). How women were affected by the tsunami: A perspective from oxfam. Plos Medicine, 2(6), 474-475. doi:10.1371/journal.pmed.0020178

Makassar Municipal Government. (2015). Makassar in figure 2015. ().Makassar Municipal Government.

Makassar Statistical Bureau. (2017). Annual report of makassar in statistic. ().Makassar Statistical Bureau.

Manda, M. Z. (2014). Where there is no local government: Addressing disaster risk reduction in a small town in malawi. Environment & Urbanization, 26(2), 586-599. doi:10.1177/0956247814530949

Maniera-Elia M. (1979). Toward an "imperial city":Daniel H burnham and the city beautiful movement. In e. a. G. Gucci (Ed.), The american city. from the civil war to the new deal. cambridge (pp. 1-122). Cambridge: MIT Press.

Mas, E., Koshimura, S., Imamura, F., Suppasri, A., Muhari, A., & Adriano, B. (2015). Recent advances in agent-based tsunami evacuation simulations: Case studies in indonesia, thailand, japan and peru. Pure and Applied Geophysics, 172(12), 3409-3424. doi:10.1007/s00024-015-1105-y

Matsutomi, H., Shuto, N., Imamura, F., & Takahashi, T. (2001). Field survey of the 1996 irian jaya earthquake tsunami in biak island. Natural Hazards, 24(3), 199-212. doi:10.1023/A:1012042222880

Mbogua, J. P. (1994). Integrating environmental with physical planning. international conference on re appraising the city planning process as an instrument for sustainable urban development,and management;united nations centre for,human settlements. Nairobi, Kenya: Josem Trust Consultancy Services.

McCaffrey, R., & Nabelek, J. (1987). Earthquakes, gravity, and the origin of the bali basin: An example of a nascent continental fold-and-thrust belt. Journal of Geophysical Research, 92(B1), 441-460. doi:10.1029/JB092iB01p00441

McDavid, J. C., & Hawthorn, L. R. L. (2006). Program evaluation & performance measurement: An introduction to practice

McHarg, I. L. (1969). Design with nature (1st ed.). Garden City, N.Y: Published for the American Museum of Natural History [by] the Natural History Press.

Menoni, S., & Pesaro, G. (2008). Is relocation a good answer to prevent risk?: Criteria to help decision makers choose candidates for relocation in areas exposed to high hydrogeological hazards. Disaster Prev and Management, 17(1), 33-53. doi:10.1108/09653560810855865

Mileti, D. (1999). Disasters by design: A reassessment of natural hazards in the united states. Washington, D.C: Joseph Henry Press.

222

Mileti, D. S., Darlington, J. D., Passerini, E., Forrest, B. C., & Myers, M. F. (1995). Toward an integration of natural hazards and sustainability. Environmental Professional, 17(2), 117- 117.

Mileti, D. S., & Gailus, J. L. (2005). Sustainable development and hazards mitigation in the united states: Disasters by design revisited. Mitigation and Adaptation Strategies for Global Change, 10(3), 491-504. doi:10.1007/s11027-005-0057-4

Mimura, N., Yasuhara, K., Kawagoe, S., Yokoki, H., & Kazama, S. (2011). Damage from the great east japan earthquake and tsunami - A quick report. Mitigation and Adaptation Strategies for Global Change, 16(7), 803-818. doi:10.1007/s11027-011-9297-7

Mitchell, J. K. (1995). Coping with natural hazards and disasters in megacities: Perspectives on the twenty-first century. GeoJournal, 37(3), 303-311. doi:10.1007/BF00814009

Moeliono, T., P. (2011). Spatial management in indonesia: From planning to implementation : Cases from west java and bandung : A socio-legal study. Leiden: Universiteit Leiden.

