The Interpretative Structural Modeling for Stakeholder Involvement to Reduce Slum Settlements

Smart City Volume 4 Issue 1 Tomorrow's Cities Today: Advancing Sustainability in Smart Urbanism. Article 2. January 2024. The Interpretative Structural Modeling for Stakeholder Involvement to Reduce Slum Settlements Bich Hanes Bich Universitas Indonesia, Faculty of Engineering, Civil Engineering Department, bichhanesbich@gmail.com. Ayomi Dita Rarasati Universitas Indonesia, Faculty of Engineering, Civil Engineering Department, ayomi@ui.ac.id. Follow this and additional works at: https://scholarhub.ui.ac.id/smartcity Part of the Architectural Engineering Commons, Civil Engineering Commons, Construction Engineering and Management Commons, and the Urban, Community and Regional Planning Commons. Recommended Citation Bich, Bich Hanes and Rarasati, Ayomi Dita (2024) "The Interpretative Structural Modeling for Stakeholder Involvement to Reduce Slum Settlements," Smart City: Vol. 4: Iss. 1, Article 2. DOI: 10.56940/sc.v4.i1.2 Available at: https://scholarhub.ui.ac.id/smartcity/vol4/iss1/2. This Article is brought to you for free and open access by the Universitas Indonesia at UI Scholars Hub. It has been accepted for inclusion in Smart City by an authorized editor of UI Scholars Hub.. Bich and Rarasati: The ISM for Stakeholder Involvement to Reduce Slum Settlements. Smart City. THE INTERPRETATIVE STRUCTURAL MODELING FOR STAKEHOLDER INVOLVEMENT TO REDUCE SLUM SETTLEMENTS 1Bich 1. Hanes Bich and 1Ayomi Dita Rarasati*. Civil Engineering Department, Faculty of Engineering, Universitas Indonesia *. Correspondence: ayomi@ui.ac.id. ABSTRACT The array of problems originating from slum settlements not only results in unwholesome environment, unlawful land utilization, and various internal challenges within the vicinity but also impacts the surrounding regions and the overall urban infrastructure network. In pursuit of Indonesia's 2045 Vision, which emphasizes on "equitable and integrated infrastructure development”, the zero slums constitutes a pivotal component of the Ministry of Public Works and Public Housing's overarching vision. Nonetheless, a disparity has been identified in addressing slum settlements in West Kalimantan, hindering the achievement of this objective. This research aims to identify the stakeholders and the priority factors in determining the priority setting for slum area management in West Kalimantan. The method used in this research is semi-structured interview to identify and map stakeholders involved in priority setting, and geometric mean to identify influential factors which will then be analyzed using Interpretative Structural Modeling. The results found are that there are 24 stakeholders who are considered to be involved. Quadrant D (Manage Closely) stakeholders and primary stakeholders are members of the supervisory team, namely the Head of the Housing and Settlement Area Office, and the Head of the Regional Development Planning Agency. However, the highest level of influence is held by the steering committee whilethe highest level of interest is held by Housing and Settlement Area Office. In addition, ten categories with 22 factors are identified with nine ranking levels found to influence the decision to prioritize slum upgrading. The most influential factor is the difference in knowledge and experience between the new and the former team members. Keywords: Housing infrastructure; Interpretative structural modeling; Slum area; Stakeholder involvement. Published by UI Scholars Hub, 2024. 1. Smart City, Vol. 4 [2024], Iss. 1, Art. 2. Smart City. INTRODUCTION Indonesia's 1945 Constitution (Government of Indonesia, 2002) guarantees the right of every person to physical and spiritual prosperity, good and healthy environment, and access to health services. However, the rapid growth of urban slums and limited basic services can result from cities' unpreparedness for urbanization (Madiasworo, 2017). In response, Law No.1 Year 2011 on Housing and Settlement Areas (Government of Indonesia, 2011) related to the Sustainable Development Goals discusses the strategic issue of slum prevention and quality improvement in a sustainable manner. This issue is further integrated in the Guidelines for Urban Slum Prevention and Quality Improvement Plan (Farida, 2018) by Ministry of Public Works and Housing (MPWH). As predicted by the National Bureau of Statistic (Badan Pusat Statistik, 2023), Kalimantan is expected to become the fourth most populous island in Indonesia by 2025. West Kalimantan, in particular, is a vast region with limited funds for handling slum settlements. It faces the risk of national urbanization growth