THE OPTIMAL PUBLIC PRIVATE PARTNERSHIPS MODEL for TRANSIT ORIENTED DEVELOPMENT Case Study Dukuh Atas, Jakarta, Indonesia

THE OPTIMAL PUBLIC PRIVATE PARTNERSHIPS MODEL FOR TRANSIT ORIENTED DEVELOPMENT Case Study Dukuh Atas, Jakarta, Indonesia

Daniel Azka Alfarobi

Supervisors: Ruth L Steiner, Professor William L. Tilson, Professor Christopher Silver, Professor

A MASTER RESEARCH PROJECT (MRP) PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN ARCHITECTURAL STUDIES WITH A CONCENTRATION IN SUSTAINABLE DESIGN UNIVERSITY OF FLORIDA 2015

To my Family

ACKNOWLEDGEMENT

This MRP might never have completed without help of many people that gave me contribution with data, information, knowledge and support, which I would like to express my gratitude to all of them.

I would like to foremost like to thank my family for their support during this period of my study, in particular to my wife Astriana Harjanti, my son Kimi Rafarel

Alfarobi, and my daughter Priyanka Namira Alfarobi.

I wish to express my sincere gratitude to Professor Ruth L. Steiner, Ph.D. for the guidance to complete this MRP with useful critiques and encouragement. My deepest thanks also goes to Professor Christopher Silver, Ph.D. FAICP and

Professor William L. Tilson who give me an opportunity to study Sustainable

Design at University of Florida.

To all relatives, friends, and others who in one way or another shared their support, thank you.

Last but not least, I gave deepest gratitude to Allah, SWT that made all of this possible.

Daniel Azka Alfarobi

TABLE OF CONTENTS

ACKNOWLEDGEMENT ...... 4 TABLE OF CONTENTS ...... 5 LIST OF TABLES ...... 8 LIST OF FIGURES ...... 9 LIST OF ABBREVIATIONS ...... 10 ABSTRACT ...... 11

CHAPTER 1. INTRODUCTION ...... 13

1.1 Background ...... 13

1.2 Problem Statement ...... 17

1.3 Research Objective ...... 18

1.4 Research Question ...... 19

1.5 Conceptual Frameworks ...... 21

1.6 Structure of Master Research Project (MRP) ...... 23

2. LITERATURE REVIEW...... 24

2.1 Public Private Partnerships (PPPs) ...... 25

2.1.1. The Form Scope of PPP ...... 25

2.1.2. PPPs scheme at The United States of America ...... 27

2.1.3. PPPs scheme in Indonesia ...... 29

2.1.4. Land Consolidation/ Right Conversions in Indonesia ...... 32

2.2 Transit Oriented Development (TOD)...... 33

2.2.1. A transport and land use development challenge ...... 34

2.2.2. Principles of Transit Oriented Development (TOD) ...... 36

2.2.3. TOD Implementation Stages in Jakarta ...... 37

3. RESEARCH METHODOLOGY ...... 39

3.1 Framework in Methodology ...... 39

3.2 Analytical Hierarchy Process (AHP) ...... 41

3.2.1. The Hierarchy Structure ...... 41

3.2.2. Determination of Priority ...... 43

3.2.3. Respondent/Expert Selection ...... 49

3.3 Cost Benefit Analysis ...... 50

4. GENERAL DESCRIPTION OF STUDY AREA ...... 52

4.1 MRT Development in Jakarta ...... 54

4.2 Transportation Condition in Jakarta ...... 57

4.3 Demography condition in Jakarta ...... 59

4.4 Economic Condition in Jakarta ...... 61

4.5 Alternative PPPs Concept at Dukuh Atas Area ...... 65

5. ANALYSIS ...... 70

5.1 Transit Oriented Development at Dukuh Atas ...... 71

5.2 Benefit Cost Analysis ...... 73

5.3 Analytical Hierarchy Process (AHP) ...... 81

6. DISCUSSION ...... 84

7. RECOMMENDATION AND CONCLUTION ...... 85

APPENDICES

1. Pairwise Comparison Questioner ...... 86

2. Recapitulation Data of Questioner ...... 91

3. Benefit Cost Analysis Calculation ...... 97

4. Analytical Hierarchy Process Calculation ...... 108

REFERENCES ...... 112

LIST OF TABLES

Table 2.1 Comparison Function between Urban and Neighborhood TOD ...... 34

Table 2.2 Staging of Rail-Based TOD Implementation in Jakarta ...... 38

Table 3.1 Pairwise Comparisons Matrix ...... 44

Table 3.2 Comparative Assessment Scale ...... 45

Table 3.3 Random Consistency Index (RI) ...... 48

Table 4.1 Total Population and Population Density based on Census Results in 2010 and Projected Population in 2014 according to the Municipality/Regency ...... 60

Table 4.2 GRDP at Current Market Prices by Industrial Origin of DKI Jakarta (Million Rupiah), 2007-2013 ...... 63

Table 4.3 GRDP at 2000 Constant Prices by Industrial Origin of DKI Jakarta (Million Rupiah), 2007-2013 ...... 64

Table 4.4 Advantage and Disadvantage of BOT Model in the Context of TOD at Dukuh Atas ...... 66

Table 4.5 Advantage and Disadvantage of Right Conversion Model in the Context of TOD at Dukuh Atas ...... 68

Table 5.1 Average CoLF 2007 – 2014 ...... 75

Table 5.2 Size of the Building...... 76

Table 5.3 Underground and Artificial Ground Development’s Cost ...... 76

Table 5.4 Occupancy Rate ...... 78

Table 5.5 BOT Model (NPV and IRR Analysis) ...... 79

Table 5.6 Right Conversion Model (NPV and IRR Analysis) ...... 80

Table 5.7 Weight of sub Hierarchy Benefit and Cost ...... 81

Table 5.8 Overall Weights of Criteria ...... 82

Table 5.9 Benefit Sub Hierarchy Economic (Alternative Priorities) ...... 82

Table 5.10 The Optimal PPPs model from AHP Analysis ...... 83

LIST OF FIGURES

Figure 1.1 MRT Station – Phase 1 ...... 15

Figure 1.2 Conceptual Framework ...... 21

Figure 2.1 PPPs Regulation Diagram in Indonesia ...... 30

Figure 2.2 The Basic Correlation between Car, Transit and Walking Environment ...... 35

Figure 3.1 Framework in Methodology ...... 40

Figure 3.2 AHP Hierarchy Structure ...... 42

Figure 4.1 DKI Jakarta Map...... 53

Figure 4.2 Map of South to North MRT Line ...... 55

Figure 4.3 MRT station catchment areas ...... 57

Figure 4.4 Traffic Condition at Dukuh Atas Area ...... 58

Figure 4.5 BOT Model ...... 66

Figure 4.6 Right Conversion Model ...... 67

Figure 4.7 Map of Study Area...... 69

Figure 5.1 Concept TOD at Dukuh Atas, Jakarta ...... 71

Figure 5.2 Public Space concept at Dukuh ...... 72

Figure 5.3 Underground Connectivity and Artificial Ground ...... 73

Figure 5.4 The Conceptual Design of the Building at Dukuh Atas ...... 77

Figure 5.5 Sectional Drawing ...... 77

LIST OF ABBREVIATIONS

AHP Analytical Hierarchy Process

BCA Benefit Cost Analysis

BCR Building Coverage Ratio

BRT Bus Rapid Transit

FAR Floor Area Ratio

GOI Government of Indonesia

GRDP Gross Regional Domestic Product

IDR Indonesian Rupiah

IRR Internal Rate of Return

JABODETABEK Jakarta, Bogor, Depok, Tangerang, Bekasi

JICA Japan International Cooperation Agency

MRT Mass Rapid Transit

NPV Net Present Value

PPP Public Private Partnership

TAD Transit Adjacent Development

TDM Transport Demand Management

TOD Transit Oriented Development

ABSTRACT

Transportation demand management encourages people to use public transportation and Transit Oriented Development (TOD) is one of the concept that can support transportation demand management. In addition with implementing TOD concept, sustainable financing become a major issue since public funding is limited. Public Private Partnerships (PPPs) can be an alternative mechanism to address this problem. To make the project more attractive for investor point of view, finding the optimal PPPs concepts is important. According to Japan Cooperation International Agency (2012), two types of PPPs mechanisms are commonly used to develop TOD. The first is Built Operate Transfer (BOT) model and the other is Right Conversion model. This study elaborates both of these models in order to find the optimal PPPs model. The Dukuh Atas area in Jakarta, Indonesia is chosen as a case study since this area is possible to develop using the TOD concept. Two different methods are used in this study. First is Benefit Cost Analysis (BCA), and the other is Analytical Hierarchy Process (AHP). The BCA compares the investment cost with potential net cash flow from the Dukuh Atas project. The discount rate is calculated based on the average 8 years data of Cost of Loanable Fund from commercial banking in Indonesia. The result of the analysis showed that Right Conversion Model has a higher Equity Internal Rate of Return (IRR) compared to the BOT model. The equity IRR right conversion model is 32% while the BOT model is only 30%. AHP analysis is an expert choice model. This tools is commonly used to solve a problem with multi-criteria analysis. In connection with finding the optimal model for PPPs model, this analysis involves not only economic variables but also non- economic variables, such as social costs and regulation issues. When calculating only the economic variable, the result from the analysis shows the same result with BCA, the right conversion model has the better figures compares to the BOT model. The priorities score from Right Conversion model is 0.542 while BOT model only 0.458. After involving non-economic variables, the result from AHP analysis shift from Right Conversion Model into BOT model. The BOT model has the priorities score of 0.577, while right conversion model is only 0.423. The analysis shows after involving non-economic variables, the BOT is the most optimal PPP model for TODs.

CHAPTER 1 INTRODUCTION

1.1 Background

Transportation demand management (TDM) encourages people to use public transportation and transit-oriented development (TOD) is one of the concepts that can support TDM. TOD is a concept that integrates transit and land use.

Furthermore, TOD combines concepts of compact and pedestrian-oriented development with mixed land use. The basic idea of TOD is to make the city more livable and optimize the transit system (Cervero, R., & Sullivan, C, 2011).

In addition with implementing the TOD concept, sustainable financing has become a major problem because TOD needs a lot of funding. PPP can be an alternative mechanism to address this issue. Private sector involvement is important to solve the limited source of funding. According to Suzuki, Cervero, and Iuchi (2013), involving the private sector is possible as long as value capture from TOD can be used as tool for generating the revenue to pay back the investment.

The PPP concept is a win-win solution between the private and the public sector.

In the PPP concept, the government could provide basic infrastructure, such as rail development, while the private sector can be involved in supporting facility for instance like the transit system, station development, parking facilities or area development surrounding the train station or the main bus shelter.

This study will use Jakarta as a case study. As a capital city of Indonesia, Jakarta becomes a growth center for other city surrounding Jakarta, and makes Jakarta

13 become a destination for many people who lived surrounding Jakarta. According to

Jakarta Provincial Government (2013), there were 21 million movements per day in Jakarta in 2010 and this number is increasing every year. Provision of better public transportation and integrated land use are some of the solutions to address the transportation issue in Jakarta. However due to public fiscal limitations, private sector involvement is necessary in order to reduce the gap between the demand and the supply of infrastructure.

Trans Jakarta Bus Rapid Transit and JABODETABEK Commuter Line Train are the public transport system that is provided by the government. Trans Jakarta Bus

Rapid Transit is provided by the local government, while the JABODETABEK

Commuter Line Train are managed by the central government. The involvement of different authorities makes the integration between these two public transportation systems difficult and makes people still prefer using private vehicle since shifting between the modes is not convenient. On the other hand, Jakarta is also having a problem with sporadic horizontal growth or urban sprawl. Low levels of service in public transport and sporadic horizontal growth accelerate the traffic congestion in

Jakarta. On 2014, Jakarta Provincial Government started the development of MRT to improve the public transport services. The phase 1 is from Lebak Bulus to

Bundaran HI, around ± 16 Km with 12 stations (Figure 1.1).

Figure 1.1 MRT Station – Phase 1

BUNDARAN HI STATION U N D DUKUH ATAS STATION E R G SETIABUDI STATION R O U BENHIL STATION DKI JAKARTA N D ISTORA STATION

SENAYAN STATION

PHASE 2 BLOK M STATION

PHASE 1

BLOK A STATION E BANTEN PROVINCE L E V E HJ NAWI STATION T E D LEGEND CIPETE STATION

MRT LINE WEST JAVA PROVINCE COMMUTER LINE LEBAK BULUS STATION FATMAWATI STATION

Source: Jakarta Provincial Government, 2010

In order to optimize the benefit of MRT, its development will need to be supported with infrastructure development such as integration between MRT stations, BRT shelters and commuter line station. The TOD system is one of the alternatives that can be developed in Jakarta in connection with integration between stations and pedestrians with residential and commercial areas.

According to the Jakarta Provincial Planning Agency and a study from the Japan

International Cooperation Agency (2012), Dukuh Atas is one of the potential locations that can be developed for TOD. Dukuh Atas is an area that has a

15 significant role for transportation in Jakarta. It is located at the down town Jakarta and dominates the commercial area. Sudirman train station for commuter line and

Dukuh Atas bus rapid transit shelter for Trans Jakarta are also located at this area.