Mori, J., Mooney, W., Afnimar, Kurniawan, S., Anaya, A., & Widiyantoro, S. (2007). The 17 july 2006 tsunami earthquake in west java, indonesia. Seismological Research Letters, 78(2), 201-207. doi:10.1785/gssrl.78.2.201

Mukherji, A. (2014). Land readjustment during post-disaster urban reconstruction. Journal of the American Planning Association, 80(4), 438-439. doi:10.1080/01944363.2014.989058

Murao, O. (2008). Case study of architecture and urban design on the disaster life cycle in japan. Paper presented at the

Nakahara, S., & Ichikawa, M. (2013). Mortality in the 2011 tsunami in japan. Journal of Epidemiology, 23(1), 70-73. doi:10.2188/jea.JE20120114

Nakaza, E., Schaab, C., & Rahman, M. M. (2017). Experimental and numerical modeling of tsunami mitigation by canals. Journal of Waterway, Port, Coastal, and Ocean Engineering, 143(1), 4016012. doi:10.1061/(ASCE)WW.1943-5460.0000355

National Centers for Environmental Information. (2014). Major tsunamis of 1992 - nicaragua and indonesia. doi:Retrieved from https://www.ngdc.noaa.gov/docucomp/page?xml=NOAA/NESDIS/NGDC/MGG/Hazard _Photos/iso/xml/G01219.xml&view=getDataView&header=none

National Tsunami Hazard Mitigation Program, NTHMP. (2001). Designing for tsunamis: Seven principles for planning and designing for tsunami hazards. Seattle, Wash.: National Tsunami Hazard Mitigation Program.

Neutze, M. (1985). Population issues and physical planning. Journal of the Australian Population Association, 1(2), 89-98.

223

Newman, P., Kenworthy, J., & Vintila, P. (1995). Can we overcome automobile dependence? Cities, 12(1), 53-65. doi:10.1016/0264-2751(95)91865-D

Nicholls, R. (2002). Improved estimates of coastal population and exposure to hazards released. EOS, Transactions, American Geophysical Union, 83(28), 301-301. doi:10.1029/2002EO000216

Niessen, N. (1999). Municipal government in indonesia: Policy, law, and practice of decentralization and urban spatial planning. Leiden: Research School CNWS, School of Asian, African, and Amerindian Studies, Universiteit Leiden.

Nijkamp, P., Rietveld, P., & Voogd, H. (1990). Multicriteria evaluation in physical planning. New York, N.Y., U.S.A; Amsterdam, Netherlands; New York: North-Holland.

Nishikiori, N., Abe, T., Costa, D., Dharmaratne, S., Kunii, O., & Moji, K. (2006). Who died as a result of the tsunami? risk factors of mortality among internally displaced persons in sri lanka: A retrospective cohort analysis. Bmc Public Health, 6(1), 73-73. doi:10.1186/1471-2458-6-73

Noy, I. (2009). The macroeconomic consequences of disasters. Journal of Development Economics, 88(2), 221-231. doi:10.1016/j.jdeveco.2008.02.005

Oberai, A. S. (1993). Population growth, employment, and poverty in third-world mega-cities: Analytical and policy issues

Oktari, R. S., Munadi, K., & Ridha, M. (2014). Effectiveness of dissemination and communication element of tsunami early warning system in aceh doi:http://dx.doi.org/10.1016/S2212-5671(14)00923-X

Olajuyigbe, A. E., & Rotowa, O. O. (2011). Optimizing physical planning in the developing countries - A case study of ondo state, nigeria. Journal of Sustainable Development, 4(4), 202-202.

Oliveira, V., & Pinho, P. (2010). Evaluation in urban planning: Advances and prospects. Journal of Planning Literature, 24(4), 343-361. doi:10.1177/0885412210364589

Oliveira, V., & Pinho, P. (2009). Evaluating plans, processes and results. Planning Theory & Practice, 10(1), 35-63. doi:10.1080/14649350802661741

Orhan, E. (2015). The consequences of security cognition in post-disaster urban planning practices in the case of turkey. Natural Hazards, 76(1), 685-703. doi:10.1007/s11069- 014-1497-5

Passchier, C. (2016). Building in indonesia, 1600-1960 LM Publishers.

Paton, D., Houghton, B. F., Gregg, C. E., Gill, D. A., Ritchie, L. A., McIvor, D., . . . Johnston, D. M. (2008). Managing tsunami risk in coastal communities : Identifying predictors or preparedness. Australian Journal of Emergency Management, The, 23(1), 4-9.

