23 GeoPlanning Journal of Geomatics and Planning Vol. 8, No. 1, 2021 Original Research Slum Upgrading Spatial Model Based on Level of Vulnerability to Climate Change in Coastal Area of Semarang City Khristiana D. Astuti 1*, P. Pangi 1, Reny Yesiana 1, Intan M. Harjanti 1 1. Diponegoro University, Indonesia DOI: 10.14710/geoplanning.8.1.23-40 Abstract Slum settlement is one of the significant global problems which requires special concern in the discussion agenda of Sustainable Development Goals (SDGs) of 2016-2030. The Sustainable Development Summit held in New York in September 2015 formulated that one of SDGs goals is to build inclusive, safe, resilient, and sustainable cities and settlements. In Indonesia, the achievement of this goal is stated in National Medium-Term Development Plan 2015- 2019, i.e. creating 0% urban slum settlement which is supported by policies expected to accommodate the achievement of national development targets. Semarang Mayor Decree No. 050/801/2014 concerning the Determination of the Location of Housing Environment and Slum Settlements in Semarang City has been issued as the basis to identify slum settlements scattered throughout Semarang city, in terms of location, physical condition, and social conditions. This study was conducted by case studies on slum settlements in Trimulyo Village and Mangkang Wetan Village, Semarang city, Central Java Province, Indonesia, to formulate a slum upgrading model based on the resilience level of coastal communities towards climate change. The analysis included identifying the characteristics of slum settlements, scoring analysis to determine the resilience level possessed by coastal communities, and analysis of pentagon assets used to formulate slum upgrading models. The results of the study showed that these two research areas had a moderate level of vulnerability, with several different characteristics of asset ownership, particularly those related to human and social assets. Increasing the quality of human resources and social relations in the community was more intensified in the environment and community in Trimulyo, while improving the physical quality of the environment through housing improvements was carried out in Mangkang Wetan. Copyright © 2021 GJGP-Undip This open access article is distributed under a Creative Commons Attribution (CC-BY-NC-SA) 4.0 International license 1. Introduction Trend on population growth is dominated by urban areas which not only function as centers for development activities but also as centers of population growth (Carter et al., 2015). The increasing number of urban residents throughout the years results from various socio-economic backgrounds and some of them come to cities without a clear purpose (Olthuis et al., 2015). Based on data from the UN Urbanization Prospect Projection, it was estimated that more than 54% of the world’s population in 2016 lived in urban (Population Divisions Department of Economic and Social Affairs, 2018). Such a high population in urban areas is often insufficiently balanced by the readiness of urban system plans which may accommodate the developments. Consequently, the increasingly diverse activities but not integrated with the planned urban activity system cause many implications for the emergence of other various urban problems. The need for housing in urban areas is an essential basic need with high demand; when housing prices are nevertheless not affordable for the poor living in cities, this certainly will worsen the conditions in urban areas, one of which is the increasing number of developing slum settlements (Saad et al., 2019). e-ISSN: 2355-6544 Received: 9 April 2020; Accepted: 5 May 2021; Published: 30 July 2021. Keywords: Slum upgrading, coastal community, vulnerability. *Corresponding author(s) email: khristiana.dwiastuti@live.undip.ac.id https://doi.org/10.14710/geoplanning.8.1.23-40 mailto:khristiana.dwiastuti@live.undip.ac.id Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 24 The increasing population growth in the East Asia and Pacific (EAP) Region over time has caused this region as the largest slum population in the world. There are approximately 75 million people (out of 250 million people) in EAP who live in slum areas living under the poverty level with income below US$ 3.10/day. Cities with the highest number of urban poor people are located in China, Indonesia, and the Philippines, while the highest rates of urban poverty are in the Pacific Island countries of Papua New Guinea and Vanuatu, Indonesia, and the Lao People's Democratic Republic (Baker & Gadgil, 2017). This issue does not only occur in one or two countries, but it has been a global issue. Thus, managing slum areas has been one of the global agendas contained in Sustainable Development Goals (SDGs) 2016- 2030 (INFID, 2019; Meredith & MacDonald, 2017). The handling of slum settlements in the SDGs is the 11th of the 17 goals and 169 targets expected to be achieved by 2030. The 11th goal describes "Building Inclusive, Safe, Resilient and Sustainable Cities and Settlements", with the first target is to ensure access for all communities to decent, safe, and affordable housing, including slum management and access to basic urban services. As an effort to achieve this goal, UN-Habitat formulated Participatory Slum Upgrading Program (PSUP) in 2008 as a result of discussions conducted with several representative countries of Africa, the Caribbean, and the Pacific (ACP), and the European Mission (EC). UN-Habitat assists countries to develop and implement housing policies, strategies, and programs aimed at increasing access to adequate housing, improving the living conditions of slum inhabitants, and preventing the proliferation of new slum settlements (De Schutter, 2014). The implementation of PSUP has been seen in various countries such as the Asia Coalition for Community Action (ACCA) Program targeting an increase in inclusive slum settlements for the urban poor in Thailand (Baker & Gadgil, 2017) and the Kenya Slum Upgrading Program (KENSUP) which seeks to improve the quality of life for people living in slum neighborhoods in Kenya by improving housing quality, community income, providing tenure security, and improving infrastructure (Meredith & MacDonald, 2017). Moreover, under the supervision of Housing and Urban Renewal Authority Inc. (HURA), a slum upgrading program is carried out in the Philippines by updating or rebuilding damaged slums and other urban communities, developing resettlement sites, and mostly by improving and promoting urban development (Minnery et al., 2013). In Indonesia, improving the quality of slum upgrading in urban areas is one of the national priority programs towards cities without slums (KOTAKU) based on the National Medium Term Development Plan (local term: RPJMN) 2015-2019 (Bappenas, 2017). KOTAKU program is an effort to accelerate the handling of slum settlements to support the achievement of the "100-0-100" target, i.e. 100% access to drinking water, 0% slum areas, and 100% access to proper sanitation by 2019 (Public Works Office/Dinas Pekerjaan Umum, 2017). According to the Central Statistic Bureau (local term: Biro Pusat Statistik/BPS) data stating that by the end of 2013, access to drinking water achieved in urban areas was 67%, 11.6% for slum areas, and 59% for access to proper sanitation. Since the trend for population growth continues to increase (BPS, 2017), it is necessary to create integrated efforts to achieve the targets of this program involving the central government, local governments (provincial, regency or city, villages), and the community. Therefore, it is fundamentally reasonable that the government should gradually reduce the areas of slum settlement and increase the achievement of settlement infrastructure, specifical access to drinking water and sanitation for urban communities (Dirjen Cipta Karya, 2015a). KOTAKU program is nationally implemented in 34 provinces involving over 268 regencies/cities in 11,067 villages (desa and kelurahan) (Dirjen Cipta Karya, 2015b). In addition, the target achievement of KOTAKU program has been carried out moderately from 2015 until 2019. Moreover, at the end of 2015, urban slum areas were targeted to be reduced to 8%; around 6% in 2016; and respectively reduced to 4% and 2% for the following years 2017 and 2018; until the target of 0% was achieved by the end of 2019. Semarang city is one of the targets for the implementation of KOTAKU program in Indonesia. There are some slum settlements scattered in this city of which are located in coastal areas. This definitely affects the characteristics of the slum settlements in the area as seen physically from the building condition, the existence of environmental infrastructure in the settlement, as well as disaster threat like rob (seawater flooding) which frequently becomes an obstacle in managing slum areas problems. Furthermore, it can also be non-physically identified from the social life pattern of the community, how they earn money (livelihoods), and people’s daily living habits. The characteristics of the people living in coastal areas certainly cannot be https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 25 separated from the current global phenomena which are closely related to climate change that directly or indirectly has implications for the lives of coastal communities (Sariffuddin et al., 2017) including those who live in the slum settlement at the coastal area. Accordingly, the efforts to improve the conditions of the slum environment must be holistically concerned both physically and non-physically regarding the characteristics of the community in dealing with the conditions they own. Thus, community participation can be considered as a significantly integral approach that needs to be implemented to achieve the goals of KOTAKU program (Yu et al., 2016). To support the realization of the '100-0-100' program, the handling and management of slum settlements specifically in coastal areas, therefore, needs to be carried out integratively through a slum upgrading model considering the resilience level of coastal communities toward climate change which differs from one region to others. 