However, those stations aren’t integrated and riders of either system have a difficult time switching from the train station to the bus station and vice versa. According

Jakarta’s Planning Agency, an MRT station and airport trains station will also located in the Dukuh Atas area.

The PPP scheme for TOD at Dukuh Atas is one of the alternative concepts that can be applied to solve the limitation of public funding. It combines public services and business profitability. In many PPPs project, the BOT concept is usually used in infrastructure projects, such as toll road or port’s development. However other models of PPPs, such as Build Operate Own or rights conversion, like in Japan, are still possible to use as long as all of the parties agree. From the investor’s point of view, the higher internal rate of return makes the project more interesting. On the other hand, from the government perspective the less it spends, the better. This conditions leads to a question, what is the best PPPs model for TOD?

This study focuses on analyzing the PPPs model for TOD Dukuh Atas. The first method uses Cost Benefit Analysis with discounted cash flow analysis to find the optimum model from a profitability point of view. The second model uses multi- criteria analysis to find the best model from the stakeholder point of view. All of the models are from the investor’s point of view. Both of the result will be compared to find the best model of PPPs for TODs at Dukuh Atas.

1.2 Problem Statement

Urban sprawl is a recent phenomenon in almost developing countries. A development away from the city center and car dependence is the characteristic from the urban sprawl. This condition is worst while people don’t have any choice except using their car to travel to their destination. Jakarta, Indonesia is perfect example from this situation. The increasing land value at the center of Jakarta makes people choose suburban areas for their residential and commute everyday using their car. This condition can cause some problems such as congestion and heavy pollution.

As the capital city of Indonesia, Jakarta has become a magnet for people in

Indonesia. However the increasing population in Jakarta has not been followed with infrastructure development. Currently, Jakarta doesn’t have a reliable public transportation. Starting in 2014, the local government of Jakarta together with central government of Indonesia developed the MRT system in Jakarta. The first phase of the development is from South to North and then will be from East to West.

The South to North line is under construction now while East to West is still under feasibility study. The development of MRT will need to be supported with other facilities, such as park and ride and pedestrian amenities to increase the ridership.

The integration of land use using a TOD concept is important to maximize public transit ridership. The TOD approach can not only solve the transportation issue, but also address urban sprawl problems in Jakarta. Furthermore the TOD approach is shifting the development strategy from horizontal to vertical approach with transit system connectivity.

Implementing the TOD concept is complicated, sustainable financing has a significant role for the success of TOD. Since the public funding in Jakarta is limited, alternative sources of financing have to be explored. PPPs are one of the schemes that can be used to solve the financing issue. The basic idea of the concept is a win-win solution between the government and the investor. The government can get the benefit from public service improvement and the investor can get the profit. The successful key from using PPP concept is defining the optimal PPPs scheme. This study elaborate the optimal PPPs scheme for TOD and using Dukuh

Atas project as a case study since according to Japanese International Cooperation

Agency (JICA) (2012) the TOD project at Dukuh Atas is possible to finance using a PPP scheme.

1.3 Research Goals and Objectives

The goal of this research is to find the most optimal PPP model for Transit Oriented

Development at Dukuh Atas Jakarta from investor perspective. This goal will be achieved through the following objectives:

1. Analyzing each of PPPs model at Dukuh Atas Jakarta using Cost Benefit

Analysis.

2. Analyzing each of PPPs model at Dukuh Atas Jakarta using multi-criteria

analysis.

3. Comparing the output of Cost Benefit Analysis and Multi Criteria Analysis.

4. Analyzing the optimal PPPs model for development of TOD Dukuh Atas

Jakarta.

1.4 Research Question

New Urbanism concept is an approach for redesigning the neighborhood to become less automobile oriented and encourage more people to walk, bicycle, and ride transit for travel (Cervero and Radisch 1996). The key for New Urbanism approach are compact development, mixed land use, pedestrian oriented and prominent civic space area. On the other hand research supports a claim that pedestrian orientation and the integration between transit and land use will reduce automobile travel

(Cervero, Radisch 1996). Furthermore according to Suzuki, Cervero, and Iuchi

(2013), the integration between transit system and land use is one of the strategies to become a sustainable city. Many cities in developed country use this strategy in order to make their city more livable. For instance in Singapore, they used a radial corridor principle to connect the central area with regional and sub-regional areas using a high-performance transit system. This strategy is a success> Singapore ranks as the most livable city in Asia based on ECA International research in 2015.

Other cities like Tokyo in Japan, Hong Kong in China or Chicago in the USA are also other examples of how the integration between transit and land use makes the city more livable.

Integration between high access to the transit system and well-designed urban space will reduce the use of automobile since it will encourage people to walk and bicycle.

These concepts are the basic idea of TOD. Furthermore implementing the TOD concept requires a high level of investment and financial sustainability is the most important key. Cities like Singapore, Hong Kong and Tokyo have been successful in implementing the TOD concept because they create a synergy between the public

19 and private funds under the PPP mechanism, they can also create the value capture from TOD. The investor can see the value capture from TOD concept and together with the government transfer it into a PPPs model. This explanation leads to a question “what is the optimal PPPs model for implementing TOD?” The optimal PPPs model is important in order to make a balance between public benefit and profitability from the investor. In addition to elaborating the concept of TOD and PPPs model, this study uses Dukuh Atas – Jakarta Indonesia as a case study.

The reason is because implementing the TOD concept in Jakarta is necessary to make the city more livable and according to a previous study from JICA, a TOD project in Dukuh Atas is feasible to develop.

1.5 Conceptual Frameworks Figure 1.2 Conceptual Frameworks Sustainable City

Compact Development Mixed Land Use Walk Friendly Urban Development Transit system connectivity

Influence Travel Demand TRANSIT ORIENTED DEVELOPMENT (TOD) BACKGROUND

Limited Public Funding Availability High Investment

Public Private Partnership Scheme Investor Profitability

RESEARCH QUESTION What is the PPPs best model for TOD development? Public services improvement

Value Capture from TOD

JICA Study 2012 TOD at Dukuh Atas Jakarta - Case Study

Built Operate Transfer (BOT) Model Conversion Right Model

ANALYSIS

Benefit Cost Analysis – Discounted Cash Flow Multi Criteria Analysis - AHP

21 The Optimal PPPs model for TOD OUTCOME Conceptual framework from this Master Research Project (MRP) is formulated from the literature review (Figure 1.2). According Cervero (2002) some variables influence travel demand, such as compact development, mixed land use, walk friendly urban development, and transit system connectivity. Furthermore, he explained that a city with good transit system become more sustainable and more livable compare with other city without a transit system.

TOD is one strategy to make a city more livable. According to Cervero and Sullivan

(2011), TOD is a promising tool for breaking the urban sprawl issue and car dependency by increasing transit use and reinforcing compact station area development. On the other hand TOD needs a high investment and the availability from the public funding is limited. Cities like Singapore, Tokyo, Hong Kong, and others cities mostly in developed countries can generate revenue and capture value from property development through implementing TOD concept. Many of those cities use a

PPP approach to address the funding issues.

Since implementing the TOD concept is important for sustainable cities and PPPs is an alternative financing strategy then the most optimal PPPs scheme has to be defined as a win – win solution between the investors and government. This study elaborates the optimal PPPs scheme from investor point of view and use Dukuh Atas Jakarta as a case study.

1.6 Structure of Master Research Project (MRP)

The MRP report is structured into six chapters organized as follows:

a) Chapter 1 Includes the background of the research, problem statement,

research objective, research question, and conceptual framework.

b) Chapter 2 Deals with literature review including elaborate the concept of

TOD and PPPs.

c) Chapter 3 Explained about Cost Benefit Analysis and Multi Criteria

Analysis as a research methodology at this research.

d) Chapter 4 Describe TOD at Dukuh Atas as a case study area.

e) Chapter 5 Discussed the results or findings of the research in connection

with the optimal PPPs model for TOD.

f) Chapter 6 Conclusions of this research

g) Chapter 7 Recommendation

CHAPTER II LITERATURE REVIEW

Investment is a complicated decision. Many criteria and methods are available for choosing the right investment decision. Investor tends to be more careful for uncertain investment condition such as political instability, complicated bureaucracy, or volatile economic condition. In the normal condition, the investor chooses the highest rate of return for investment. However, in certain conditions, investors give close attention in other aspect such as the duration of the payback period, social risk from the project, and the supporting regulation from the government. The longer the duration of the investment, the more complicated the analysis of the investment.

In many countries, the government gives special incentives mostly in a project with special characteristic such as a large project and a long-term investment, Greenfield project (a new project started from zero), and others. The incentive can be in tax reduction, special interest rate or other considerations that reduce risk or costs.

PPP is one strategy to accelerate the development of projects. It can reduce the gap between the infrastructure demand need with the availability of public funding. This literature review presents some aspects of the PPP and TOD concepts.

2.1 Public Private Partnerships (PPPs)

At the first time PPP was introduced in early 1990s, many stakeholders thought that

PPP has the same concept as privatization. However, according to Levy (2011), the

PPP concept is completely different from privatization. The PPP concept is giving an operational project to the private sector in a long term (concession or lease type contract) but the ownership of the project is still maintained by the public authority.

Colverson and Oshani (2012) define PPPs as a different type of contractual agreement between the public agency and private sector for the purpose of public infrastructure development and services provision. From the definition of PPPs, some experts argue that there is no partnership in the PPP concept; the relationship for a PPP is straight forward between lessor and lessee. However, the idea of the PPP is to cover the limitation of public services budget, the trend of infrastructure development remain stagnant due to budget limitation while the demand has risen exponentially. PPP is an alternative financing to develop many projects in order to make public services better

(levy, 2011).

2.1.1 The Form Scope of PPP

According to Levy 2011, PPPs can take several forms including:

1. Build Operate Transfer (BOT)

In this form, the private entity develops a project according to the public agency’s

guidance, such as providing design, construction, operational and maintenance for

a certain period or concession. The private entity collects the funds during the

concession period then give the project back into the public agency without any

compensation.

2. Build Own Operate (BOO)

With a BOO contract, a private entity has the right to develop, finance, design,

build, own, operate, and maintain a project for a certain period. The private entity

covers all the construction risk as well as the operating risk of the project. Over all,

this scheme is almost the same as BOT however in BOO there is no transfer of the

project at the end of concession since the value of the project is already zero. This

kind of approach is quite common in the power generation sector.

3. Design–build–operate–maintain (DBOM):

A private entity provides design build services then construct the public facility

based on the design, furthermore they also responsible for operational and

maintenance of the project for certain period. The idea of this approach is to get a

high quality from the project since the private entity not only designs and builds

but also has a responsibility to operate and maintain the project for the certain

period.

4. Lease–develop–operate (LDO):

A private entity leases a facility from a public agency, and is responsible to provide

equity for upgrading or renovating the facility. This private entity has the right to

operate the facility under a contract with the public agency.

5. Availability payment process:

The public agency periodically pays to private entity a certain amount in connection

with providing a service. All service specifications are under an agreement between

the public agency and the private entity.

6. Shadow tolling:

In connection with collecting the revenue from a tolled roadway, a private entity

gets the payment from public agency using a certain formula rather than physically

collecting revenue from the toll’s user. The public agency and a private entity agree

on a formula at the beginning of the PPP.

Beside all the forms described above, other forms of hybrid financing in PPP model are still possible as long as all the stakeholder agreed to put these terms into an agreement.

2.1.2 PPPs scheme at The United States of America

The Federal Highway Administration (FHWA) realizes that the gap between

America’s infrastructure requirements with the ability to fund infrastructure development through public funding is widening and a need for private sector involvement to reduce the gap (Levy, 2011). In addition with private sector involvement, the FHWA recognized that PPPs are one of the alternatives that can be applied to reduce the gap.

According to Levy (2011), in the USA, the public agency already has a financial guidance to execute PPP projects, these guidance can be use both for a mega project or smaller projects. Some of the guidance are as follows:

1. Cost Estimate

The cost estimate is the total cost for the whole project from providing the design,

construction, acquisition cost, insurance cost, and other cost including mobilization

and demobilization cost. All costs are based on standard accounting methods and

generally do not include costs of acquiring revenue (taxation, mortgage interest

payment, and other items included in DOT Order 4600.17A/ a guidance of financial

term and condition for PPPs mechanism provided by The US Government).

2. Implementation Plan

The implementation plan includes all aspect for completing the projects, such as

estimated expenditure to be covered by projected revenue, the project’s schedule

plan, and operational and maintenance cost assumptions. The forecasting of project

profitability is also made using several sensitivity analysis in order to find the

financial figures of the projects such as cost sensitivity, revenue sensitivity or other

unpredictable condition like unanticipated environmental concerns that could be

arise, high technology that can reduce the cost or the potential for litigation.

3. Revenue Sources

The revenue sources are projected using normal conditions and potential changes

in expected revenue that may affect the whole project. These changes may include

the delays of the project or changes in government rules that could affect the

project’s revenue.

4. Cash Flow

Cash flow is the most important item for the continuity of projects. The revenue of

the projects has to cover all operational and maintenance cost and also project

obligation and expenditure payments. This guidance includes an annual schedule

of cash needs and available cash to meet those needs.