224

Patton, C. V., & Subanu, L. P. (1988). Meeting shelter needs to indonesia, spontaneous shelter. International Perspective and Prospects, , 168-190.

Pelling, M. (2003). The vulnerability of cities: Natural disasters and social resilience. Sterling, VA; London: Earthscan Publications.

Perin, C. (1967). A noiseless secession from the comprehensive plan. American Institute of Planners.Journal, 33(5), 336-347.

Petersen, M., Harmsen, S., Muller, C., Haller, K., Dewey, J., Luco, N., . . . Rukstales, K. (2007). Documentation for the southeast asia seismic hazard maps. doi:available at: http://earthquake.usgs.gov/hazards/products/images/SEASIA_2007.pdf

Pickvance, C. (1982). Physical planning and market forces in urban development. In C. Paris (Ed.), Critical readings in planning theory (pp. 69-82). Oxford: Pergmon Press.

Pivo, G., Ellis, C., Leaf, M., & Magutu, G. (1990). Physical planning thought - retrospect and prospect. Journal of Architectural and Planning Research, 7(1), 53-70.

Planitz, A. (2007). Implementing the hyogo framework for action 2005-2015: Building the resilience of nations and communities to disasters

Poisson, B., Oliveros, C., & Pedreros, R. (2011). Is there a best source model of the sumatra 2004 earthquake for simulating the consecutive tsunami?: A best source for sumatra 2004 tsunami? Geophysical Journal International, 185(3), 1365-1378. doi:10.1111/j.1365- 246X.2011.05009.x

Porfiriev, B. N. (2016). The economics of natural disasters. Herald of the Russian Academy of Sciences, 86(1), 1-11. doi:10.1134/S1019331616010020

Prasetya, G. S., De Lange, W. P., & Healy, T. R. (2001). The makassar strait tsunamigenic region, indonesia. Natural Hazards, 24(3), 295-307. doi:10.1023/A:1012297413280

Preuss, J. (1982). Land management guidelines in tsunami hazard zones. In K. Iida, & T. Iwasaki. (Eds.), Tsunamis: Their science and engineering (pp. 527-539). Terra Scientific Publishing Company: Tokyo.

Ranghieri, F., Ishiwatari, M., & World Bank. (2014). Learning from megadisasters: Lessons from the great east japan earthquake. Washington, DC: World Bank. doi:10.1596/978-1- 4648-0153-2

Rees, W. E. (1996). Revisiting carrying capacity: Area-based indicators of sustainability. Population and Environment, 17(3), 195-215. doi:10.1007/BF02208489

Reilly, B. (2009). Disaster and human history : Case studies in nature, society and catastrophe. Jefferson, N.C: McFarland & Co.

225

Renaud, F. G., Sudmeier-Rieux, K., Estrella, M., & ebrary, I. (2013). The role of ecosystems in disaster risk reduction. Shibuya-ku, Tokyo: United Nations University Press.

The spatial planning law 26 year 2007, (2007).

Rofi, A., Doocy, S., & Robinson, C. (2006). Tsunami mortality and displacement in aceh province, indonesia. Disasters, 30(3), 340-350. doi:10.1111/j.0361-3666.2005.00324.x

Roosmalen, V. (2005). Expanding grounds:The roots of spatial planning in indonesia/the history of the indonesian city before and after independence. In F. Colombijn, & M. Barwegen (Eds.), Kota lama, kota baru: Sejarah kota-kota di indonesia sebelum dan setelah kemerdekaan (pp. 75-117). Yogyakarta: Ombak,.

Rückert, J. J. G. E. (1930). Volkshuisvesting II. In F. Kerchman (Ed.), 25 jaren decentralisatie in nederlandsch-indië 1905-1930 (pp. 162-173) Weltevreden.