2. Data and Method 2.1 Study Area The scope area of this research covered Mangkang Wetan Village (local term in Semarang city: kelurahan) located in Mangkang Village and Trimulyo Village, a part of Genuk subdistrict (Figure 1). Both villages (Figure 2) are included in the administrative local government of Semarang City. These two areas were selected as the research areas because these villages are listed in the Decree of Semarang city Mayor No. 050/801/2014 about the Determination of the Location of Slum Housing and Settlements Environment of Semarang City, and became part of the pilot projects to improve coastal community resilience by strengthening mangrove ecosystem services and developing sustainable livelihoods in Semarang City in collaboration between Semarang City Government and NGO (Mercy Corps Indonesia) with funding assistance from the Rockefeller Foundation. Figure 1. Location of Study Area https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 26 Figure 2. Map of Mangkang Wetan and Trimulyo Villages 2.2 Method The method used in this study was quantitative. The method was used to analyze the vulnerability level of the community toward the climate change in the coastal area and formulate the slum upgrading strategy based on-field characteristics. Data gathering was performed using questionnaires and observation, also document assessment. Samples were taken using simple random sampling, with 18 respondents from Mangkang Wetan Village and 14 respondents from Trimulyo Village. There were 3 stages to answer the aim of the study: a. Slum settlement characteristic identification Slum settlement characteristic identification was based on few aspects which had been determined by Dirjen Cipta Karya which consists of: building condition, road condition, drainage condition, water supply condition, wastewater management, waste management, and fire extinguish system condition. Those aspects and criteria could be seen in Table 1. b. Vulnerability level of community in the coastal area The analysis technique used to identify the vulnerability level of the community in the coastal area was scoring. This analysis technique was performed to identify the score of every sub-variable (Table 2) in each exposure variable, sensitivity variable, and adaptation capability variable (Boer, 2012). The highest score from each sub-variable was different, the score was based on how much the indicator used for the scoring. In the exposure variable, the highest score was 5 points, while in the sensitivity variable the highest score was 3 and 4 points for the adaptation capability variable. However, the lowest score from every variable was all the same as, i.e. 1 point. Thus, after counting each variable, there would be 3 scores for each respondent. The formula for each respondent could be seen at equation (1) and (2): As explained previously, the vulnerability was affected by the exposure level, sensitivity, and adaptation capability. The vulnerability formula could be seen below: Variable cumulative score = Sub variable score amount ……………………………… (1) Sub variable highest score amount Vulnerability rate = exposure score x sensitivity score ……………………………………... (2) Adaptation capability score https://doi.org/10.14710/geoplanning.8.1.23-40 18465-46665-1-SM%20New.docx#Boer2012 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 27 Table 1. Slum Settlements Criteria (Dirjen Cipta Karya, 2015a) No Aspects Criteria 1. Building condition Building regularity (dimension, orientation, footprint, and building form) Building compactness Building technical requirement (structure system, lighting safety, weather control, lighting, sanitation, and building material) 2. Road condition Service area Road condition 3. Drainage condition Inundation presence (inundation duration, inundation frequency) Service area 4. Water supply condition Technical requirement (pipe network, non-pipe network) Service area 5. Wastewater management Technical requirement (personal wastewater management, communal and center wastewater management) Service area 6. Waste management Technical requirement (warehouse, sorting, gathering, and management) Service area 7. Fire extinguish system condition Water supply to extinguish the fire (natural resource: pond, lake, river, deep well; artificial resource: water tank, pool, water reservoir, water tank car, hydrant) The road for the fire truck Table 2. Sub Variable and Scoring that Affected Vulnerability Level (Analysis, 2018) No Variable Sub Variable Weight No Variable Sub Variable Weight Exposure Variable Adaptation Capability Variable 1 Occupation Fishpond owner 5 1 Group program Exist 2 Fishpond worker 4 Nothing 1 Fisherman 3 2 Group program involvement Often 4 Processing fishery products 2 Sometimes 3 Don’t have a job 