Overall, this guidance tries to address some of the concerns in connection with the completion of the projects.

2.1.3 PPPs schemes in Indonesia

The Government of Indonesia (GOI) already has a policy in connection with PPP schemes in Indonesia. The policy has changed several times in order to attract and make it more competitive from the investor point of view. Furthermore the GOI, through the

National Development Agency, issues a guidance handbook every year as a reference for the investor who wants to participate in infrastructure development in Indonesia.

Figure 2.1 PPPs Regulation Diagram in Indonesia

Source: National Development Planning Agency, 2013, page 7.

The regulation as shown at the picture 2.1 above are discussed PPPs mechanism in

Indonesia (National Development Agency, 2013), in general the PPPs regulation in

Indonesia is governing about:

• Cooperation between the Government and the private sector

• Land acquisition.

• Environmental assessment and protection.

• Development’s regulation for sea, rail, air and land transportation, water supply and

sanitation, energy and telecommunications.

The commitment from the GOI to attract the investor is clearly defined at the regulation of land acquisition.

The GOI is also issued some terms and conditions for PPP schemes in Indonesia. This terms and conditions are made based on win-win solutions approach for investor benefit and public service (social) benefit. Some of the term and conditions are:

1. The project must be economically feasible based upon the social cost benefit

analysis;

2. The project must be technically, legally, and financially feasible based on the

feasibility study;

3. Project’s risk assessment is already done;

4. The need of land acquisition requirement are already identified;

5. If necessary, the need of government support/guaranteed have to identified;

6. Preliminary Environmental Impact Assessment (EIA) have to be started or in case

the project doesn’t need EIA then recommendation from authorized agency for

environmental permit is necessary; and

7. Preparing the plan for land acquisitions and resettlement.

It is clear that PPP projects are not only feasible from the private sector economic perspective but it has to be also feasible from the social cost benefit analysis.

2.1.4 Land Consolidation/ Right Conversions in Indonesia

Land consolidation is one of the possible models for the PPP mechanism. According to Coelho , Portela, and Pinto (1996), land consolidation is a method that tries to solve the spatial issue by eliminating certain types of land fragmentation and creating the new concentrations plot accompanied with infrastructure development, such as new road, irrigation facilities and other services. Furthermore Yoshida (2003) mentioned that land consolidation is an arrangement of ownership and land use with involving community participation by donates partially of their land for public space in order to make the environment better.

Four aspects should be analyzed in connection with land consolidation process: economic, social system, physical and environment (Coelho , Portela, and Pinto, 1996).

The success of land consolidation will depends on these four aspects.

In the context of the land consolidation process in Indonesia, there are several case studies in Indonesia one of them is in Denpasar Bali in 1982. However, in the Jakarta context, there is no case example of land consolidation implementation. According to

Yoshida (2003), this conditions probably exists for two reasons. First, some parts of

Jakarta area are already improved by the Kampung Improvement Program. This program uses a regional budget (APBD) to improve some slum areas in Jakarta. The second reason is that most land in the urbanized area in Jakarta is already registered with a land title, and existing land owner may not be willing negotiate with anyone about development.

2.2 Transit Oriented Development (TOD)

Before describing TOD, several terms need to be defined. Parker, McKeever, Arrington and Smith-Heimer, (2002) as cited in Lund, Cervero, and Wilson (2004) defines TOD as:

…moderate to higher-density development, located within an easy walk of a major transit stop, generally with a mix of residential, employment and shopping opportunities…[It is] designed for pedestrians without excluding the auto [and can be achieved through either] new construction or redevelopment of one or more buildings whose design and orientation facilitate transit use (Parker, McKeever, Arrington and Smith-Heimer, 2002).

Furthermore the Washington Metropolitan Area Transit Authority (2005) as cited in

Faghri (2012) defines TOD as an area near the transit stop with smart growth concept development, high accessible for pedestrian and bicycles, less car dependences and enhance physical connection between the transit stop with the surrounding area.

According to Calthrope (1993), TOD can be divided into two main urban TOD and neighborhood TOD. The urban TOD is usually located only ½ or 1 mile from the main transit station, and has the potential for commercial and high density residential. On the other hand neighborhood, TOD is located within 10 minutes or not more than 3 miles walking distance from a feeder line transit. Neighborhood TOD usually has lower density residential and smaller scale of commercial area compared to urban TOD

(Table 2.1).

Table 2.1 Comparison Function between Urban and Neighborhood TOD

Function Neighborhood TOD Urban TOD Public 10% – 15% 5% – 15% Commercial/Office 10% – 40% 30% – 70% Residential 50% – 80% 20% – 60% Source: Calthrope, 1993

Furthermore, Reconnecting America and the Center for TOD (2008) divide the typology of TOD based on frequent public transportation services, and the land use characteristic such as: regional center, urban center, suburban center, transit town center, urban neighborhood, transit neighborhood, special-use/employment district and mixed-use corridor.

In general, TOD can be summarized as an area with commercial and medium to high- density residential land uses located within walking distance from public transit. Some important elements from TOD are the transit system, mixed land use, compact development, and walkable communities.

2.2.1 A transport and land use development challenge

The competitiveness of public transit relative to the car is determined from the characteristic of transport and land use (Bertolini, Curtis and Renne, 2009). Thus condition makes the characteristic both of transport and land use become very important for developing TOD. According to Bertolini and Le Clercq (2003) as cited in Bertolini, Curtis and Renne (2009), two basics correlations exist between transport and land use, “first is between the speeds of transportation system and second is

34 between the flexibility of transportation system and the degree of spatial concentration”

(page 4).

A car has a high flexibility, high speed but low capacity that is suitable for low density urban environments. On the other hand public transit has a high speed, high capacity but low flexibility that is suitable for high density urban environment. Furthermore the non-motorized mode has high flexibility, high capacity but lower speed and spatial reach. In order to provide an alternative for a car use, the competitive advantage from public transit and non-motorized need to be combined. According to Bertolini, Curtis and Renne (2009) the combination of public transit and non-motorized modes are important for implementing the TOD concept (Figure 2.2).

Figure 2.2 The Basic Correlation between Car, Transit and Walking Environment

Source: Bertolini, Curtis and Renne, 2009, page 5.

2.2.2 Principles of Transit Oriented Development (TOD)

TOD is a one of the concept to address the urban issue such as urban sprawl and congestion. The TOD concept allows development to move back to the city center and optimize the transit system and the land use. According to Calthrope (1993), the development principles of TOD in connection with addressing urban design can be summarized as follow: a. Controlling growth on a regional level to be more compact and supports the

function of transit. b. Placing a commercial, residential, offices and public functions within a comfortable

walking distance from the point of transit. c. Creating a road network that is friendly to pedestrians. d. Maintaining the regional ecological conditions and increase open public space

quality. e. Encourage development that is infill and redevelopment in the transit area.

However the application of TOD concept in the transit area development is also subject to criticism. One of them is the failure of planners in applying a comprehensive concept of TOD called Transit Related Development (TRD) or Transit Adjacent Development

(TAD). TAD is an area that physically adjacent to transit, but in functional characteristics, such as land use composition, accessibility, and design, are not connected with the transit system. TAD breaks many or all of the rules and principles

36 of the TOD concepts, If TOD encourages the users to walk and using modes of transit,

TAD tends not to stimulate users to walk and use transit modes.

2.2.3 TOD Implementation Stages in Jakarta

In Jakarta, several transit points can be developed as intermodal transit integration.

According to Master Plan of Jakarta Metropolitan Area (JMA) Railway system (2012),

Dukuh Atas and Manggarai station are some of the transit point that can be developed as intermodal transit integration. However implementing of TOD concept in Jakarta is still a big challenge due to some problems. Land acquisition and sustainable financing are some of the challenge that need to address for implementing TOD in Jakarta.

Prijanto (2013) in Dirgahayani, Syabri, Waluyo (2014) classified the TOD implementation in Jakarta into three level categories, as follow:

1. Seamless Mobility

In this stage, the transit agency improves the accessibility from and to the station

with reducing the pedestrian flow interruption from road traffic.

2. Sustainable Neighborhood

In this stage, the station is not only become a transit for the passenger but also

become a place for their activity.

3. Optimum Growth District

In this stage, the overall transit area is successfully creating a distinctive and vibrant

transit oriented place.

Furthermore, a little different with Prijanto (2013), Dirgahayani, Syabri, Waluyo

(2014) classifies the TOD in Jakarta based on stage of implementation. The implementation of TOD in Jakarta can be described in three stages, as follow:

Table 2.2 Staging of Rail-Based TOD Implementation in Jakarta

No Stage Facilities 1. Station as Destination: ▪ Parking or park and ride spaces (bicycle, motorcycle, and car) Rail station revitalization ▪ Drop off/ pick up bays ▪ Pedestrian way ▪ Commercial area (underground and upper ground) 2. Sustainable Transit – Oriented ▪ Neighborhood pedestrian facilities Neighborhood: ▪ Neighborhood cycling facilities Integration with activities within walking ▪ Green open space distance or rail - service catchment area (up to 800 m radius from the rail station) ▪ Traffic calming facilities ▪ Commercial centers ▪ Vertical housing for high, medium, and low income people 3. Seamless Mobility: ▪ Sustainable transit oriented neighborhood Citywide multimodal transit and land use ▪ Integrated feeder system integration (beyond TOD) ▪ Intermodal facility ▪ Pedestrian way from intermodal facility to the station ▪ Cycling facilities at the intermodal facility

Source: Dirgahayani, Syabri, Waluyo (2014), page 7

CHAPTER III RESEARCH METHODOLOGY

This study uses BCA and Multi Criteria Analysis for determining the optimal PPPs model for TOD. BCA compares between initial investments with net cash flow and only involve economic variables. On the other hand, multi-criteria analysis use both economic and non-economic variables. Many tools can be used for multi-criteria analysis; one of the most commonly used for choosing the optimal alternative with many criteria is analytical hierarchy process (AHP). Two different alternatives of PPP models for TOD discussed in this study are the BOT model and the Right Conversion

Model. Both of this alternatives are analyzed using BCA and AHP model.

3.1 Framework in Methodology

The first step in this study is calculating the economic benefit from TOD at Dukuh Atas

Jakarta using BCA. The net present value (NPV) from the BOT and Right Conversion

PPP models are compared in order to find the highest profitable model from investor point of view.

The second step is analyzing both of the BOT and Right Conversion PPP models using multi-criteria analysis. The hierarchy structure is the important key for developing multi-criteria analysis using AHP. Based on the hierarchy structure, a questionnaire is constructed and given to a group of respondent who are knowledgeable of the topic of the analysis. The priority scale from the respondent experts is the final result from AHP.

The main difference between the AHP and BCA model is the variables involved. In

AHP, non-economic parameter such as social and bureaucracy variable are discussed

to find the optimal of PPPs model from investor point of view. Since AHP is an expert

choice model then the subjectivity from the respondent is very dominant.

The last step from this study is comparing the result from BCA with AHP in order to

get the best optimal PPP model for TOD at Dukuh Atas.

Figure 3.1 Framework in Methodology

Alternatives of PPPs model for TOD Development . Right Conversion Model . BOT Model

BCA AHP

Economic Variable Investment Cost Net Cash Flow Hierarchy Structure Non-Economic Variable

Concession Period Expert Choice Model (For BOT Model)

Discount Factor Priority Scale

Net Present Value The highest priority score of alternative PPPs Model

The Highest NPV of Alternative PPPs Model Comparison

The Optimal PPPs Model for TOD

Source:3.2 Analytical Author (modified Hierarchy diagram Processflow from (AHP)Akiki, Cisternas and Tudela, 2006)

3.2 Analytical Hierarchy Process (AHP)

AHP was created by Thomas L. Saaty in the late 1970s and is commonly used to analyze weights of each alternative in many variables involved for solving a problem

(Mendes, 2011). AHP requires the respondent experts to give a judgment about the relative importance of each criterion, and then, give a preference from each of the alternatives using those criteria. Providing a judgement is important in order to get a weight from each of criterion. The result of AHP is a prioritized ranking of the alternatives based on the criteria (Mendes, 2011).

According to Saaty (1986), three basic principles are used to solve a problem using explicitly logical analysis; the first is the hierarchy structure, the second is the principle of setting priority, and the last is consistency logic principle. These are described below. Furthermore Xia and Wu 2007 as cited in Mendes 2011 mentioned that to develop problem solving using AHP, requires a three part sequence of analysis: The hierarchy structure, the matrix of pairwise comparison ratios, and finally, the method for calculating weights.

3.2.1 The Hierarchy Structure

According to Saaty (1986), there are two types of hierarchy. The first is structural hierarchy and the other is functional hierarchy. In structural hierarchy, a complex system is arranged descending into core components according to their structural nature, for instance, the structural hierarchy of the universe is galaxy, solar system, planet and other smaller structural units on each planet.