Rukmana, D. (2015). The change and transformation of indonesian spatial planning after suharto's new order regime: The case of the jakarta metropolitan area. International Planning Studies, 20(4), 350-370. doi:10.1080/13563475.2015.1008723

Saatçioğlu, M. (2009). Performance of structures during the 2004 indian ocean tsunami and tsunami induced forces for structural design. (1st ed., pp. 153-178). Dordrecht: Springer Netherlands. doi:10.1007/978-90-481-2399-5_10

Satake, K., Okal, E. A., & Borrero, J. C. (2007). Tsunami and its hazards in the indian and pacific oceans. Basel; London: Birkhäuser. doi:10.1007/978-3-7643-8364-0

Saunders, W., & Kilvington, M. (2016). Innovative land use planning for natural hazard risk reduction: A consequence-driven approach from new zealand. International Journal of Disaster Risk Reduction, 18, 244-255. doi:10.1016/j.ijdrr.2016.07.002

Schmidt, S. (2012). Fluid city: Transforming melbourne's urban waterfront Taylor & Francis Group. doi:10.1080/13574809.2012.666184

Schneider, R. O. (2002). Hazard mitigation and sustainable community development. Disaster Prevention and Management: An International Journal, 11(2), 141-147. doi:10.1108/09653560210426821

Schwab, A. K., & Brower, D. J. (2008). Increasing resilience to natural hazards: Obstacles and opportunities for local governments under the disaster mitigation act of 2000. Environmental Law Reporter, 38(3), 10171.

Schwab, J., & American Planning Association. (2010). Hazard mitigation: Integrating best practices into planning. Chicago: American Planning Association.

Seasons, M. (2003a). Indicators and core area planning: Applications in canada's mid-sized cities. Planning Practice & Research, 18(1), 63-63. doi:10.1080/0269745032000132646

226

Seasons, M. (2003b). Monitoring and evaluation in municipal planning. American Planning Association.Journal of the American Planning Association, 69(4), 430.

Sendai City. (2011). The sendai city earthquake disaster reconstruction plan.sendai city earthquake disaster reconstruction plan, digest version. doi:available at: http://www.preventionweb.net/applications/hfa/lgsat/en/image/href/824

Sendai City. (2012). Sendai city earthquake disaster reconstruction plan Sendai City. doi:http://www.preventionweb.net/applications/hfa/lgsat/en/image/href/824

Shadish, W., Thomas, C., & Laura, L. (1991). Good theory for social program evaluation. In W. Shadish, C. Thomas & L. Laura (Eds.), Foundations of program evaluation: Theories of practice (pp. 36–67). Newbury Park, CA: Sage.

Shaw, R. (2006). Indian ocean tsunami and aftermath: Need for environment‐disaster synergy in the reconstruction process. Disaster Prev and Management, 15(1), 5-20. doi:10.1108/09653560610654202

Shevlin, M., & Miles, J. N. V. (1998). Effects of sample size, model specification and factor loadings on the GFI in confirmatory factor analysis. Personality and Individual Differences, 25(1), 85-90. doi:10.1016/S0191-8869(98)00055-5

Shigenobu, T., & Dinar, I. (2010). Tsunami hazard mapping in developing countries an effective way of raising awareness for tsunami disaster risk reduction ICHARM Publication.

Silas, J. (1984). The kampung improvement programme of indonesia: A comparative case study of jakarta and surbaya. In G.K Payne (Ed.), Low-income housing in the developing world: The role of sites and services and settlement upgrading (). Chichester: John Wiley and Sons.

Silver, C. (2008). Planning the megacity: Jakarta in the twentieth century. New York; London: Routledge.

Silver, E. A., McCaffrey, R., & Smith, R. B. (1983). Collision, rotation, and the initiation of subduction in the evolution of sulawesi, indonesia. Journal of Geophysical Research: Solid Earth, 88(B11), 9407-9418. doi:10.1029/JB088iB11p09407

Sims, J. H., & Baumann, D. D. (1972). The tornado threat: Coping styles of the north and south. Science, 176(4042), 1386-1392. doi:10.1126/science.176.4042.1386

Skoufias, E. (2003). Economic crises and natural disasters: Coping strategies and policy implications. World Development, 31(7), 1087-1102. doi:10.1016/S0305- 750X(03)00069-X

Smith, K. (2004). Environmental hazards assessing risk and reducing disaster (4th ed. ed.). London ; New York: Routledge. Retrieved from http://www.netLibrary.com/urlapi.asp?action=summary&v=1&bookid=94678

227

Socquet, A., Simons, W., Vigny, C., McCaffrey, R., Subarya, C., Sarsito, D., . . . Spakman, W. (2006). Microblock rotations and fault coupling in SE asia triple junction (sulawesi, indonesia) from GPS and earthquake slip vector data. Journal of Geophysical Research - Solid Earth, 111(B8), B08409. doi:10.1029/2005JB003963

Solway, L. (2004). Reducing the effect of natural disaster on urban areas. In R. Casale, & C. Margottini (Eds.), Natural disasters and sustainable development (). New York: Springer.