1 Never 2 2 Fishpond ownership Yes 2 Not active 1 No 1 3 Skill training involvement Yes 2 3 Fishpond productivity Not productive 2 No 1 Productive 1 4 Training advantages Yes 2 4 Fishpond is stricken by flood Yes 2 No 1 No 1 5 Training result utilization for income resource alternative Yes 2 5 Home is stricken by flood Yes 2 No 1 No 1 6 Routine meeting involvement Yes 2 6 Flood frequency in every house in a month. > 2 x 2 No 1 < 2 x 1 7 Routine meeting frequency Once a week 3 7 Flood duration in every house > 2 hour 3 Once a month 2 1-2 hour 2 More than once a month 1 < 1 hour 1 8 Routine meeting benefits Exist 2 8 Source of clean water Well 3 Nothing 1 artesian well 2 9 Media information (group meeting, meeting in RT/RW, Radio, SMS) >4 of media 3 PDAM 1 2-3 of media 2 9 Family member amount >4 people 2-3 people 3 <2 of media 1 2 10 Group meeting Very effective 4 < 2 people 1 Effective 3 Number of Exposure 24 Less effective 2 Not effective 1 Sensitivity Variable Meeting (RT/RW) Very effective 4 1 Monthly income < IDR 1,500,000 3 Effective 3 IDR 1,500,000- IDR 2,000,000 2 Less effective 2 > IDR 2,000,000 1 Not effective 1 2 Monthly outcome > IDR 2,000,000 3 Radio Very effective 4 IDR 1,500,000- IDR 2,000,000 2 Effective 3 < IDR 1,500,000 1 Less effective 2 3 Asset ownership (Land, House, Boat, Fishpond, Etc.) < 1 asset 3 Not effective 1 1-3 assets 2 SMS/ WA Very effective 4 > 4 assets 1 Effective 3 4 Capital access/ loan No 2 Less effective 2 Yes 1 Not effective 1 Number of Sensitivity 11 11 Information media usage Yes 2 No 1 12 Weather information needs Yes 2 No 1 13 Media used to spread the information >4 of media 3 2-3 of media 2 <2 of media 1 Number of Adaptation Capability 45 https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 28 c. Spatial Analysis of community in the coastal area Spatial analysis was carried out on the results of the questionnaire in two research locations. In addition to using random sampling to determine the number of samples, the location of the sample is determined by spatial sampling. Spatial sampling is a sampling activity based on geographic/coordinate locations (Buchori & Pangi, 2015; Thompson, 1997). Respondents are marked based on their location coordinates. The results of the questionnaire answers were mapped based on sample locations and continued with interpolation analysis. The results of the interpolation analysis of the questionnaire data were used to perform spatial analysis based on the vulnerability criteria. 3. Results and Discussion 3.1 Slum settlements characteristic The slum settlements area used in this study was the settlements in Mangkang Wetan village and Trimulyo village. Mangkang Wetan village is part of the Tugu subdistrict which is located in the western part of Semarang City, while Trimulyo village is one of the coastal areas located in Genuk subdistrict, Semarang City. a. Mangkang Wetan Village The location distribution of slum settlements in Mangkang Wetan village is in RW 5, 6, and 7 with a total slum settlements area of 13.59 hectares. The distribution of slum locations in Mangkang Wetan Village can be seen in Figure 3 and Appendix 1. Figure 3. Map of Slum Settlements Distribution in Mangkang Wetan Village (BKM, 2017) https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 29 There were approximately 388 units of houses in the slum settlements area. Some of them were permanent units with plaster (cemented floor) or ceramic made floor, brick or wood mass wall and the roof was constructed by using the tin roof and/or wavy tile roof. The rest, 136 units, were semi-permanent buildings and 46 units were non-permanent buildings. Generally, the status of the houses in the slum settlements was personal ownership. Based on the identification results during the field research, infrastructure in the slum area in Mangkang Wetan includes a road network in the form of footpaths and some of which were already damaged, especially in RW 05 and RW 07. The drainage system in the slum settlements area was in the form of the open canal and close canal. The drainage system of the settlements mostly had got shallower and some of the canals were already damaged. The inundation from flood location or the area with the high frequency of precipitation was the effect of this suboptimal drainage system. In addition, the clean water supply system is fulfilled through drilled wells because the PDAM (drinking water regional company – a company owned by the city government) piping system has not yet reached the location. Meanwhile, concerning wastewater treatment infrastructure (Sanitation), approximately 92% of the houses already had sanitation facilities/toileting; however, 8% of the community which does not possess the toileting yet still use the communal sanitation facilities. b. Trimulyo Village The location distribution of slum settlements area in Trimulyo village is in RW 3, particularly in RT 3 and RT 4 with 3.55-hectare total slum settlements area. The distribution of slum