On the other hand, the functional hierarchy outlines the complex system into its

elements according to their essential relationships. This study is used functional

structure and involved both economic and non-economic variable in order to find the

optimal PPP model for TOD (Figure 3.2)

Figure 3.2 AHP Hierarchy Structure

Finding the optimal PPPs model for TOD From Investor Perspective

BENEFIT COST

ECONOMIC NON-ECONOMIC ECONOMIC NON-ECONOMIC C C

 High Revenue  Low Social Issue  Investment Cost  Social Cost  Low Equity Portion  Rules and Regulation  Maintenance Cost  Bureaucracy Cost Support  Low Financial Risk  Interest Cost  Tax Cost

Source: Author (modified hierarchy structure model from Akiki, Cisternas and Tudela, 2006, and Nijkamp et al, 1993 as cited in Beria, Maltese & Mariotti, 2012)

3.2.2 Determination of Priority

According to Saaty (1986), several stages are used for determining the priority in AHP model, as follow:

1. Relative Measurement

The AHP’s basis calculation model determines priority for a decision-making

process by making a comparison from two things on the same criteria by using a

ratio scale which would later become the basis of a model's input. The ratio scale

limits of human perception in the AHP model is 1 to 9.

In a pairwise comparison, the matrix is used to help the analysis and provide a

framework to test the consistency. The design of this matrix reflects two priorities,

namely in terms of dominating and dominated.

If the respondent already give his/her perception in determining which elements are

most preferred or most importantly for each comparison between the elements that

are in the same level then the result is composed on a matrix of pairwise

comparisons.

For instance, suppose there is a hierarchy subsystem x criteria and sub-criteria

underlying a number n, A1 through An. Comparisons between sub-criteria in a

hierarchical structure can be made in the form of a matrix n x n, as the table below;

Tabel 3.1. Pairwise Comparisons Matrix

X A1 A2 A3 …… An A1 a11 a12 a13 a1n A2 A21 A22 A23 A2n A3 a13 A23 A33 A3n …… …… An an1 an2 an3 ……. ann Source: Thomas L. Saaty, 1986

A11 value is a value comparison element A1 (row) to A1 (column) that states the relationship: a. How far the level of interest of the A1 (row) against the criteria of x compared

to the A1 (column), or b. How much dominance A1 (row) to A1 (column), or c. How many properties are on the A1 criteria x (row) compared with the A1

(column).

Numerical values imposed for the whole comparison is obtained from the comparison scale in the table below:

Tabel 3.2 Comparative Assessment Scale

Scale of Definition Information Importance 1 Equally important Both elements have the same effect 3 Slightly more important Experience and judgment slightly favoring to one element compared to the other element. 5 More important Experience and judgment so favoring one element compared to the other element 7 Very important One element is preferred and practically very real dominance compared with the other element 9 Absolutly more important One element of absolute proven preferable to other component at the highest level of confidence 2,4,6,8 Median This score is given if there is any doubt between two adjacent assessment

Reverse Aij = 1/AIJ If activity i obtain a figure when compared with activity j, then j have the opposite values when compared with i

Source : Thomas L. Saaty, 1986

After the comparison matrix for a group of elements are formed, the next step is to measure the priority weight each of these elements on the basis of expert’s perception who has been included in the matrix. Weight calculation can be done manually (if the matrix is a 2 x 2) or by means of mathematical operations based on matrix and vector operations known as eigenvector by using a computer program.

2. Eigenvector and Eigenvalue

The result from the respondent is compiled into a comparison matrix in order to

determine which criteria are most preferred or most important. The matrix form is

symmetrical/ square matrix in which the number of rows and columns depends on

the number of elements in one level.

After the comparison matrix has been completed, then the next step is to measure

the weight of each criteria on the basis of the perception of an expert who has been

included in the matrix. The final calculation of the priority weight is a decimal

number less than one and the total priority of the criteria at the same group is one.

The most accurate way to calculate the priority weights is with a mathematical

approach based on matrix and vector operation known as eigenvector. Eigenvector

is a vector, which when multiplied by a matrix, the result is itself multiplied by a

scalar number or parameter which is known as eigenvalue.

This vector together with a matrix used in mathematical operations to search for

more accurate weights priority on a comparison matrix. Equations used in this

operation are:

퐴. 푤 = 휆. 푤

where :

A = Pairwise Matrix Comparison

λ = Eigenvalue

w = Eigenvector

Eigenvector is commonly referred as characteristics vector of a square matrix,

while the eigenvalue is a characteristic root of the matrix.

This method is commonly used to measure weight of the priority of each

comparison matrix in AHP model since it is more accurate and calculate all the

interactions between the elements and the matrix. The weakness of this method is

that it is difficult to do it manually, especially if the matrix is composed of three or

more criteria; this requires the assistance of a computer program to solve.

3. Consistency

AHP use a humans perception as their input, then the inconsistencies may be occur

since humans have limitations in expressing perceptions consistently, especially if

they need to compare with many elements.

Measurement consistency in AHP model is conducted in two stages. The first stage

is to measure the consistency of each comparison matrix, and the second stage is to

measure the consistency of the entire hierarchy.

Measurement of the consistency of a matrix itself is based on the maximum

eigenvalue. With using the maximum eigenvalue, the inconsistency comparison

matrix can be minimized.

The formula of consistency index (Consistency Index / CI) are:

( λ maks - n ) CI = ( n – 1 )

Where

CI = Consistency Index

λ max = Maximum eigenvalue

n = size/orde matrix

With λ is the eigenvalue and n is the size of the matrix, the maximum eigenvalue of a matrix will not be less than the value of n so that there can be no negative CI value. The closer the maximum eigenvalue to the magnitude of the matrix, the matrix is more consistent and if equal then the matrix is 100 percent consistent or inconsistent 0 percent.

Tabel 3.3 Random Consistency Index (RI)

n 1 2 3 4 5 6 7 8 9 10 11

RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 1.51

Source: Thomas L. Saaty, 1986

CR = CI/RI

CR = Consistency Ratio

RI = Random Consistency Index

Furthermore, the consistency of the respondents in filling out the questionnaire measured. Consistency measurement is intended to look at the responses given inconsistencies. If CR <0.1 then the value of the pairwise comparison matrix given

criteria consistent. If CR> 0.1 then the value of the pairwise comparison matrix

given criteria inconsistent. So if it is not consistent, then filling the values of the

matrix elements in pairs on the criteria and alternatives should be repeated.

3.2.3 Respondent/Expert Selection

AHP is an expert choice model, that makes the expert selection is very crucial to find the appropriate result. According to Kumar (2011), in qualitative analysis, the information is collected until the data saturation point. In this case the concept of data saturation point is highly subjective. With consideration of the representation of each stakeholder for determining the optimal PPPs model for TOD, Eight experts with diverse experiences were involved in this study.

All of the respondent had more than 10 years of experience in the investment climate of Indonesia. Two respondent work as a government official with PPPs experience in

Jakarta City, one respondent from the Central Bank of Indonesia had exposure to creating investment regulation in Indonesia, one respondent from a commercial banking had high exposure in giving corporate loan in Indonesia, and the four remaining are from the private sector with significant exposure and investment experience in Indonesia. The private sector respondent representation is greater than other groups because this study analyzes the optimal PPP model from an investor point of view.

3.3 Cost Benefit Analysis

Many tools can be used to calculate the benefit cost analysis (BCA). According to

Sobel et all as cited in Latif and Hanafizadeh 2011, NPV is one of the appropriate tools to analyze the project. The basic idea from NPV is calculating the future value into the present value with a discount factor. Schwab and Lusztig (1969), explained that NPV is calculated by taking the present value of all cash benefits using a discount factor rate then subtracting all the cash out flows for the investment. Furthermore Schwab and

Lusztig 1969 explained the NPV into a mathematical concept as follow:

Where: bt all benefit generated in period t ct all cost, including operating and maintenance cost in period t r the discount rate that represent the time value of money.

The net present value of the investment is then given as

NPV=B-C

Both of alternative PPPs model for TOD at Dukuh Atas are calculated using the NPV approach in order to get the highest profitable model from investor point of view. The

50 basic assumption for the NPV calculation, such as total investment cost, discount rate, and others, is based on previous Dukuh Atas project study conducted by JICA in 2012.

The final step from this study is comparing the result from AHP method with BCA method in order to get the optimal PPPs model for TOD at Dukuh Atas.

CHAPTER 4 GENERAL DESCRIPTION OF STUDY AREA

DKI Jakarta lies in position 6°12' south latitude and 106° 48' east longitude.

Geographically Jakarta bordering with the province of Banten in the west, the province of West Java in the east and south, and Java Sea in the north (Figure 4.1). Thirteen rivers and two canals pass through the Jakarta area. The Jakarta region lay on the lowlands with an average height of 7 meters above sea level. However, according to the World Bank (2010), 40 percent of Jakarta area, mainly in the north, is below the sea level due to land subsidence (as cited in Hasudungan, Rasman, Pujiastuti, Utami,

Supendi, 2014, page 3). This makes Jakarta highly vulnerable to flooding. Rivers and reservoirs normalization in Jakarta conducted by Jakarta Provincial Government is currently an effort in order to reduce the risk of flooding.

Based on Law No. 29 of 2007, the Province of Jakarta as the State Capital, has a special status and granted special autonomy so that the whole policy of the government and the budget is determined at the provincial level. In the structure of the administrative area, Jakarta is divided into one administrative district, and five city administrations

The total population of Jakarta is 9.78 million people and an additional 4 million commuters from the area around Jakarta on working days (based on the results of the population census in 2010). On the other hand, the carrying capacity of the city is unable to accommodate the growth of people. This condition causes some urban

52 problems in Jakarta, such as urban sprawl, slum area, flooding, and urban transportation.

Figure 4.1 DKI Jakarta Map

Java Sea

North Jakarta

West Jakarta

Central Jakarta

East Jakarta

Banten Province South Jakarta West Java Prov.

Source: Jakarta Provincial Government (2010)

Public transport in Jakarta has been widely served by the various modes of transport, ranging from small vehicles such as taxi, and minibus; medium vehicle such as

Metromini/ Kopaja; or big vehicle such as Trans Jakarta buses and commuter line trains. However all modes are not connected, not yet integrated within the area, and

53 have development in its path; these condition make urban transportation become a major problem in Jakarta.

Jakarta needs reliable mass transportation system in order to support the entire movement of the city. On the other hand, Jakarta also needs to rearrange the city spaces to make the city more livable. Redevelopment and revitalization of the city space is important in order to optimize the mass transportation system.

4.1 MRT Development in Jakarta

The idea of the development of an MRT system in Jakarta began around 1980. In its development, this idea had been halted due to economic turmoil in Indonesia in 1997.

Even though this idea was reintroduced in 2002 by the Jakarta Provincial Government, the new development just begun on 2006 when the local government signed an agreement with JICA to realize this project. The construction of the MRT system will begin with the Phase 1 and Phase 2. Phase 1 will be located in the corridor from Lebak

Bulus to Bundaran Hotel Indonesia, which has 12 points station development. While

Phase 2 will continue the corridor development to the North of Jakarta and has 9 points station development. Most of the stations are underground, while the rest are elevated stations.

Figure 4.2 Map of South to North MRT Line

DKI JAKARTA

PHASE 2 9 Underground Station PHASE 1 6 Underground Station and 6 Elevated Station

BANTEN PROVINCE

LEGEND MRT LINE WEST JAVA PROVINCE COMMUTER LINE

Source: Jakarta Provincial Government, 2010

In connection with the macro region context in Jakarta, several points of MRT station in Phase 1 could a pool origin station modal transfer personal towards public transport, as follow:

. Lebak Bulus Station

This station is planned to be a MRT station (now is under construction), used to be

this location was a bus station with several of modes. Lebak Bulus Station is the

catchment area of Bintaro (6.7km), Bumi Serpong Damai (13.3km), Ciputat

(3.8km), Pamulang (8.3km), and Parung (15.5km).

. Fatmawati Station.

There is no terminal/station in the existing condition at this point, but there are

several shadow terminals at this location since this area is the catchment area from

east of Jakarta such as Pondok Cabe (6.7km), Cinere (6.2km), Depok (14.5km),

Ragunan (5.9km), Cibubur (15.8km), Bekasi (24km).

. Blok M Station.

There is a central bus terminal near the location of Blok M station, and many modes

of transportation pass through this area. This conditions make the Blok M station

is one of the potential locations to be the pool of origin station modal transfer

towards the public transport.

Figure 4.3 MRT station catchment areas

Blok M Station

Fatmawati Station

Lebak Bulus Station

Source: UDGL Sudirman Thamrin – Jakarta 2013

4.2 Transportation Condition in Jakarta

The population and economic growth in Jakarta as the capital of Indonesia changes the city and make the city dynamic. This condition is also happening in the surrounding

Jakarta area even though with a smaller scale. On the other side, the development of transport system is not growing as fast as the city changes, is not able to accommodate urban development that occurred, and is causing urban problems, such as heavy congestion (Figure 4.4).