Steckley, M., & Doberstein, B. (2011). Tsunami survivors' perspectives on vulnerability and vulnerability reduction: Evidence from koh phi phi don and khao lak, thailand. Disasters, 35(3), 465-487. doi:10.1111/j.1467-7717.2010.01221.x

Stepanov, A., & Smith, J. M. (2009). Multi-objective evacuation routing in transportation networks. European Journal of Operational Research, 198(2), 435-446. doi:10.1016/j.ejor.2008.08.025

Strunz, G., Post, J., Zosseder, K., Wegscheider, S., Muck, M., Riedlinger, T., . . . Muhari, A. (2011). Tsunami risk assessment in indonesia. Natural Hazards and Earth System Sciences, 11(1), 67-82. doi:10.5194/nhess-11-67-2011

Sumalyo, Y. (1996). Arsitektur dan tata kota colonial belanda di indonesia.paper on one day seminar the dilemma conservation and utilization of cultural heritage in SouthSulawesi

Sunarharum, T. M., Sloan, M., & Susilawati, C. (2014). Re-framing planning decision-making: Increasing flood resilience in jakarta. International Journal of Disaster Resilience in the Built Environment, 5(3), 230-242. doi:10.1108/IJDRBE-02-2014-0015

Suppasri, A., Hasegawa, N., Makinoshima, F., Imamura, F., Latcharote, P., & Day, S. (2016). An analysis of fatality ratios and the factors that affected human fatalities in the 2011 great east japan tsunami. Frontiers in Built Environment, doi:10.3389/fbuil.2016.00032

Suppasri, A., Shuto, N., Imamura, F., Koshimura, S., Mas, E., & Yalciner, A. C. (2013). Lessons learned from the 2011 great east japan tsunami: Performance of tsunami countermeasures, coastal buildings, and tsunami evacuation in japan. Pure and Applied Geophysics, 170(6), 993-1018. doi:10.1007/s00024-012-0511-7

Susmayadi, I. M., Sudibyakto, Kanagae, H., Adiyoso, W., & Suryanti, E. D. (2014). Sustainable disaster risk reduction through effective risk communication media in parangtritis tourism area, yogyakarta. Procedia Environmental Sciences, 20, 684-692. doi:https://doi.org/10.1016/j.proenv.2014.03.082

Synolakis, C. (1995). Damage, conditions of east java tsunami of 1994 analyzed. EOS Transactions, American Geophysical Union, 76(26), 257-257. doi:10.1029/95EO00150

Tabachnick, B. G., & Fidell, L. S. (1989). Using multivariate statistics (2nd ed.). New York: Harper & Row.

228

Talen, E. (1997). Success, failure, and conformance: An alternative approach to planning evaluation. Environment and Planning B-Planning & Design, 24(4), 573-587.

Talen, E. (1996). Do plans get implemented? A review of evaluation in planning. Journal of Planning Literature, 10(3), 248-259. doi:10.1177/088541229601000302

Tang, Z., Lindell, M., Prater, C., & Brody, S. (2008). Measuring tsunami planning capacity on U.S. pacific coast. Natural Hazards Review, 9(2), 91-100. doi:10.1061/(ASCE)1527- 6988(2008)9:2(91)

Tarigan, R. (2015). Perencanaan pembangunan wilayah/ urban and regional planning development. Jakarta: .Bumi Aksara.

Tetsushi, K., Akiko, N., Miki, K., & Sisira, R. N. C. (2006). Disaster prevention and management: An international journal.5(1), 92-110.