influencing its own growing slum settlements. Decisive actions are needed to ensure that this risk can be mitigated and slum settlements can be addressed. The expansion of slum areas over time (Jannah, 2019) indicates social and economic injustice, which in turn exacerbates the gap between the rich and the poor (Satterthwaite, 2009). Slum settlements depict living conditions that are lacking in access to essential daily life facilities with low security levels (African Population and Health Research Center, 2002). The potential for slum settlements to become sites of conflicts and crimes is also indicated by an increase of unemployment which eventually leads to criminal activities (McIlwaine and Moser, 2001). Furthermore, slum settlements have the potential to cause natural disasters and are more prone to significant physical damages (Adamtey et al., 2021; Iskandar, 1998; Nsorfon, 2015; Rashid et al., 2013), as well as being vulnerable to extreme climate changes due to a lack of access to basic services. These vulnerable settlements contribute to an increased risk of waterrelated diseases in the surrounding community (Gqomfa et al., 2022; Gwija, 2021). Having identified these issues, it is crucial to address them promptly to realize Indonesia's 2045 vision of "even and integrated infrastructure development”, where zero slums is part of the MPWH’s vision to achieve this goal (Government of Indonesia, 2017). In 2021, the Housing and Settlement Area Office (HSAO) of West Kalimantan successfully addressed one city and one district (Bich et al., 2021). However, in 2023, 98.002% of the area in West Kalimantan. https://scholarhub.ui.ac.id/smartcity/vol4/iss1/2 DOI: 10.56940/sc.v4.i1.2. 2. 2. Bich and Rarasati: The ISM for Stakeholder Involvement to Reduce Slum Settlements. Smart City. remained unaddressed. Therefore, it is necessary to analyze the management of slum areas to ensure that the above risks can be reduced or overcome. The purpose of this analysis is to improve the quality of the prioritization with regards to slum upgrading in West Kalimantan. To achieve this, the research will identify the stakeholders involved and, according to these stakeholders, the most important factors in the decision making on prioritizing slum upgrading in West Kalimantan.. METHODS This paper aims to identify and to map stakeholders’ involvement in reducing slum settlement area in West Kalimantan. Therefore, nine questions were developed in semistructured interviews for data collection. Out of the eight targeted interviewees, only seven were eligible to be interviewed. The interviews were conducted with four main objectives which are: identifying and formulating project challenges, identifying stakeholders, collecting stakeholder data resulting in astakeholder list, and mapping stakeholders. The stakeholder mapping section itself included questions related to stakeholder classification, as well as the level of influence and interest of eachidentified stakeholder. In this research, the Interpretative Structural Modeling (ISM) was applied for analysis and assisted by geometric mean (GM). At the identification stage, the weighting of each candidate variable was carried out using a likert scale, which was further analyzed with GM. The likert scale ranged from number one to indicate strongly disagreeing to the number five to indicate strongly agreeing. After the respondents gave their assessments, the middle value was sought with GM. G M is a calculation method with the square root of n from the product of all existing values. Variables that have a value more than 3.5 will be used in the ISM analysis. The factors were analyzed through related literature and journals before being compiled in the ISM questionnaire. By analyzing the data using structural self-interaction (SSIM), reachability matrix (RM), level partition (LP) and canonical matrix (CM), followed by matrice d’impacts croises multiplication applique an classment (MICMAC), the sequence of factors that influenced the prioritization of slum handling could be seen.. RESULTS AND DISCUSSION To obtain an overview of the research on stakeholder management and stakeholder involvement in slum upgrading, 31 previous studies on similar topics were analyzed. There are. Published by UI Scholars Hub, 2024. 