Figure 4.4 Traffic Condition at Dukuh Atas Area

Source: Picture taken from Dukuh Atas area, on July 8th 2015 at 08:00 PM

According to Jakarta Provincial Government, 2013, the traffic congestion problem in

Jakarta is caused by several conditions, as follow:

. The difference in the width dimension of the road at the same hierarchical level

road,

. Systems parking and building access,

. The intersection of the rail lanes with the automobile crossroad,

. Side friction due to economic activities,

. Insufficient public transportation, and

. Unintegrated land use planning,

In order to address this problem, the Jakarta Provincial Government has shifted their strategy development from automobile dependence into a new urbanism concept (less dependence on automobiles). Implementation of this strategy will be done in stages,

58 and is expected to be realized by 2025. Several directives related to this strategy can be summed up with the following:

. It focuses on the pedestrian, introducing a new urban lifestyle which reduces the

use of private vehicles, and encourages compact and sustainable development.

. MRT corridor arrangement will lead to smart urban redevelopment - smart growth

with comprehensive policy and control arrangement.

. Reducing the urban sprawl and send back the development into the city center again

with the MRT corridor as the backboned.

. Sustainable and more environmentally friendly development.

4.3 Demography condition in Jakarta

The total population of Jakarta is increasing every year, either due to natural growth or because of migration. Based on the results of the population census in 2010, the total population of Jakarta is 9.78 million. In 2014, the estimation of total population in

Jakarta is around 10.07 million or can be assumed that the average population of Jakarta is increased by 7 people every hour, this number is based on population projections

2010 to 2035 from Indonesia Statistical Bureau (2014).

Jakarta is the most populous province in Indonesia where the density reaches more than

15 thousand people every km² (Table 4.1). Based on data from Indonesia Statistical

Bureau (2014), the Central Jakarta is the most densely populated areas. In one of the districts in Central Jakarta, population density reached nearly 90 thousand people per km².

Table 4.1 Total Population and Population Density based on Census Results in 2010 and Projected Population in 2014 according to the Municipality/Regency

Municipality/Regency Total Population Population Density 2010 2014 2010 2014 Thousand Island 21,520 23,011 2,465 2,645 South Jakarta 2,104,092 2,164,070 14,620 15,273 East Jakarta 2,748,371 2,817,994 14,367 14,963 Central Jakarta 904,630 910,381 18,603 18,914 West Jakarta 2,328,936 2,430,410 17,749 18,812 North Jakarta 1,679,141 1,729,444 12,019 12,573 Total 9,786,690 10,075,310 14,750 15,415 Source: Hasudungan, Rasman, Pujiastuti, Utami, Supendi (2014)

Jakarta’s population in 2014 was dominated by productive age population (15-64 years) with composition 71.8%. However the percentage’s population for unproductive age at the range 0-14 years and who are no longer productive or passed retirement in

2014 are continued to increase. This condition is like two sides of a coin, one side shows improvements in the health of society with both a population that has not yet been productive or children/youth and an increasing elderly population in Jakarta. On the other side, the liabilities to be borne by the productive population are more severe, especially in elderly people where the health care costs are greater.

The Dependency Ratio (DR) in 2014 reached 39.28, an increase in 1.92 points compared to 2010. This figure can be interpreted that the productive population of 100 in Jakarta will need to provide for 39 economically unproductive age population. This

60 shows that Jakarta still got a demographic bonus due to a DR value of less than 40%

(Hasudungan, Rasman, Pujiastuti, Utami, Supendi, 2014).

4.4 Economic condition in Jakarta

Jakarta economic structure is dominated by the financial sector, leasing, and business services; followed by trade, hotels and restaurants; and the manufacturing sector. The structure reinforces the role of Jakarta as the center services, finance, and trade in

Indonesia. Jakarta Gross Regional Domestic Product (GRDP) according to current prices during the period 2007 - 2013 noted an increasing trend continuously. Jakarta in aggregate GRDP at current prices continue to rise, when in 2003 amounted to Rp

566,449.360 billion, then in 2013 increased to Rp 1,255,926.782 billion, of which the contribution of the financial sector, leasing, and business services and trade, hotel and restaurant is always dominant. During the period, the contribution of the financial sector, leasing, and business services reached an average of 27.94% of the GRDP of

Jakarta; while the contribution of the trade, hotels and restaurants reached an average of 20.76%, followed with the manufacturing sector which contributes an average of

15.60%; the services sector amounted to 12.73%; and the construction sector amounted to 11.34%. (Table 4.2)

Similarly, when viewed from GRDP Jakarta in 2007-2013, based on constant 2000 prices, it appears that the contribution of the financial sector, leasing, and business services to the GRDP is greater than in other sectors. The contribution of the financial sector, leasing, and corporate services in 2007 amounted to 29.6% and in 2013 it

61 decreased to 27.21%. While trade, hotels and restaurants accounted for 21.70% in 2007 and continues to increase every year and in 2013 accounted for 22.08%. The condition describes the structure of the economy in Jakarta in the period 2007 - 2013 was dominated by the financial sector, leasing, and business services and trade, hotels and restaurants. GRDP Jakarta according to constant prices also informed that the contribution of the manufacturing sector to the GRDP of Jakarta tended to decline each year. If in 2007 it accounted for 16.90%, then in 2013 dropped to 13.6%. (Table 4.3).

Table 4.2 GRDP at Current Market Prices by Industrial Origin of DKI Jakarta (Million Rupiah), 2007-2013

GRDP Industrial Origin 2007 2008 2009 2010 2011 2012 2013 1. Agriculture 571,425 687,829 762,980 849,560 918,712 968,362 1,044,225 2. Mining/Quarrying 2,636,093 3,178,746 3,155,761 3,701,136 4,934,368 5,182,086 5,466,950 3. Manufacturing Industry 90,446,591 106,418,776 118,163,190 135,614,690 153,620,854 172,334,747 191,337,110 4. Electricity, Gas, and Water Supply 6,021,390 7,525,841 8,294,308 8,879,872 9,583,515 10,234,109 11,023,861 5. Construction 63,448,564 76,502,861 86,646,985 98,424,987 112,056,288 126,274,091 140,171,537 6. Trade, Hotel and Restaurant 115,311,319 140,420,036 156,084,326 178,357,449 204,480,250 228,042,601 265,127,737 7. Transportation and Communication 52,793,003 63,430,684 74,970,893 87,688,423 101,265,389 114,228,509 131,763,264 8. Financial, Real Estate, and Business Services 162,297,780 193,513,702 213,437,911 239,155,971 270,951,564 305,617,626 348,546,440 9. Services 72,923,194 85,366,268 96,180,339 109,253,577 124,065,602 140,810,529 161,444,657

TOTAL of GRDP 566,449,359 677,044,743 757,696,693 861,925,666 981,876,542 1,103,692,660 1,255,925,781 Source: Hasudungan, Rasman, Pujiastuti, Utami, Supendi, 2014

Table 4.3 GRDP at 2000 Constant Prices by Industrial Origin of DKI Jakarta (Million Rupiah), 2007-2013

GRDP Industrial Origin 2007 2008 2009 2010 2011 2012 2013 1. Agriculture 298,415 300,720 301,754 304,274 306,623 309,136 314,206 2. Mining/Quarrying 937,343 937,999 936,029 949,742 991,055 982,250 973,975 3. Manufacturing Industry 56,195,163 58,367,314 58,447,652 60,555,943 63,591,049 65,591,049 65,134,279 4. Electricity, Gas, and Water Supply 2,183,806 2,343,587 2,450,865 2,556,922 2,675,718 2,794,493 2,874,116 5. Construction 33,600,764 36,178,854 38,422,395 41,143,270 44,115,689 47,126,748 49,830,408 6. Trade, Hotel and Restaurant 72,249,706 77,064,386 80,154,121 85,980,580 92,345,063 99,005,738 105,365,077 7. Transportation and Communication 30,697,406 35,258,578 40,769,712 46,766,560 53,233,290 55,509,410 65,960,941 8. Financial, Real Estate, and Business Services 98,558,328 102,707,651 106,788,434 111,312,730 117,190,316 123,460,986 129,848,397 9. Services 38,250,324 40,564,301 43,198,538 46,042,416 49,288,737 53,025,607 56,983,846 TOTAL of GRDP 332,971,255 353,723,390 371,469,500 395,612,437 423,737,540 447,805,417 477,285,245 Source: Hasudungan, Rasman, Pujiastuti, Utami, Supendi, 2014

4.5 Alternative PPPs Concept at Dukuh Atas Area

Dukuh Atas area is located at the center of Jakarta and is one of the Central Business

Districts in Jakarta. The main advantage of the Dukuh Atas area is that it easily accessed by different modes of public transport. However these different modes of public transport are not integrated and not supported with convenient pedestrian facilities. In order to the re-develop area using TOD concept, JICA and Jakarta

Provincial Government in 2012 conducted a study of the re-development of Dukuh

Atas area using PPP mechanisms. According to JICA (2012), two alternative schemes can be applied to develop a TOD at Dukuh Atas, as follows:

1. BOT Model

In the BOT model, it is assumed that the government already owns the land, and in

the case that the land is not owned by the government, it is responsible to acquire

the land before appointing the private sector firm to develop the area using the BOT

mechanism.

In the BOT model, the private sector will take full responsibility for developing the

Dukuh Atas area including development of supporting infrastructure such as

artificial ground for BRT terminal and pedestrian tunnel to connect between the

MRT station and the BRT terminal, and in return the government gives a

concession for certain period to the private sector actors. After the concession is

finished, the private entity transfers all of the project to the public agency.

Figure 4.5 BOT Model

Public Agency

Relocation Land Acquisition Cost Fund by Private Entity

Public Infrastructure Fund artificial ground & pedestrian tunnel

Land Owner Land Owner – Public Agency

Source: JICA, 2012, page 35

In general, the advantage and disadvantage of the BOT Model in the context of TOD at Dukuh Atas, Jakarta can be summarized as follow:

Table 4.4 Advantage and Disadvantage of BOT Model in the Context of TOD at Dukuh Atas

Government Private Sectors 1. At the end of the concession, The The project schedule will be public agency will have the land more timely since in this and the building model, the public agency is Advantage assumed already owned the 2. No need to spend public funding land for development artificial ground and underground connectivity

Disadvantage Since the public agency only owned The private sector only has the 17% from the total area in Zona A, right to operate the building then the public agency needs to during the concession period provide public funding to acquire the rest of Zona A, Zona B , Zona C, and Zona D at Dukuh Atas Source: JICA 2012 and Author

2. Rights Conversions

This type of PPPs project is a common project in developed countries, especially

in Japan. The idea of this project is to make the existing ownership of the land still

having the right to stay at the area. In many projects, the people who live in the area

don’t agree to move to another area because their daily activities are already close

to their home. This concept is accommodating the issue since the existing people

who live in the area still live in the area and get the benefits from the development

of TOD. However if one or more residents don’t agree with the concept, the whole

project can be delayed.

Figure 4.6 Right Conversion Model

No Land New Owner Acquisition Cost Fund by Private Entity Existing Owner Public Infrastructure Partial fund for artificial ground & pedestrian tunnel A B C A B Land Owner - Private Land Owner C

Source: JICA, 2012, page 35

In this scheme the public agency can be joined with the consortium through a state-

owned company or only support a private entity with supporting regulations. A

private entity is also responsible to build the pedestrian tunnel to connect between

67 the stations and build artificial ground to support the Bus Rapid Transit Corridor 4

& 6. On the other hand, a private entity gets compensation through the right to build at a higher flooring area ratio.

This study analyze both of PPPs scenario at Dukuh Atas project using cost benefit analysis and multi-criteria analysis in order to find the optimal PPP’s model for

TOD’s project.

In general, the advantage and disadvantage from Right Conversion Model in the context of TOD at Dukuh Atas, Jakarta can be summarized as follow:

Table 4.5 Advantage and Disadvantage of Right Conversion Model in the Context of TOD at Dukuh Atas

Government Private Sectors 1. FAR incentive No public funding needed to Advantage 2. Possible higher revenue compare to acquire the land BOT model 1. Time consuming for negotiating The land is not owned by the with existing land owner Disadvantage public agency 2. Possible to have cost overrun due to project's delay Source: JICA 2012 and Author

Figure 4.7 Map of Study Area

LEGEND

Zona A

Zona B Zona C

Zona D Commuter Line Station

MRT Station

Future Airport Station Artificial Ground for Bus Terminal

Underground Walkaway Facility BNI TOWER

Source: - Retrieved from google maps, 2015 - JICA 2012 & Author

SCALE Dukuh Atas Area Daniel Azka Alfarobi Jakarta, INDONESIA MASTER RESEARCH PROJECT July , 2015 0 100 m

CHAPTER 5 ANALYSIS

The Dukuh Atas area is located at the center of Jakarta and is considered as one of the most prestigious Commercial Business Districts. According to a study conducted by

JICA in 2012, Dukuh Atas area has the potential to re-develop using the concept of

TOD. Furthermore the Jakarta Master Plan 2030 also mentioned that Dukuh Atas area is an area that can be developed using the concept of TOD. To support this planning, the Jakarta Provincial Government already make an Urban Design Guideline for Dukuh

Atas area as part of MRT Corridor. Implementing the concept of TOD will need a lot of funding. On the other side, the public funding is limited. In order to address this issue, PPPs could be an alternative solution.

