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Determination of Risk Areas in the Cimahi City (Drainage Sector) Based on City Sanitation Strategy Guidelines

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Determination of Risk Areas in the Cimahi City (Drainage Sector) Based on City Sanitation Strategy Guidelines Journal of the Civil Engineering Forum, September 2020, 6(3): 215-224 DOI 10.22146/jcef.53052 Available Online at http: https://jurnal.ugm.ac.id/jcef/issue/archive Determination of Risk Areas in the Cimahi City (Drainage Sector) Based on City Sanitation Strategy Guidelines Iwan Juwana*, Elvira Rizqita Utami Department of Environmental Engineering, Institut Teknologi Nasional (ITENAS) Bandung, INDONESIA jL. PHH Mustafa 23 Bandung 40123, West Java *Corresponding authors: [email protected] SUBMITTED 31 December 2019 REVISED 21 February 2020 ACCEPTED 30 April 2020 ABSTRACT Cimahi is one of the cities which participated in the Accelerated Habitat Sanitation Development Program in 2011 due to its poor sanitation conditions. The city experienced high flooding in 2018 as observed in the 36.4 hectares or approximately 0.76% of the total area affected even though its drainage system was discovered to be covering 89.87% in 2015. There are also several reports of displacement of residents and significant financial loss in the city due to flooding in the past decade and this means urgent attention needs to be provided to improve the condition of the city. Therefore, this study was conducted to calculate the level of risk from the drainage sector in each urban village of Cimahi City. This involves using scores ranging from 1 – 4, with a score of 1 indicating very low risk while 4 represents very high risk based on exposure factors such as percentage of inundation area, sanitation risk index (IRS) score, and the opinions of local government as well as impact factors such as population, population density, poverty rate, and urban/rural function. The research made use of both primary and secondary data with the primary data obtained through interviews with the population in the study area and local government representatives while secondary data were obtained from different institutions. The results showed 7 out of the 16 urban villages in Cimahi City are in Risk Category 1, 5 in Category 2, 1 in Category 3, and the remaining 2 in Category 4. This information with the risk category map for each village is expected to be used by the local government of Cimahi to analyze the flood-related problems better and create more effective solutions. KEYWORDS Drainage; Risk Score; Exposure Factors; Impact Factors; Risk Areas. © The Author(s) 2020. This article is distributed under a Creative Commons Attribution-ShareAlike 4.0 International license. 1 INTRODUCTION The recent growth, development, and increase in gates to drain water to its final destination, which population density in many areas of Indonesia is usually the sea (Imrona, Budiutama, including Cimahi City have increased the Darwiyanto, & Handayani, 2019, Wijaya & pressure on space and the environment and this Permana, 2017). is evident in the need for housing, Cimahi is one of the cities that participated in the industrial/service areas, and supporting facilities 2011 Sanitation Settlement Development which have led to the transformation of open land Acceleration Program (Samyahardja, 2019; and/or wetlands into built-up areas (Iwan Juwana, Triningtyas & Putri, 2019) based on the poor Muttil, & Perera, 2014, I. Juwana, B. Perera, & N. sanitation conditions as observed by the Cimahi Muttil, 2009, Noor & Pratiwi, 2016, Nursidika, City Government (Bahari, Kastolani, Waluya, & Sugihartina, Susanto, & Agustina, 2018, Sutiarani Geografi, 2016; Herdianti, Gemala, & Erfina, & Rahmafitria, 2016). This further has severe 2019) which are particularly drainage-related as impacts on the capacity of urban drainage and evident with the occurrence of flood in several flood control facilities and infrastructures such as areas of the city. According to the drainage rivers, reservoirs, flood pumps, and regulating master plan released by the Local Planning 215 Vol. 6 No. 3 (September 2020) Journal of the Civil Engineering Forum Agency (OPD), there are 36 floods spots and 2 most suitable method in this context (Diana floods areas in the Cimahi Tengah sub-district & Utari, 2019). alone which are mainly caused by the poor A pairwise comparison was conducted for condition of drainage infrastructure and public each parameter of both exposure and impact sanitation attitudes. These have, however, led to factors to determine the weight. The rating for infrastructural damage, economic loss, and a the exposure factor is as follows: decrease in community health in the last decade - Total population takes precedence over (Fauziah, Putu, Sukmono, & Karnisah, 2018; population density. Nandi, 2018; Wisata, Wardhani, & Sulistyowati, - Total population takes precedence over 