3. Smart City, Vol. 4 [2024], Iss. 1, Art. 2. Smart City. 11 (Annas et al., 2018; Halim, 2020; Leonita et al., 2018; Nugraha et al., 2019; Oktarini et al., 2023; Purwanto et al., 2017; Radliya et al., 2020; Tamtomo et al., 2019; Wijaya, 2016) topics related to stakeholder analysis or slums in Indonesia, none of which discusses specifically about plans to involve stakeholder in prioritizing slum upgrading, especially in West Kalimantan. Twenty other of literatures (Alam et al., 2020; Anthony and Preko, 2021; Badmos et al., 2019; Celentano et al., 2020; Deza et al., 2023; Flinck, 2017; Iwuagwu and Nwankwo, 2018; Jasim, 2021; Kapiriri, 2017; Maluka, 2011; Meredith and MacDonald, 2017; Meredith et al., 2021; Purnama et al., 2022; Rao et al., 2021; Semiyaga et al., 2015; Sibbald, 2008; Sikder et al., 2015; Tjia and Coetzee, 2022; Valencia et al., 2019; Vostanis et al., 2021) address slums or informal settlements in other countries and stakeholder engagement as an ISM in different areas of the world. However, no analysis of stakeholder engagement plans for slum upgrading decision-making was found. It can be concluded that there is a gap in the previous literatures regarding research on the relationship between slum upgrading and the management of stakeholder involvement or interest in Indonesia. The identified stakeholders and their mapping results are presented in Table 1. Table 1. Stakeholder Influence and Interest Level Level of Level of Influence Interest Director 3.86 3.29 Chairman of the Supervisory Team 3.57 3.29 Vice Chairman of the Supervisory Team (RDPA) 3.57 3.71 Member of Supervisory Team (HSAO) 3.57 3.86 Member of Supervisory Team (PWH Office) 3.57 3.29 Member of Supervisory Team (Environment and 3.57 3.43 Forestry Office) Member of Supervisory Team (Health Office) 3.57 3.29 Member of Supervisory Team (Village and 3.57 3.29 Community Empowerment Office) Implementation Team Leader / Working Group 2.86 3.71 Leader Secretary of the Implementation Team 2.57 3.71 Implementation Team Member (Village and 2.57 3.29 Community Empowerment Office) Member of Implementation Team (RDPA) 2.57 3.71 Member of the Implementation Team (HSAO) of 2.57 3.71 the Housing Section Member of the Implementation Team (HSAO) of 2.57 3.71 the Settlement Area section Head of Housing and Settlement Technical 2.86 3.71 Division Member of Technical Division of Housing and 2.57 3.71 Settlement Areas (PWH Office) Member of Technical Division of Housing and 2.57 3.71 Settlement Area (RDPA) Stakeholder. https://scholarhub.ui.ac.id/smartcity/vol4/iss1/2 DOI: 10.56940/sc.v4.i1.2. Quadrant. Classification. C (Keep Satisfied) C (Keep Satisfied) D (Manage Closely) D (Manage Closely) C (Keep Satisfied). Secondary Secondary Primary Primary Secondary. C (Keep Satisfied). Secondary. C (Keep Satisfied). Secondary. C (Keep Satisfied). Secondary. B (Keep Informed). Primary. B (Keep Informed). Primary. A (Monitor). Secondary. B (Keep Informed). Primary. B (Keep Informed). Primary. B (Keep Informed). Primary. B (Keep Informed). Primary. B (Keep Informed). Primary. B (Keep Informed). Primary. 4. 4. Bich and Rarasati: The ISM for Stakeholder Involvement to Reduce Slum Settlements. Smart City Level of Level of Influence Interest. Stakeholder Member of the Technical Division of Housing and Settlement Areas (HSAO) Member of the Technical Division of Housing and Settlement Areas (HSAO) Member of the Technical Division of Housing and Settlement Areas (HSAO) Head of Water and Sanitation Member of Water and Sanitation Division Head of Waste and Solid Waste Technical Division Member of Waste and Solid Waste Technical Division. Quadrant. Classification. 2.57. 3.71. B (Keep Informed). Primary. 2.57. 3.71. B (Keep Informed). Primary. 2.57. 3.71. B (Keep Informed). Primary. 2.86 2.57. 3.29 3.29. A (Monitor) A (Monitor). Secondary Secondary. 2.86. 3.43. A (Monitor). Secondary. 2.57. 3.43. A (Monitor). Secondary. There are 24 stakeholders who are considered to have influence and interest in slum upgrading decision-making. These stakeholders are classified into two types: primary and secondary. Based on the results of the analysis, four types of quadrants were obtained for the identified stakeholders. The results of the GM and ISM questionnaires from seven respondents involved in slum upgrading in West Kalimantan Province are presented in Table 2. Table 2. Analysis of the Geometric Mean Category. Stakeholder Satisfaction and Engagement. Employee Rotations in the Stakeholder Environment. Objectives and Targets for Prioritization. Transparency and Fairness. Communication System. Factor Meeting the technical and political needs of each stakeholder in decision making The realization of a commitment from the initiating party (the stakeholder responsible for proposing slum upgrading) to involve every stakeholder in every slum upgrading activity. The realization of active participation of every stakeholder in slum upgrading. There are changes in the number of working group team members. There are differences in the knowledge and experience of new team members and previous