In addition with PPPs mechanism, defining the optimal model that can accommodate both public and private interest is the key success of the project. In order to find the optimal model for PPPs, this study uses BCA and AHP. The goal of the analysis is to choose the optimal PPPs model between Built Operate Transfer Model and Right

Conversion Model. Previous studied conducted by JICA (2012), shows that Right

Conversion Model is preferable and this model is commonly used to develop an area in Japan.

5.1 Transit Oriented Development at Dukuh Atas

According to previous study conducted by JICA (2012), the development of Dukuh

Atas area is divided into four zones – or zonas. Each of the zones is connected with the transit system and all of the movements are on the ground level (Figure 5.1). Based on the Urban Design Guideline (UDGL) of the Jakarta Provincial Government (2012), the

Dukuh Atas area has the average building coverage ratio (BCR) around 40% with the floor area ratio (FAR) of 600%.

Figure 5.1 Concept TOD at Dukuh Atas, Jakarta

Zona D

Zona C

Zona B Zona A

Source: Author

The basic design concept for TOD at Dukuh Atas will accommodate the UDGL from the Jakarta Provincial Government. The design of TOD at Dukuh Atas will be compact and pedestrian friendly, and have an adequate open space network (Figure 5.2). Green rooftop and green wall design are some of the strategies that will be used in designing

the Dukuh Atas area in order to reduce the urban heat island in Jakarta due to massive development. Furthermore, in order to optimize the storm water infiltrations, the pedestrian facilities and the road will be made from pervious concrete.

Figure 5.2 Public Space concept at Dukuh Atas

Location: Raffles Station Picture is Taken on 03/03 2015

Source: Author

The pictures in Figure 5.2 are Raffles station at Singapore. Raffles Station is an example of the successful TOD concept in Singapore. At Raffles Station, people easily

shift between modes as pedestrians. Mixed land use, compact development, an adequate open space network and pedestrian-friendly design are some of the important elements of the success of the Raffles Station as a TOD in Singapore. The development in Dukuh Atas area will also put those elements as an important aspect of the project.

5.2 Benefit Cost Analysis

In connection with PPP mechanisms for the construction of TOD, the private partners are responsible for the construction cost of Dukuh Atas area including the connectivity and an artificial ground for the Bus Rapid Transit Terminal (Figure 5.3).

Figure 5.3 Underground Connectivity and Artificial Ground

Zona C Zona D UNDERGROUND CONNECTIVITY

Zona B

Zona A

ARTIFICIAL GROUND

Source: JICA 2012, page 29 and Author

In the BOT model, the land will be owned by the Government. In the Dukuh Atas area, at this time, the Government only has 3,000 m², or around 17% of the total land area, of Zona A and around 7,000 m² at the MRT station. However, the MRT station have a structural limitation on development. To implement the BOT mechanism, the government needs to provide public funding to acquire most of the land in Zona B, 73

Zona C, Zona D and some portion of land in Zona A. After the land is fully owned by the government then the government could cooperate with private sector with the PPP mechanism in the development of TOD at Dukuh Atas. The investors will cover the building construction cost, underground connectivity construction cost and artificial ground construction cost and in return they have the right to operate the building during the concession periods. After the concession period is finished, the Government will own the land and the building.

In contrast, in the right conversion model, the role of the government is only as a facilitator to support the development. In this case, the area is fully owned by the private sector. But the government can support the private partners by giving an incentive such as higher FAR and supporting regulations. However, since the government will give an incentive in FAR, then the private partners still has an obligation to develop underground facility and an artificial ground.

In BCA, the analysis is only calculating the financial projections with economic variables as the main driver from the investor for deciding the most attractive PPP mechanism. In connection with forecasting the cash flow, some assumptions are made based on data from previous studies and surveys about economic and potential market in Indonesia, such as from JICA, Jakarta Provincial Government, Central Bank of

Indonesia and Colliers International Indonesia. These include:

. Discount Factor

The discount factor for calculating the present value is refer on average Cost of

Loanable Funds (CoLF) from commercial banking in Indonesia. The reason of

using this reference is for conservative reason. Usually the calculation of discount

rate is based on the Central Bank Rate, but, in reality, the cost of money from

commercial banks in Indonesia is much higher than the Central Bank Rate. Because

of this, this study is using CoLF rate as a reference for discount rate in order to

make the present value calculation more reliable. The CoLF figures are obtained

from the average of the data for 8 years.

Table 5.1 Average CoLF 2007 – 2014

Year 2007 2008 2009 2010 2011 2012 2013 2014 CoLF 8.87% 8.49% 8.54% 8.01% 8.27% 8.38% 9.46% 9.53% Average 8.69% Source: Central Bank of Indonesia Banking Surveys, 2007 – 2014

. Construction Cost

The constructions cost is estimated around IDR 9.4 Million/m² (equivalent with US

$ 725 / m²). This number is based on JICA’s studies about Dukuh Atas project on

2012 with yearly escalation 8.69%/year (The escalation rate is using the same data

with discount factor). Total size of the building both of the models are as follows:

Table 5.2 Size of the Building

Size (Total Zona Total Size of PPPs Model BCR FAR Max Floor A, B, C, D) the Building BOT 67,696 m² 35% 600% 406,178 m ² 17 Right Conversion 67,696 m² 35% 1000% 676,964 m² 29 Source: Author

Both in the BOT model and the Right Conversion model, the private sector needs

to develop underground facility and artificial ground for the BRT terminal as a

public facility. According data from JICA (2012), the estimated cost for developing

the underground facility and artificial ground are as follow:

Table 5.3 Underground and Artificial Ground Development’s Cost

Artificial Ground Development Cost IDR Rp 385,203,319,473 USD $ 29,631,025

Under Ground Walkaway Development Cost IDR Rp 513,604,425,964 USD $ 39,508,033 Source: JICA, 2012 and Author

. Maintenance Cost

The re-development of Dukuh Atas area is using green development concepts. It is

more costly for capital expenditure but cheaper for O&M costs. The assumption

for maintenance cost is around 3% of the potential revenue. This referral number

is from Jakarta Integrated Urban Transport Hub Development Project from JICA

and Jakarta Provincial Government in 2012.

. Sectional Drawing

In the BOT concept each zone has the same typical use as office and commercial

use, while in the Right Conversion concept, the typical use is as residential and

office, and commercial (Figures 5.4 and 5.5).

Figure 5.4 The Conceptual Design of the Building at Dukuh Atas

Zona B &C Zona A & D

Source: Author

Figure 5.5 Sectional Drawing

Typical use for BOT Model

OFFICE SPACE (3 – 17 Floor)

RETAIL SHOP AND RESTAURANT LOBBY AND BANKING

BASEMENT – PARKING (B1 & B2)

Typical use for Right Conversion Model Residential, Office, and Commercial

OFFICE (11 – 29 Floor)

RESIDENTIAL (3 – 10 Floor)

RETAIL SHOP AND RESTAURANT

LOBBY AND BANKING

BASEMENT – PARKING (B1 & B2)

Source: Author

. Revenue Estimation

At the beginning of the operation, the occupancy rate is projected to be 55% and

increase by 5% per year consecutively up to the year 12, after which the occupancy

rate will level off at 85%:

Table 5.4 Occupancy Rate

Year Percentage Year 1 0% Year 2 0% Construction Period Year 3 55% Year 4 58% Year 5 61% Year 6 64% Year 7 67% Increased by 5% consecutively Year 8 70% Year 9 74% Year 10 77% Year 11 81% Year 12 85% Level off at 85% until the end of concession period

Source: Author (modified from JICA 2012 and Colliers International Research, 2015)

After calculating Benefit Cost Analysis using the assumptions as mentioned above, the result of the analysis can be summarized as follow:

. Built Operate Transfer Model

The maximum BOT mechanism for State property utilization based on Indonesia’s

Ministry of Finance Regulation number 78, 2014, is 30 years without any

possibilities for extension. In this study, the concession period is assumed to be 20

years. The reason is that with a 20-year concession period, the private investor will

still have a room to ask for an extension for another 10 years in the case there is

unpredictable economic situation. The previous studied from JICA in 2012 also

used 20 years as a reference period for calculating the IRR and NPV.

Table 5.5 BOT Model NPV and IRR Analysis

IRR NPV PROJECT 20% $ 359,359,126 EQUITY 30% $ 364,158,750

Source: Author

From the NPV and IRR result, The Dukuh Atas Re-Development concept is

profitable and possible to use PPPs.

. Right Conversion Model

The main different between right conversions and the BOT model is in land

ownerships. In the BOT model, the land is owned by the government. On the other

hand, in the right conversion model, the land is jointly ownered by the existing 79

owner and the investors. However the Government has to give additional incentives to make the project more attractive from the investor point of view. The incentive can be in tax abatement, a higher FAR, or other types of regulatory incentives.

Since the tax incentive is more complicated (involve local and central Government in Indonesia) the higher FAR is chosen for this study as an incentive. The existing maximum FAR is 600%, and the incentive FAR given in this study is up to 1000%.

The incentive is important to make the economic figure more attractive and also comparable with the BOT model.

Table 5.6 Right Conversion Model NPV and IRR Analysis

IRR NPV PROJECT 21% $ 628,642,020 EQUITY 32% $ 636,222,711

Source: Author

The Equity IRR calculation showed that the right conversion model has a better economic figured compared to BOT model from the investor point of view.

However the communication between the investor and the existing land owner is time consuming and can be the major constraint for investor to finish the project on time.

5.3 Analytical Hierarchy Process (AHP)

AHP is a method to solve problem with multi-criteria analysis. In this study, AHP is chosen since it can analyze economic and non-economic variables in connection with finding the most optimal PPP model for TOD development.

The result from the AHP model showed that non-economic variables are more considerable for investor when they want to invest their equity into the project. Non- economic variables have the bigger priorities both in benefit and cost criteria. The respondents were concerned about non-economic variable since it is difficult to measure and could significantly affect the profitability calculation.

Table 5.7 Weight of sub Hierarchy Benefit and Cost

Economic Non-Economic Benefit 0.315 0.685 Cost 0.393 0.607 Source: Author

Overall the result of the weight of criteria can be summarized as follow:

Table 5.8 Overall Weight of Criteria

Goal: Finding the optimal PPPs model for TOD

Criteria Weight Criteria Weight Benefit Cost Economic 0.315 Economic 0.393 High Revenue 0.195 Investment Cost 0.465 Low Equity Portion 0.296 Operational & Maintenance Cost 0.288 Low Financial Risk 0.509 Interest Cost 0.119 Tax Cost 0.128 Non-Economic 0.685 Law social issue 0.505 Non-Economic 0.607 Rules and Regulation Support 0.495 Social Cost 0.645 Bureaucracy Cost 0.355 Source: Author

The result from this process showed that calculating only the economic variables gives the same result with BCA method. Right Conversion model has better results compared to the BOT model (Table 5.9).

Table 5.9 Benefit Sub Hierarchy Economic Alternative Priorities

BOT Right Conversion Economic 0.458 0.542 Source: Author

In contrast, after calculating both economic and non-economic variable there are significant changes in alternative priorities. The BOT model becomes a higher priority

compared to the right conversion model. It is clear that non-economic variable shift the result of the analysis from right conversion model to BOT model (Table 5.10).

Table 5.10 The Optimal PPPs model from AHP Analysis

Right Conversion BOT Optimal PPPs Model for TOD 0.423 0.577 Source: Author

On the other hand the combined Consistency Index from all of the experts for the analysis is 6%. This number is still tolerable. According to Saaty 1986, the consistency index for AHP analysis should be below 10%. The consistency index of 6% means that the experts are consistent in their responses based upon the pairwise comparison.

CHAPTER 6 DISCUSSION

Built Operate Transfer and Right Conversion Model are the alternative mechanism that can be used to implement the concept of TOD through PPPs mechanism at Dukuh Atas,

Jakarta, Indonesia. Based on the BCA calculation, both BOT and Right Conversion models have a positive NPV, means that the projects is feasible from the financial perspective. Furthermore, the BCA shows that the Right Conversion Model has a better economic figure compared to the BOT model, the Equity IRR of Right Conversion model is 32% while the BOT model is only 30%.

It can be concluded that from financial projection perspective, the investor prefer to choose the right conversion model instead of BOT model in the context of PPPs mechanism. On the other hand, the AHP analysis gives the same result with BCA when calculating only the economic variable. The Right Conversion Model has the priorities scale 0.542 while BOT Model only 0.458. This result reinforces the conclusion that from financial projection perspective, the investors will tend to choose the right conversion models

In contrast, after involving non-economic variable, the result from AHP analysis is changed, BOT model has a better priorities scale 0.577 while right conversion model only 0.423. This condition showed that the expert/respondent give more attention on non-economic variable compare to economic variable. Overall, the AHP result shows that BOT model is the optimal PPPs model for TOD from investor point of view. 84

CHAPTER 7 RECOMMENDATION AND CONCLUSION

TOD is a development strategy that could make a city more livable. This strategy needs sustainable financial sources and the public funding is limited. Involving the private sector could be an alternative solution to address the problem however the project needs to be attractive from investor point of view.