Tobin, G. A., & Montz, B. (1997). Natural hazards: Explanation and integration. New York: Guilford Press.

Tomascik, T., Mah, A., Nontji, A., & Moosa, M. (1997). The ecology of the indonesian seas;part one. Singapore: Periplus Editions.

Tourangeau, R., & Plewes, T. J. (2013). Nonresponse in social science surveys: A research agenda. Washington, D.C: National Academies Press.

Toya, H., & Skidmore, M. (2007). Economic development and the impacts of natural disasters. Economics Letters, 94(1), 20-25. doi:10.1016/j.econlet.2006.06.020

Tran, P., & Shaw, R. (2007). Towards an integrated approach of disaster and environment management: A case study of thua thien hue province, central viet nam. Environmental Hazards, 7, 271–282.

Tsuji, Y., Matsutomi, H., Imamura, F., Takeo, M., Kawata, Y., Matsuyama, M., . . . Harjadi, P. (1995). Damage to coastal villages due to the 1992 flores island earthquake tsunami. Pure and Applied Geophysics, 144(3-4), 481-524. doi:10.1007/BF00874380

Uitto, J. (1998). The geography of disaster vulnerability in megacities - A theoretical framework. Applied Geography, 18(1), 7-16. doi:10.1016/S0143-6228(97)00041-6

United Nations International Strategy for Disaster Reduction, UNISDR. (2007). Hyogo framework for action 2005-2015:Building the resilience of nations and communities to disasters . Geneva: International Strategy for Disaster Reduction.

United Nations International Strategy for Disaster Reduction, UNISDR. (2015). Sendai framework for disaster risk reduction 2015 - 2030 UNISDR.

229

United Nations International Strategy for Disaster Reduction,ISDR. (2002). Natural disasters and sustainable development: Understanding the links between development, environment and natural disasters, background paper no. 5. secretariat for the united nation’s international strategy for disaster reduction (ISDR), 2001. 10 pp. free available on the ISDR website at http://Www.unisdr.org/unisdr/wssdisdrdoc.pdf. Disaster Prevention and Management: An International Journal, 11(3), 222-223. doi:10.1108/dpm.2002.11.3.222.3

United Nations Office for Disaster Risk Reduction,UNISDR. (2013). From shared risk to shared value: The business case for disaster risk reduction – the 2013 global assessment report on disaster risk reduction. International Journal of Disaster Resilience in the Built Environment, 4(3) doi:10.1108/IJDRBE-06-2013-0020

United Nations Population Fund. (2007). UNFPA state of world population, 2007: Unleashing the potential of urban growth. (). New York: United Nations Population Fund.

United Nations. Dept. of Economic and Social Affairs. (2014). World urbanization prospects: The 2014 revision. New York: United Nations, Department of Economic and Social Affairs, Population Division.

Unnikrishnan, S., Singh, A., & Kharat, M. G. (2012). The role of mangroves in disaster mitigation: A review. International Journal of Environment and Sustainable Development, 11(2), 164-179. doi:10.1504/IJESD.2012.049180

Utexas. (2017). Power of a statistical procedure. Retrieved from https://www.ma.utexas.edu/users/mks/statmistakes/power.html

Vijayakumar, L., Kannan, G. K., & Daniel, S. J. (2006). Mental health status in children exposed to tsunami. International Review of Psychiatry, 18(6), 507-513. doi:10.1080/09540260601037581

Vries, J. d., & Broeck, J. v. d. (1997). Benelux: A microcosm of planning cultures. Built Environment, 23(1), 58-69.

Webster, D. H. (1958). Urban planning and municipal public policy. New York: Harper.

Weiss, C. H. (1998). Evaluation, 2nd ed. USA: Prentice Hall.

Western States Seismic Policy Council. (2011). Tsunami hazard mitigation and preparedness A perspective from state and territory tsunami programs in the high tsunami risk pacific region WSSPC Report 2011-01.

White, G. F. (1964). Choice of adjustment to floods. Chicago: Dept. of Geography, University of Chicago.

White, G. F. (1974). Natural hazards, local, national, global. New York: Oxford University Press.