2019). poverty rate. This, therefore, shows the need to develop an - The population is preferred over the appropriate sanitation strategy for Cimahi City urban/rural function. and this led to the conduct of the study to - Population density takes precedence over determine the risk areas related to the poverty rates. management of drainage system in order to have - Population density takes precedence over the adequate information in formulating the urban/rural functions. strategy (Fionita & Juwana, 2019; Yasya & - The poverty rate takes precedence over Juwana, 2019). urban/rural function. The rating for the impact factors are as 2 METHODS follows: This study was conducted using both primary and - Percentage of pool area takes precedence secondary data. The primary data were mainly on over IRS. the sanitation risk index of the community and - Percentage area of inundation takes opinion of local governments which were precedence over OPD perception. obtained through questionnaires while secondary - IRS takes precedence over OPD perception. data including the maps of the area, existing flood 2. Determination of Exposure Score spots, population, population density, and The exposure score was calculated by poverty rate were retrieved from the documents aggregating the values for the inundation provided by government institutions. area, IRS score, and OPD perception after the The research was conducted using the following weights have been obtained (Fionita & steps: Juwana, 2019; Sunik, Kristianto, & Khamelda, 1. Determination of Weights for Exposure and 2018; Yasya & Juwana, 2019). These values Impact were normalized using a computer-based The importance of exposure and impact application provided by the National factors is not equal, and this means there is a Development Planning of Indonesia need to assign certain weights for each of (BAPPENAS) with the value for the them and their subsequent parameters. The parameters obtained as follow: exposure factor has 3 parameters which are a. Percentage Area of Inundation the percentage of inundation area, IRS score, The value for each urban village in the studied and OPD perception while impact factor has 4 area was calculated using the following which are the population, population density, Equation (1) (Yasya & Juwana, 2019). 퐼푛푢푛푑푎푡표푛 퐴푟푒푎 푝푒푟 푈푟푏푎푛 푉푙푙푎푔푒 poverty rate, and urban/rural function. An %inundation area =퐴푑푚푛푠푡푟푎푡푣푒 퐴푟푒푎 푝푒푟 푈푟푏푎푛 푉푙푙푎푔푒 (1) Analytical Hierarchy Process (AHP) was, however, used due to its consideration as the b. IRS Score Based on EHRA 216 Journal of the Civil Engineering Forum Vol. 6 No. 3 (September 2020) This was calculated using the following steps: Q1: Is there a waste disposal facility - Stratification of Urban Village apart from feces disposal in your house? The samples were selected through A : (a). Yes, there is. stratified random sampling method based (b). No, there is not. on certain population differences (de - Weighting Oliveira Arieira, Santiago, Franchini, & de The weight for each question is Fátima Guimarães, 2016; Jing, Tian, & determined based on its level of risk to the Huang, 2015; Shields, Teferra, Hapij, & drainage (I Juwana, Muttil, & Perera, Daddazio, 2015) including population 2016a, 2016b; I. Juwana, Muttil, & Perera, density, poverty rates, areas drained by 2012; I Juwana, Perera, & Muttil, 2010; I. rivers, and areas affected by flooding. Juwana, B. J. C. Perera, & N. Muttil, 2009). - Determination of the Number of Family as For example, the previous sample Samples question is weighted 20% due to its A certain number of families were selected possible strong effects on the final IRS as samples through the use of the Slovin score. formula presented in the following - Environmental Risk Index Score (IRS) Equation (2). This was calculated after the information 푁 푛 = (2) 1 + 푁 ×푒2 has been obtained from the respondents using Equations (4) and (5). Where n is the number of samples, N is the 푛푢푚푏푒푟 표푓 푟푒푠푝표푛푑푒푛푡푠 푡ℎ푎푡 푠푒푙푒푐푡푒푑 푎 푝푎푟푡푐푢푙푎푟 × number of family in Cimahi City while e is %Q1= 푡표푡푎푙 표푓 푟푒푠푝표푛푑푒푛푡푠 an error of 10% 100% (4) - Determination of Number of Respondents nQ1 = weight × %Q1 (5) The number of respondents for each urban Where %Q1 is the percentage of village was also obtained based on the respondents that selected a particular stratified sampling method. This involved answer from question number 1 (Q1) while multiplying the number of family and nQ1 is the risk index score for Q1 after percentage of urban villages per stratum which the final risk index score was as shown in Equation (3). calculated by aggregating the risk index 푁푅1 = 푛 × %푅 (3) scores for all the questions. Where NR1 is the number of respondents c. Relevant Local Institution (Organisasi in stratum 1, n is the number of family Perangkat Daerah, known as OPD) card samples, and %R is the percentage of Perception urban village per stratum. This was a risk assessment conducted based
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