Many tools can be used to analyze the most attractive scenario for TOD. This study use

AHP and BCA in order to find the optimal PPPs model for TOD. BCA is a commonly used to forecast the feasibility of the project, however most of BCA calculation only involve economic variable as the main consideration. The result of AHP analysis in this study shows that non-economic variables shift the result of alternative priority. It can be ensured that the investor put a higher priory on non-economic variable compare to economic variable in the context of Indonesia climate investment.

In connection with this result, a further research with involving non-economic variable in the BCA method is necessary in order to give a comprehensive overview to the stakeholder.

APPENDIX 1 Pairwise Comparison Questioner

Name : Background : Contact No. : Email : Explanations

. Summary This research is using Analytical Hierarchy Process for analyzing the most optimal public private partnership model for transit oriented development project at Dukuh Atas – Jakarta. The first model is Built Operate Transfer model and the other model is right conversion model. This research is comparing between benefit and cost from both of model and then determining the most optimal PPPs model for TOD project. . Examples of terms and Scale use. If you think criteria A is 9 times more important than criteria B in attracting private to choose the optimal PPPs model for TOD project at Dukuh Atas, then please circle as follows:

CRITERIA (A) Intensity of Relative Importance CRITERIA (B)

Economic 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Non-Economic

Note: Circle means that from private perspective, economic benefit has extreme importance for choosing the most optimal PPPs model when compare with social or legal benefit.

If you think criteria B is 9 times more important than criteria A in attracting private to choose the optimal PPPs approach for TOD project at Dukuh Atas, then please circle as follows:

CRITERIA (A) Intensity of Relative Importance CRITERIA (B)

Economic 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Non-Economic

Note: Circle means that from private perspective, Social and Legal benefit has extreme importance for choosing the most optimal PPPs model when compare with Economic Benefit.

Source: Saaty, 1986 86

AHP HIERARCHY STRUCTURE

Finding the optimal PPPs model for TOD From Investor Perspective

BENEFIT COST

ECONOMIC NON-ECONOMIC ECONOMIC NON-ECONOMIC C C

 High Revenue  Low Social Issue  Investment Cost  Social Cost  Low Equity Portion  Rules and Regulation  Maintenance Cost  Bureaucracy Cost  Low Financial Risk Support  Interest Cost  Tax Cost

Source: Author (Modified hierarchy structure model from Akiki, Cisternas and Tudela, 2006, and Nijkamp et al, 1993 as cited in Beria, Maltese & Mariotti, 2012)

BENEFIT

CRITERIA Intensity of Relative Importance CRITERIA Economic 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Non-Economic BENEFIT SUB ECONOMIC

CRITERIA Intensity of Relative Importance CRITERIA High Revenue 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Low Equity Portion

CRITERIA Intensity of Relative Importance CRITERIA High Revenue 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Low Financial Risk

CRITERIA Intensity of Relative Importance CRITERIA Low Equity 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Low Financial Risk Portion BENEFIT SUB NON ECONOMIC

CRITERIA Intensity of Relative Importance CRITERIA Low Social Issue 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Rules and Regulation Support COST

CRITERIA Intensity of Relative Importance CRITERIA Economic 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Non-Economic COST SUB ECONOMIC

CRITERIA Intensity of Relative Importance CRITERIA Investment Maintenance Cost 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Cost

CRITERIA Intensity of Relative Importance CRITERIA Investment Cost 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Interest Cost

CRITERIA Intensity of Relative Importance CRITERIA Investment Cost 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Tax Cost

CRITERIA Intensity of Relative Importance CRITERIA Maintenance Cost 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Interest Cost

CRITERIA Intensity of Relative Importance CRITERIA Maintenance Cost 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Tax Cost

CRITERIA Intensity of Relative Importance CRITERIA Interest Cost 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Tax Cost

BOT VS Right Conversion BENEFIT

High Revenue

CRITERIA Intensity of Relative Importance CRITERIA BOT Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Right Conversion Model Low Investment Risk CRITERIA Intensity of Relative Importance CRITERIA BOT Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Right Conversion Model Low Equity Portion

CRITERIA Intensity of Relative Importance CRITERIA BOT Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Right Conversion Model Low Social Issue CRITERIA Intensity of Relative Importance CRITERIA BOT Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Right Conversion Model Rules and Regulation Support CRITERIA Intensity of Relative Importance CRITERIA BOT Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Right Conversion Model COST Investment Cost

CRITERIA Intensity of Relative Importance CRITERIA BOT Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Right Conversion Model Maintenance Cost

CRITERIA Intensity of Relative Importance CRITERIA BOT Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Right Conversion Model

Interest Cost

CRITERIA Intensity of Relative Importance CRITERIA BOT Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Right Conversion Model Tax Cost

CRITERIA Intensity of Relative Importance CRITERIA BOT Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Right Conversion Model Social Cost

CRITERIA Intensity of Relative Importance CRITERIA BOT Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Right Conversion Model Bureaucracy Cost

CRITERIA Intensity of Relative Importance CRITERIA BOT Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Right Conversion Model

APPENDIX 2 QUESTIONNAIRE RECAPITULATION

BENEFIT

Economic Non-Economic High Revenue Low Financial Risk WSB 6 WSB 6 ANP 3 ANP 3 SBW 6 SBW 6 AGG 8 AGG 4 AIS 4 AIS 7 BSN 3 BSN 6 HBS 7 HBS 3 DPW 3 DPW 3

High Low Equity Revenue Low Equity Portion Portion Low Financial Risk WSB 3 WSB 2 ANP 4 ANP 2 SBW 4 SBW 3 AGG 3 AGG 3 AIS 3 AIS 3 BSN 3 BSN 7 HBS 2 HBS 3 DPW 3 DPW 3

Low Social Rules & Regulation Issue Support WSB 3 ANP 6 SBW 3 AGG 4 AIS 7 BSN 4 HBS 4 DPW 4

COST

Economic Non-Economic Investment Tax WSB 2 WSB 5 ANP 4 ANP 3 SBW 3 SBW 3 AGG 6 AGG 3 AIS 3 AIS 2 BSN 4 BSN 5 HBS 2 HBS 3 DPW 3 DPW 3

Investment Maintenance Maintenance Interest Rate WSB 4 WSB 4 ANP 3 ANP 3 SBW 6 SBW 2 AGG 2 AGG 4 AIS 4 AIS 2 BSN 4 BSN 5 HBS 2 HBS 4 DPW 4 DPW 3

Investment Interest Rate Maintenance Tax WSB 5 WSB 6 ANP 2 ANP 2 SBW 6 SBW 2 AGG 8 AGG 3 AIS 7 AIS 4 BSN 7 BSN 3 HBS 4 HBS 2 DPW 3 DPW 3

Interest Tax Social Bureaucracy WSB 3 WSB 6 ANP 3 ANP 2 SBW 4 SBW 3 AGG 5 AGG 2 AIS 4 AIS 5 BSN 3 BSN 6 HBS 6 HBS 2 DPW 4 DPW 4

Right Conversion vs BOT

WSB AIS Right Right Conversion BOT Conversion BOT High Revenue 3 High Revenue 3 Low Equity Portion 5 Low Equity Portion 4 Low Financial Risk 2 Low Financial Risk 3 Low Social Issue 4 Low Social Issue 5 Rules & Regulation Rules & Regulation Support 3 Support 3 Investment Cost 7 Investment Cost 3 Maintenance Cost 3 Maintenance Cost 6 Interest Rate Cost 3 Interest Rate Cost 5 Tax Cost 2 Tax Cost 3 Social Cost 4 Social Cost 2 Bureaucracy Cost 3 Bureaucracy Cost 3

ANP BSN Right Right Conversion BOT Conversion BOT High Revenue 5 High Revenue 4 Low Equity Portion 7 Low Equity Portion 3 Low Financial Risk 4 Low Financial Risk 3 Low Social Issue 8 Low Social Issue 7 Rules & Regulation Rules & Regulation Support 7 Support 4 Investment Cost 5 Investment Cost 3 Maintenance Cost 6 Maintenance Cost 5 Interest Rate Cost 5 Interest Rate Cost 7 Tax Cost 4 Tax Cost 5 Social Cost 4 Social Cost 4 Bureaucracy Cost 4 Bureaucracy Cost 5

SBW HBS Right Right Conversion BOT Conversion BOT High Revenue 5 High Revenue 4 Low Equity Portion 6 Low Equity Portion 3 Low Financial Risk 5 Low Financial Risk 6 Low Social Issue 4 Low Social Issue 5 Rules & Regulation Rules & Regulation Support 4 Support 4 Investment Cost 3 Investment Cost 4 Maintenance Cost 2 Maintenance Cost 5 Interest Rate Cost 3 Interest Rate Cost 5 Tax Cost 3 Tax Cost 6 Social Cost 4 Social Cost 3 Bureaucracy Cost 8 Bureaucracy Cost 4 93

AGG DPW Right Right Conversion BOT Conversion BOT High Revenue 3 High Revenue 3 Low Equity Portion 4 Low Equity Portion 4 Low Financial Risk 3 Low Financial Risk 4 Low Social Issue 4 Low Social Issue 3 Rules & Regulation Rules & Regulation Support 3 Support 4 Investment Cost 6 Investment Cost 3 Maintenance Cost 3 Maintenance Cost 3 Interest Rate Cost 2 Interest Rate Cost 3 Tax Cost 4 Tax Cost 3 Social Cost 3 Social Cost 3 Bureaucracy Cost 2 Bureaucracy Cost 3

Source: Barata, Wisnu; Parulian, Andronico; Subowo; Gunawan, Agus; Shihab, Ady Iktimal; Nasution, Benny Swastika; Subangun, Heriman Budi; Wijaya, Dicky Pramayudha (2015)

WSB :Wisnu Barata ANP :Andronico Parulian SBW :Subowo AGG :Agus Gunawan AIS :Ady Iktimal Shihab BSN :Benny Swastika Nasution HBS :Heriman Budi Subangun DPW :Dikcy Pramayudha Wijaya

Profile of Respondent

1. Wisnu Barata (WSB) WSB was born in Jakarta, March 28th 1976, He got a bachelor degree and master degree in Civil Engineering from University of Indonesia. He started his career at PT. Pembangunan Perumahan (Indonesia state owned company in housing development) and then join with Jakarta Provincial Government. His professional experience more than 10 years both in private and public sector makes him understand about the investment regulation in Jakarta, Indonesia. Furthermore, his research in Public Private Partnerships in connection with 6 Toll Road development in Jakarta makes him familiar with PPPs scheme in Indonesia. 2. Andronico Parullian (ANP) ANP was born in Jakarta, July 9th 1977, he got a bachelor and master degree in economics from University of Indonesia. He started his career in Asian Development Bank before join as government official. His expertise is in econometric and financial modelling. Currently, he is join with Jakarta Provincial Government, and doing some research in connection with transportation issue in Jakarta including Transit Oriented Development. 3. Subowo (SBW) SBW was born in Bojonegoro, July 19th 1966, He got a master degree in Business Administration from IPMI, Jakarta, Indonesia. SBW has an experience in financial management more than 20 years both in local and overseas company (most of them in Japanese company). He has a knowledge in Japanese investment regulation and Indonesia investment regulation. Beside his professional career, he also run his owned property business in Jakarta, Indonesia. 4. Agus Gunawam (AGG) AGG was born in Nganjuk, Dec 25th 1959, He got a bachelor degree in Geophysics from ITB, Indonesia and master degree in management from Prasetya Mulya Business School Jakarta. He has more than 20 years’ experience in investment climate in Indonesia. His experience as Corporate Secretary in PT. Elnusa, Tbk Jakarta makes him understand about political issue, Government Issue, and other issue in connection with investment in Indonesia. 5. Ady Iktimal Shihab (AIS) AIS was born in Makasar May 30th 1975, he got a master degree in industrial management from University of Indonesia. He started his career as an entrepreneur in automotive industry. After successful in automotive industry, he expanses his business in property and energy. As an entrepreneur, he is familiar with financial modelling and investment opportunity in Indonesia. He knows well Dukuh Atas area, since his family has a property located at Dukuh Atas area.

6. Benny Swastika Nasution (BSN) BSN was born in Pematang Siantar, December 28th, 1982, he got his bachelor and master degree in Law from University of Indonesia. He has an experience in business and legal due diligence more than 10 years. His experience as a legal supervisor in MNC group make him understand about the acquisition process in Indonesia. 7. Heriman Budi Subangun (HBS) HBS was born in Bandung, Oct 1980, he got Master of Science in finance and management from Cranfield University, United Kingdom. He has worked at Central Bank of Indonesia (BI) more than 10 years and has qualification in financial risk management. During his working time in BI, he has made a lot of research about economic and infrastructure development in Indonesia. 8. Dicky Pramayudha Wijaya (DPW) DPW was born on April 1st 1980, He got a master degree of business administration from Gadjah Mada University, Indonesia and Asian Institute of Management, Philippines. DPW has an experience in Banking Industry more than 10 years with qualification in commercial and corporate banking. Some of the DPW’s expertise are in property financing and infrastructure financing.