locations in Trimulyo Village can be seen in Figure 4 and Appendix 2. Figure 4. Map of Slum Settlements Distribution in Trimulyo Village (BKM, 2017) The houses in slum settlements area of Trimulyo village were entirely permanent units with plaster/ceramic made floor, brick or wood mass wall and the roof was constructed by a tin roof and wavy tile roof. The status of the houses in the slum settlement was personal ownership. The road network was in the form of local environmental roads and they were generally in good condition and usable, while the drainage network was dominated by soil and masonry construction but less optimal function due to silting. As the supply of clean water in Mangkang Wetan Village, Trimulyo has not been reached by the local drinking water company (PDAM) network; thus, the community meets their clean water needs by using drilled wells. However, for sanitation, all of the people in Trimulyo Village already have their own sanitation facilities. https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 30 3.2 Vulnerability Level Analysis of Coastal Area Community in Mangkang Wetan Village and Trimulyo Village As one of the global warming effects, the rise of sea surface has caused a change in sea current and also made the land near the seashore logged, and thus it often affects the settlements in the coastal area (Susandi et al., 2008). The settlements near the shore/river are commonly more susceptible than any other settlements far from the shore/river. It could happen since the land far from the shore/river or any waters would spend a longer duration to get logged (Wulandari et al., 2013). A damaged mangrove ecosystem is another effect of the rising sea surface. Therefore, if mangrove existence cannot be revived anymore, the abrasion of the land will occur more frequently than before because there is no backup when the wave comes. This phenomenon will affect the economic condition of the community in the coastal area; thus the coastal community will be more susceptible the climate change. In concordance, the relative escalation of sea surface would bring some consequences toward the coastal area, such as littoral area would be logged (1 cm escalation of the sea surface would decrease 1 cm of the shore), erosion would occur more frequently, the salt concentration of the soil will increase so it would no longer suitable for human to consume, and also the escalation of the sea in estuary area (Suhelmi & Prihatno, 2014). This study aimed to assess the vulnerability level of coastal areas in Semarang city by considering Mangkang Wetan (west coastal area) and Trimulyo Genuk (east coastal area) as the location of this case study. There were 3 variables analyzed in this study, i.e. exposure, sensitivity, and adaptation capability. Based on the data acquired in the field study, the result of those variables can be described as follow: a. Exposure Gallopin (2006) stated that exposure level represents the level, duration, and/or chance of a system to contact with disturbance or shock (Boer, 2012). The exposure level in Trimulyo and Mangkang Wetan villages was categorized as high, i.e. 76% and 74% respectively. Moreover, the exposure level in Mangkang Wetan village was affected by the occupation of the people living mostly as pond owners. Since the expense of pond maintenance was quite high, when the abrasion came it would bring more disadvantages toward the people. Meanwhile, the vulnerability of Trimulyo village was affected by the community occupation as fishermen. Trimulyo community had no land to make a pond and there were only 2-3 people of Trimulyo village whose pond for fish cultivation. However, the land used as a pond was a government-owned one. In addition, the majority of the community worked as fishermen. Furthermore, another indicator of vulnerability level was that there were more houses damaged by the flood in Trimulyo village than those in Mangkang Wetan village. Nevertheless, in some points, flood duration in Mangkang Wetan village was much longer than in Trimulyo village. The exposure levels are depicted spatially in Figure 5. The spatial characteristics of exposure levels between Mangkang Wetan and Trimulyo village are different since Mangkang Wetan exposure level is higher than that of Trimulyo (Appendix 3). b. Sensitivity Sensitivity was the internal condition of the system representing the vulnerability level toward any disasters (Boer, 2012). The sensitivity level of Trimulyo village was lower than that of Mangkang Wetan village (Figure 6). Moreover, Mangkang Wetan village’s sensitivity level was affected by higher monthly income gained by the community than that in Trimulyo village. Furthermore, Mangkang Wetan village income ranged from IDR 1,874,931, while Trimulyo village was only ranging from IDR 1,438,889,-. Therefore, the community in Mangkang Wetan village had generally more assets than Trimulyo village’s community. The assets were mostly in the form of land, house, boat, fishpond, etc. In