team members. There are clear benchmarks for slum upgrading success (e.g. Zero Slum Vision by 2045 (Government of Indonesia, 2017). Achieved efficiency in accordance with the availability of revenue and expenditure (RE) West Kalimantan Provincia funds in handling slums Easy access to the background, outcomes, and implementation of slum upgrading decisions. Good distribution (non-discriminatory) and balance between rights and obligations for each stakeholder. Legal clarity to ensure transparency and fairness in decision-making Availability of comprehensive clarity of communication media to connect each stakeholder in slum upgrading. Published by UI Scholars Hub, 2024. Analysis Code. Geometric Mean. Remark. V1. 4.0. Fulfilled. V2. 3.7. Fulfilled. V3. 4.3. Fulfilled. V4. 2.5. Not Fulfilled. V5. 3.6. Fulfilled. V6. 3.8. Fulfilled. V7. 4.4. Fulfilled. V8. 3.7. Fulfilled. V9. 3.7. Fulfilled. V10. 3.9. Fulfilled. V11. 3.8. Fulfilled. 5. Smart City, Vol. 4 [2024], Iss. 1, Art. 2. Smart City. Category. Data and Evidence. Legitimacy / Compliance with existing policies Accountability for Clarity. Sustainability. Slum Handling Working Group Stakeholder Linkage Plan. Factor Clarity is provided on the initiating party responsible for the implemented communication system. Availability of data and evidence related to 7 aspects of slum assessment (building condition, environmental roads, drinking water supply, environmental drainage, wastewater management, solid waste management, and fire protection) Availability of data and evidence related to land legality, and strategic value of location and population Availability of human resources (experts) and natural resources (materials and equipment) in the technical implementation of slum area management Acceptance of slum upgrading decisions by every stakeholder, legitimate, correct, and recognized by those with authority. The decisions that have been issued can be disputed / formally appealed. The decisions that have been issued can be revised or amended. Having a positive impact on sustainable urban development control and the achievement of slumfree cities Having a positive impact on slum upgrading policies and implementation practices Improvement in financial and political accountability in West Kalimantan Province Increased investment in the West Kalimantan region Improved quality of prioritization of slum settlement management in West Kalimantan. Analysis Code. Geometric Mean. Remark. V12. 3.9. Fulfilled. V13. 4.8. Fulfilled. V14. 4.7. Fulfilled. V16. 3.6. Fulfilled. V17. 4.1. Fulfilled. V18. 3.2. Not Fulfilled. V19. 3.7. Fulfilled. V20. 4.2. Fulfilled. V21. 4.1. Fulfilled. V22. 4.3. Fulfilled. V23. 4.2. Fulfilled. V24. 3.8. Fulfilled. Based on the results of this analysis, two variables were found to have a geometric mean value of less than 3.5; therefore only 22 variables were eligible to be used in the ISM questionnaire. The unqualified variables are Variable X.2.1 "There is a change in the number of Team Members", and Variable X.8.1 "The decisions that have been issued can be debated/officially appealed”. Hence, only 22 variables or factors would be tested using the ISM method. The analysis of the ISM Questionnaire with 22 variables was conducted, resulting in the driving and dependence power diagrams.. https://scholarhub.ui.ac.id/smartcity/vol4/iss1/2 DOI: 10.56940/sc.v4.i1.2. 6. 6. Bich and Rarasati: The ISM for Stakeholder Involvement to Reduce Slum Settlements. Smart City. Figure 1. Driving and Dependence Power Diagram Using the driving power and dependence power, we can also determine the level of each variable. The results are summarized in Table 3. Table 3. Driving and Dependence Score Variables V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19. Published by UI Scholars Hub, 2024. Driving Power 22 22 22 22 22 22 22 22 22 22 22 21 21 22 22 21 19 22 22. Dependence Power 22 20 20 18 22 19 22 22 22 21 22 22 22 22 22 22 22 22 22. Level V VII VII IX V VIII V V V VI V IV IV V V IV II V V. 7. Smart City, Vol. 4 [2024], Iss. 1, Art. 2. Smart City. Based on the level sequencing, a structure of the factors affecting the prioritization of slum handling can be modelled are presented in Figure 2.. Figure 2. Slum Settlement Prioritization Factor Structure Model The hierarchical pattern of the structure model shows that "the differences in terms of knowledge and experience between the new team members and the previous team members" is the basic factor affecting various other factors. This is because the knowledge and experience of team members has a major influence on the process of prioritizing slum handling. The ability of the team members in developing a plan affects its achievement and efficiency to match the availability of revenue and expenditure (RE) of the province of West Kalimantan slum handling funds. When RE efficiency is achieved, the commitment of the initiating party (the stakeholders responsible for proposing slum upgrading) to involve every stakeholder in every slum upgrading activity can be realized. In addition, RE efficiency will also enable the active participation of each stakeholder in slum upgrading.. https://scholarhub.ui.ac.id/smartcity/vol4/iss1/2 DOI: 10.56940/sc.v4.i1.2. 