230

Widianingsih, I., & Morrell, E. (2007). PARTICIPATORY PLANNING IN INDONESIA: Seeking a new path to democracy. Policy Studies, 28(1), 1-15. doi:10.1080/01442870601121320

Wignjosoebroto, S. (2004). Desentralisasi dalam tata pemerintahan kolonial hindia-belanda : Kebijakan dan upaya sepanjang babak akhir kekuasaan kolonial di indonesia, 1900- 1940. Indonesia:

Wildavsky, A. (1973). If planning is everything, maybe it's nothing. Policy Sciences, 4(2), 127- 153. doi:10.1007/BF01405729

Wilkie, L., & Leon, J. (2014). Urban planning and disaster. Australian Journal of Emergency Management, The, 29(3), 57-59.

Wilson, K., Hannington, S., & Stephen, M. (2015). The role of community participation in planning processes of emerging urban centres. A study of paidha town in northern uganda. . International Refereed Journal of Engineering and Science (IRJES), 4(6), 61- 71.

Winarso, H., & Firman, T. (2002). Residential land development in jabotabek, indonesia: Triggering economic crisis? Habitat International, 26(4), 487-506. doi:10.1016/S0197- 3975(02)00023-1

Winchester, P. (2000). Cyclone mitigation, resource allocation and post‐disaster reconstruction in south india: Lessons from two decades of research. Disasters, 24(1), 18-37. doi:10.1111/1467-7717.00129

Winchester, S. (2003). Krakatoa: The day the world exploded, august 27, 1883 (1st U.S. ed.). New York: Harper-Collins.

World Bank. (2011). Indonesia advancing a national disaster risk financing strategy – options for consideration. doi:https://www.gfdrr.org/sites/gfdrr/files/publication/Indonesia_DRFI_Report_FINALO ct11.pdf

World Bank, & United Nations. (2010). Natural hazards, unnatural disasters: The economics of effective prevention. Washington, D.C: World Bank. doi:10.1596/978-0-8213-8050-5

World Health Organization. (1992). Psychological consequences of disasters: Prevention and management. (). Geneva: World Health Organization.

Yeh, H. (2010). Gender and age factors in tsunami casualties. Natural Hazards Review, 11(1), 29-34. doi:10.1061/(ASCE)1527-6988(2010)11:1(29)

Yunus, S. (2000). Struktur tata ruang kota/ urban spatial structure. Yogyakarta.: Pustaka Pelajar.

231

Zapata-Marti, R. (1997). Methodological approaches: The ECLAC methodology. Center for the Research on the Epidemiology of Disasters (CRED), Assessment of the Economic Impact of Natural and Man-made Disasters. Proceedings of the Expert Consultation on Methodologies. Brussels, Universite Catholique de Louvain, Belgium.

Zhang, J. M., & Sun, X. D. (2013). Research of city (country) urban system planning evaluation. Applied Mechanics and Materials, 357-360, 1801. doi:10.4028/www.scientific.net/AMM.357-360.1801

232

BIOGRAPHICAL SKETCH

Fahmyddin Araaf Tauhid was born in FakFak, West Papua Province, Indonesia. He completed his undergraduate program in Architecture from University of Hasanuddin, Makassar

Indonesia in March 2000 and a Magister of Architecture on urban design in University of

Nottingham, UK in July 2007 under the Chevening scholarship. He also pursued the Diploma of

Leadership of Development from Coady International Institute at St Francis Xavier University,

Canada in December 2012 under Canadian International Development Agency/ CIDA scholarship.

He has been a lecturer at the Department of Architecture, UIN Alauddin Makassar,

Indonesia since 2006, and researcher in Urban Design Research Group in the same department.

He is actively involved in urban design and planning consultancy projects as well as a community facilitator for urban planning facilitation. He started pursuing a Ph.D. program in urban and regional planning at the University of Florida in 2014 under the Fulbright scholarship of USA. He received his Ph.D. from University of Florida in the Summer 2017. His research interests include urban disaster resilience and mitigation, smart growth in developing countries, urban community and change, quantitative approaches with statistical and GIS. His thoughts can be accessed in https://fahmyddincity.wordpress.com/ and https://twitter.com/FahmyddinTauhid

233