addition, the sensitivity level of these two villages is illustrated in Appendix 4. https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 31 Figure 5. Map of Exposure Level in Mangkang Wetan and Trimulyo Villages Figure 6. Map of Sensitivity Level in Mangkang Wetan and Trimulyo Villages https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 32 c. Adaptation capability Adaptation capability represents the ability of a system to adapt toward the climate change phenomenon to reduce the negative effect and to maximize the positive effect or in other words, it could handle the consequences of climate change (Boer, 2012). The approach conducted to fishing groups was by doing some attempts to increase the community's adaptive capability toward disaster vulnerability such as training to improve skills in processing fishery products and mangrove tourism entrepreneurship as alternative sources of income for the community. Regular meetings and the use of information media are some means used by the community to respond to disasters as they live in coastal areas. Appendix 5 describes the level of adaptation capability found in this study. Map of adaptation capability in both of study area can be seen in Figure 7. Based on the result of three variables, the vulnerability level of both villages was then being counted. Vulnerability level was categorized in 3 groups: High vulnerability (>0.6), moderate vulnerability (0.3-0.6), and low vulnerability (<0.3). Table 3. Result of Vulnerability Calculation in Mangkang Wetan dan Trimulyo Villages (Analysis, 2018) Vulnerability Variable Village Mangkang Wetan Trimulyo Exposure (K) 76% 74% Sensitivity (S) 54% 49% Adaptation(A) 74% 69% Vulnerability Level (KxS/A) 0.56 0.53 The level of vulnerability in Mangkang Wetan and Trimulyo villages was categorized in moderate, i.e. 0.56 and 0.53 respectively (Tabel 3). However, the vulnerability level of Mangkang Wetan village showed a higher rate (74%) than Trimulyo village (69%). This result showed that the vulnerability of Mangkang Wetan community was stronger than that of Trimulyo village. In addition, the vulnerability level represents the survival rate of the community in handling the climate change phenomenon. Map of vulnerability in both of study area can be seen in Figure 8. Figure 7. Map of Adaptation capability in Mangkang Wetan and Trimulyo Villages https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 33 Figure 8. Map of Vulnerability in Mangkang Wetan and Trimulyo Villages 3.3 Slum Upgrading Spatial Model The formulation of the slum upgrading model is based on the characteristics of the slum settlements in Mangkang Wetan and Trimulyo Villages by paying attention to the level of community vulnerability to climate change. This is done considering that both villages (local term: kelurahan) are coastal areas that are at risk from the impacts of climate change. This is in line with the implementation of the Asian Cities Climate Change Resilience Network (ACCCRN) program which seeks to make Semarang a resilient city through increasing attitudes and behavior as well as knowledge and skills capabilities, building networks to increase knowledge and skills for the community (Sariffuddin et al., 2017). Vulnerability and risks to climate change are influenced by the existence of social relations between the community and its surrounding environment, both related to their physical, social and economic conditions (Folke, 2006). Various asset limitations and conditions in accessing existing resources become obstacles in improving the quality of slum settlements (Olotuah, 2012). Therefore, strategic efforts as a solution to improve the quality of the slum environment are needed to involve all relevant stakeholders. Slum upgrading, which is an effort to improve the quality of the slum environment, is realized through the community's active participation and involvement. This is because slum upgrading is realized through a social program and a series of democratic activities with a clear direction of communication (deliberation for instance) to accommodate the aspirations of the community, as well as to increase the capacity of its human resources. Improving the quality of the environment in slum settlements is also inappropriate if it is carried out through a top-down approach by ignoring the role of the community (Meredith & MacDonald, 2017; Olotuah, 2012; UN Habitat, 2016). The pattern of activities in the community is influenced by asset ownership and community livelihoods (Singh & Gilman, 2000). In this study, asset ownership was identified from 5 components: human capital, physical capital, social capital, finance capital, and natural capital, which were obtained through observations and questionnaires. Human capital represents the ability of someone in acquiring better access to their lifestyle (Nugroho et al., 2017). Human capital assessment in this study was measured by education, involvement, and creativity inside the group, using