8. 8. Bich and Rarasati: The ISM for Stakeholder Involvement to Reduce Slum Settlements. Smart City. With the realization of the commitment to involve each stakeholder and the active participation of said stakeholders, there will be a clear and comprehensive communication media to connect each stakeholder. Such media will influence the following factors: 1.. Fulfillment of the technical and political needs of each stakeholder in decisionmaking;. 2.. Clear benchmarks for slum upgrading success (Zero Slum Vision by 2030);. 3.. Easy access to the background, outcomes and implementation of slum upgrading decisions;. 4.. Good (non-discriminatory) distribution and balance between rights and obligations for each stakeholder;. 5.. Legal clarity to ensure transparency and fairness in decision-making;. 6.. Clarity regarding the initiating party responsible for the communication system implemented;. 7.. Availability of a priority order for slum area handling based on the formulation of handling priority scale determination stipulated in the circular letter of the Directorate General of Human Settlements;. 8.. Availability of human resources (experts) and natural resources (materials and equipment) in the technical implementation of slum area management;. 9.. Positive impact on sustainable urban development control and the achievement of slum-free cities;. 10.. Positive impact on slum upgrading policies and implementation practices;. 11.. Quality improvement in the prioritization of slum upgrading in West Kalimantan.. The above 11 factors will affect the availability of data and evidence related to the seven aspects of slum assessment, land legality, and the strategic value of location and population. These 11 factors are also the basis for the acceptance of slum upgrading decisions by each stakeholder, which are legal, correct, and recognized by those with authority. In addition, the availability of data and the acceptance of handling decisions by each stakeholder can trigger increased investment in the West Kalimantan region. In turn, increased investment is the basis for revising and amending issued decisions, while revised decisions are the basis for improving financial and political accountability in West Kalimantan Province.. Published by UI Scholars Hub, 2024. 9. Smart City, Vol. 4 [2024], Iss. 1, Art. 2. CONCLUSION The highest influence value is held by the steering committee, namely the Governor of West Kalimantan, while the highest interest value is held by the members of the advisory team, which is the agency directly responsible for the slum upgrading program in West Kalimantan. There are 24 stakeholders with four types of quadrants and two types of classifications. Stakeholders who will be involved in decision-making are in Quadrant D (Manage Closely) and the primary stakeholders who have a direct interest in resources are the agencies responsible for the slum upgrading programs. These stakeholders are members of the supervisory team, namely the Head of the HSAO, and the Head of the RDPA. There are 10 categories and 22 factors identified as influencing the decisions in slum upgrading prioritizaton. The categories are stakeholder satisfaction and engagement, stakeholder turnover, goals and targets for prioritization, transparency and fairness, communication systems, data and evidence, legality or compliance with existing policies, accountability for clarity, sustainability, and stakeholder linkage plans of the slum handling working group. The results of the analysis show that there are nine levels of ranking based on the interpretative structural modeling. Level nine is the most significant factor that influences decisions in prioritizing slum upgrading, namely “the differences in terms of knowledge and experience between the new team members and the previous team members”. This research is limited to the area which is the responsibility of the HSAO of West Kalimantan, especially the slum settlement. The stakeholders analyzed are internal stakeholders in West Kalimantan Province who are officially involved in the slum upgrading program. 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