APPENDIX 3 BCA - BASIC ASSUMPTIONS

Exchange Rate US $ 1 13,000 IDR Land Acquisition Cost

Building Coverage Ratio (BCR) 35% IDR 66,904,000 /m2

Floor Area Ratio (FAR) USD 5,146 /m2 Right Conversion Model 1000% BOT Model 600% Discount Rate 8.69%

Size of The Zonation Area Occupancy Rate Baseline 55% Block A 17,621 m2 Rise 5%/year consecutively and level off at 85% Block B 9,824 m2 Block C 12,646 m2 Maintenance Cost 3% From Revenue Block D 27,605 m2 Inflation Cost 5% Artificial Ground Dev. Cost

IDR 385,203,319,473 Office Rent $25 /Month USD 29,631,025 Commercial Rent $35 /Month

Under Ground Walkaway Dev. Cost

IDR 513,604,425,964 Interest Rate USD 39,508,033 Bank 12% Equity 15% Construction Cost WACC 13% IDR 9,424,641 /m2 Concessions 20 Years USD 725 /m2

In US $ (Exchange Rate US $ 1 ~ IDR 13,000) CASH FLOW - BOT Cash In Flow Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Equity 114,063,374 - Bank Loan 70,162,694 195,985,178 Revenue Block A - - 18,840,794 19,782,833 20,771,975 21,810,574 22,901,102 Block B - - 10,504,317 11,029,533 11,581,010 12,160,060 12,768,063 Block C - - 13,521,155 14,197,213 14,907,074 15,652,427 16,435,049 Block D - - 29,514,742 30,990,479 32,540,003 34,167,003 35,875,353 Sub Total - - 72,381,008 76,000,058 79,800,061 83,790,064 87,979,568

Total Cash in Flow 184,226,068 195,985,178 72,381,008 76,000,058 79,800,061 83,790,064 87,979,568

Cash Out Flow Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Building Construction Cost Block A 38,325,071.09 38,325,071.09 Block B 21,367,396.30 21,367,396.30 Block C 27,504,109.02 27,504,109.02 Block D 60,037,523.50 60,037,523.50 Sub Total 147,234,099.91 147,234,099.91

Under Ground Walkaway Development Cost 19,754,016 19,754,016

Artificial Development Cost 14,815,512 14,815,512

Maintenance Cost

Block A - - 565,224 593,485 623,159 654,317 687,033 Block B - - 315,130 330,886 347,430 364,802 383,042 Block C - - 405,635 425,916 447,212 469,573 493,051 Block D - - 885,442 929,714 976,200 1,025,010 1,076,261 Sub Total - - 2,171,430 2,280,002 2,394,002 2,513,702 2,639,387

Interest During Construction Cost (IDC) 2,422,439 14,181,550

Interest Cost 30,801,936 28,125,169 25,108,921 21,710,138 16,548,024 Principal Payment 21,105,984 23,782,751 26,798,999 30,197,755 31,034,236

Total Cash Out Flow 184,226,068 195,985,178 54,079,350 54,187,922 54,301,922 54,421,595 50,221,647

Free Cash Flow - - 18,301,658 40,113,794 65,611,934 94,980,404 132,738,324

In US $ (Exchange Rate US $ 1 ~ IDR 13,000) CASH FLOW Cash In Flow Year 8 Year 9 Year 10 Year 11 Year 12 Year 13 Year 14 Equity Bank Loan Revenue Block A 24,046,157 25,248,465 26,510,889 27,836,433 29,228,255 29,228,255 29,228,255 Block B 13,406,466 14,076,790 14,780,629 15,519,661 16,295,644 16,295,644 16,295,644 Block C 17,256,801 18,119,641 19,025,623 19,976,905 20,975,750 20,975,750 20,975,750 Block D 37,669,121 39,552,577 41,530,206 43,606,716 45,787,052 45,787,052 45,787,052 Sub Total 92,378,546 96,997,473 101,847,347 106,939,714 112,286,700 112,286,700 112,286,700

Total Cash in Flow 92,378,546 96,997,473 101,847,347 106,939,714 112,286,700 112,286,700 112,286,700

Cash Out Flow Year 8 Year 9 Year 10 Year 11 Year 12 Year 13 Year 14 Building Construction Cost Block A Block B Block C Block D Sub Total

Under Ground Walkaway Development Cost

Artificial Development Cost

Maintenance Cost Block A 721,385 757,454 795,327 835,093 876,848 876,848 876,848 Block B 402,194 422,304 443,419 465,590 488,869 488,869 488,869 Block C 517,704 543,589 570,769 599,307 629,272 629,272 629,272 Block D 1,130,074 1,186,577 1,245,906 1,308,201 1,373,612 1,373,612 1,373,612 Sub Total 2,771,356 2,909,924 3,055,420 3,208,191 3,368,601 3,368,601 3,368,601

Interest During Construction Cost (IDC)

Interest Cost 13,944,391 9,129,667 3,704,316 - Principal Payment 37,963,502 42,778,226 48,203,577 -

Total Cash Out Flow 54,679,249 54,817,817 54,963,313 3,208,191 3,368,601 3,368,601 3,368,601

Free Cash Flow 170,437,621 212,617,277 259,501,311 363,232,834 472,150,933 581,069,032 689,987,131

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In US $ (Exchange Rate US $ 1 ~ IDR 13,000) CASH FLOW Cash In Flow Year 15 Year 16 Year 17 Year 18 Year 19 Year 20 Equity Bank Loan Revenue Block A 29,228,255 29,228,255 29,228,255 29,228,255 29,228,255 29,228,255 Block B 16,295,644 16,295,644 16,295,644 16,295,644 16,295,644 16,295,644 Block C 20,975,750 20,975,750 20,975,750 20,975,750 20,975,750 20,975,750 Block D 45,787,052 45,787,052 45,787,052 45,787,052 45,787,052 45,787,052 Sub Total 112,286,700 112,286,700 112,286,700 112,286,700 112,286,700 112,286,700

Total Cash in Flow 112,286,700 112,286,700 112,286,700 112,286,700 112,286,700 112,286,700

Cash Out Flow Year 15 Year 16 Year 17 Year 18 Year 19 Year 20 Building Construction Cost Block A Block B Block C Block D Sub Total

Under Ground Walkaway Development Cost

Artificial Development Cost

Maintenance Cost Block A 876,848 876,848 876,848 876,848 876,848 876,848 Block B 488,869 488,869 488,869 488,869 488,869 488,869 Block C 629,272 629,272 629,272 629,272 629,272 629,272

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Block D 1,373,612 1,373,612 1,373,612 1,373,612 1,373,612 1,373,612 Sub Total 3,368,601 3,368,601 3,368,601 3,368,601 3,368,601 3,368,601

Interest During Construction Cost (IDC)

Interest Cost Principal Payment

Total Cash Out Flow 3,368,601 3,368,601 3,368,601 3,368,601 3,368,601 3,368,601

Free Cash Flow 798,905,230 907,823,329 1,016,741,428 1,125,659,527 1,234,577,626 1,343,495,725

BOT Model IRR NPV Project 20% 359,359,126 Equity 30% 364,158,750

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In US $ (Exchange Rate US $ 1 ~ IDR 13,000) CASH FLOW – RIGHT CONVERSION Cash In Flow Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Equity 176,038,656 - Bank Loan 110,640,072 300,116,793 Revenue Block A - - 30,587,214 32,116,575 33,722,404 35,408,524 37,178,950 Block B - - 17,053,305 17,905,970 18,801,269 19,741,332 20,728,399 Block C - - 21,951,011 23,048,562 24,200,990 25,411,040 26,681,592 Block D - - 47,915,908 50,311,704 52,827,289 55,468,653 58,242,086 Sub Total - - 117,507,439 123,382,811 129,551,951 136,029,549 142,831,027

Total Cash in Flow 286,678,728 300,116,793 117,507,439 123,382,811 129,551,951 136,029,549 142,831,027

Cash Out Flow Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Building Construction Cost Block A 63,875,118.49 63,875,118.49 Block B 35,612,327.17 35,612,327.17 Block C 45,840,181.70 45,840,181.70 Block D 100,062,539.16 100,062,539.16 Sub Total 245,390,166.52 245,390,166.52

Under Ground Walkaway Development Cost 19,754,016 19,754,016

Artificial Development Cost 14,815,512 14,815,512

Maintenance Cost Block A - - 917,616 963,497 1,011,672 1,062,256 1,115,369 Block B - - 511,599 537,179 564,038 592,240 621,852 Block C - - 658,530 691,457 726,030 762,331 800,448

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Block D - - 1,437,477 1,509,351 1,584,819 1,664,060 1,747,263 Sub Total - - 3,525,223 3,701,484 3,886,559 4,080,886 4,284,931

Interest During Construction Cost (IDC) 6,719,033 20,157,098.05

Interest Cost 47,537,884 43,406,721 38,751,623 33,506,143 25,539,242 Principal Payment 32,573,720 36,704,883 41,359,981 46,605,434 47,896,395

Total Cash Out Flow 286,678,728 300,116,793 83,636,827 83,813,088 83,998,163 84,192,463 77,720,568

Free Cash Flow 0 0 33,870,612 73,440,334 118,994,123 170,831,209 235,941,668

In US $ (Exchange Rate US $ 1 ~ IDR 13,000) CASH FLOW Cash In Flow Year 8 Year 9 Year 10 Year 11 Year 12 Year 13 Year 14 Equity Bank Loan Revenue Block A 39,037,898 40,989,792 43,039,282 45,191,246 47,450,808 47,450,808 47,450,808 Block B 21,764,819 22,853,060 23,995,713 25,195,498 26,455,273 26,455,273 26,455,273 Block C 28,015,671 29,416,455 30,887,277 32,431,641 34,053,223 34,053,223 34,053,223 Block D 61,154,190 64,211,900 67,422,495 70,793,620 74,333,301 74,333,301 74,333,301 Sub Total 149,972,578 157,471,207 165,344,767 173,612,005 182,292,606 182,292,606 182,292,606

Total Cash in Flow 149,972,578 157,471,207 165,344,767 173,612,005 182,292,606 182,292,606 182,292,606

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Cash Out Flow Year 8 Year 9 Year 10 Year 11 Year 12 Year 13 Year 14 Building Construction Cost Block A Block B Block C Block D Sub Total

Under Ground Walkaway Development Cost

Artificial Development Cost

Maintenance Cost Block A 1,171,137 1,229,694 1,291,178 1,355,737 1,423,524 1,423,524 1,423,524 Block B 652,945 685,592 719,871 755,865 793,658 793,658 793,658 Block C 840,470 882,494 926,618 972,949 1,021,597 1,021,597 1,021,597 Block D 1,834,626 1,926,357 2,022,675 2,123,809 2,229,999 2,229,999 2,229,999 Sub Total 4,499,177 4,724,136 4,960,343 5,208,360 5,468,778 5,468,778 5,468,778

Interest During Construction Cost (IDC)

Interest Cost 21,520,948 14,090,189 5,717,023 - Principal Payment 58,590,629 66,021,388 74,394,554 -

Total Cash Out Flow 84,610,754 84,835,713 85,071,920 5,208,360 5,468,778 5,468,778 5,468,778

Free Cash Flow 301,303,491 373,938,985 454,211,832 622,615,477 799,439,305 976,263,132 1,153,086,960

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In US $ (Exchange Rate US $ 1 ~ IDR 13,000) CASH FLOW Cash In Flow Year 15 Year 16 Year 17 Year 18 Year 19 Year 20 Equity Bank Loan Revenue Block A 47,450,808 47,450,808 47,450,808 47,450,808 47,450,808 47,450,808 Block B 26,455,273 26,455,273 26,455,273 26,455,273 26,455,273 26,455,273 Block C 34,053,223 34,053,223 34,053,223 34,053,223 34,053,223 34,053,223 Block D 74,333,301 74,333,301 74,333,301 74,333,301 74,333,301 74,333,301 Sub Total 182,292,606 182,292,606 182,292,606 182,292,606 182,292,606 182,292,606

Total Cash in Flow 182,292,606 182,292,606 182,292,606 182,292,606 182,292,606 182,292,606

Cash Out Flow Year 15 Year 16 Year 17 Year 18 Year 19 Year 20 Building Construction Cost Block A Block B Block C Block D Sub Total

Under Ground Walkaway Development Cost

Artificial Development Cost

Maintenance Cost Block A 1,423,524 1,423,524 1,423,524 1,423,524 1,423,524 1,423,524

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Block B 793,658 793,658 793,658 793,658 793,658 793,658 Block C 1,021,597 1,021,597 1,021,597 1,021,597 1,021,597 1,021,597 Block D 2,229,999 2,229,999 2,229,999 2,229,999 2,229,999 2,229,999 Sub Total 5,468,778 5,468,778 5,468,778 5,468,778 5,468,778 5,468,778

Interest During Construction Cost (IDC)

Interest Cost Principal Payment

Total Cash Out Flow 5,468,778 5,468,778 5,468,778 5,468,778 5,468,778 5,468,778

Free Cash Flow 1,329,910,787 1,506,734,615 1,683,558,442 1,860,382,270 2,037,206,097 2,214,029,925

Right Conversion Model IRR NPV Project 21% 628,642,020 Equity 32% 636,222,711

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APPENDIX 4 AHP RESULT The Optimal PPPs model for TOD (From Economic and Non Economic Variable)

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Inconsistency Index

109

Grafic Model

110

Result Only from Economic Variable Analysis

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