the training result as an income alternative (Singh & Gilman, 2000). In addition, social capital was identified through social connections or relations among the https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 34 community to support their social lives. In this study social capital was being assessed using 6 indicators: group program, group program involvement in both villages, routine meeting involvement, group meeting, and media usage for transferring information in daily life, especially for the matters related to coastal area community adaptation toward the vulnerability of each region also how much the network of stakeholders involved in giving training in every village. Slum settlement area of the coastal area had a physical characteristic which may be seen from their dwelling or the infrastructure. The physical capital in this study was identified using 5 indicators, i.e. house condition assessed from the permanence of their building, road condition seen from the damage of the road itself, drainage system, clean water accommodation, and also sanitation system. Then, financial capital was related to income or salary acquired by the individuals of the community each month, monthly outcome, and access to get capital or loan for their business or their asset ownership. That financial capital can encourage community participation in improving the quality of their lives (Das, 2015). Natural capital assessed in this study was based on 5 indicators: Fishpond productivity, Fishpond damaged by flood, house damaged or stricken by flood, flood duration in every house, and flood frequency in a month. Table 4. Result of Pentagon Asset Assessment (Analysis, 2018) No Indicator Mangkang Wetan Trimulyo No Indicator Mangkang Wetan Trimulyo 1 Human Capital 0.88 0.53 4 Finance Capital 0.69 0.75 Education 0.26 0.11 Monthly income 0.13 0.13 Involvement inside the group 0.22 0.20 Monthly outcome 0.13 0.13 Creativity (using the training result as income alternative) 0.18 0.11 Capital access/ loan 0.06 0.06 Participation in skill training 0.22 0.11 Fishpond ownership 0.13 0.06 2 Social Capital 1.00 0.78 Land ownership 0.06 0.13 Group program 0.17 0.11 House ownership 0.13 0.13 Group program Involvement 0.17 0.17 Boat ownership 0.06 0.13 Routine meeting involvement 0.17 0.17 5 Natural Capital 0.12 0.15 Group meeting 0.17 0.17 Fishpond productivity 0.17 0.08 Media usage for information transfer in daily life 0.17 0.11 Fishpond damaged by flood 0.17 0.08 Network (government and NGO) 0.17 0.06 Damaged houses because they were stricken by flood, 0.08 0.17 3 Physical Capital 0.80 0.73 Flood duration in every house 0.10 0.25 House condition 0.20 0.20 Flood frequency in every house in a month. 0.08 0.17 Road condition 0.20 0.13 Drainage system 0.07 0.07 Clean water accommodation 0.13 0.13 Sanitation system 0.20 0.20 Based on vulnerability analysis of the community in the coastal area, Mangkang Wetan Village and Trimulyo Village both had moderate vulnerability levels. Mangkang Wetan village represented the coastal area of West Semarang, while Trimulyo village represented the coastal area of North Semarang. Although both villages were categorized as slum settlement areas with similar vulnerability levels, the slum upgrading model for these two villages was different. The result of the pentagon asset analysis (Figure 9) showed that Human Capital and Social Capital aspects in Mangkang Wetan village were higher than those in Trimulyo village, while the other capital conditions were almost similar both in Mangkang Wetan and Trimulyo villages. The result of pentagon asset assesment can be seen in Table 4. https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 35 Figure 9. Analysis of Pentagon Asset in Mangkang Wetan and Trimulyo Villages (Analysis, 2018) Slum upgrading strategy in slum settlement of study area can be seen in Table 5. Table 5. Slum Upgrading Strategy in slum settlements of Mangkang Wetan and Trimulyo Villages (Analysis, 2018) No. Pentagon Asset Mangkang Wetan Trimulyo 1. Human Capital Training improvement should be maintained to support the creativity of Mangkang Wetan community. Increasing the training and skill among the community in Trimulyo village. This program was aimed to increase the creativity of the people to take every benefit from the training activity. 2. Social Capital Innovation in group programs so that people are not bored and increasingly interested in engaging in the program Increasing the government network involvement and NGO in the village was necessary. Along with the improvement of the network, it could open the access to increase the training process toward the community. 3. Physical Capital  Building regulation and physical condition refinement of the house  Reducing inundation spots and increasing the capacity also the quality of drainage in the settlements.  House system improvement to access decent sanitation.  Fire hydrant availability for fire safety.  Road quality and access improvement.  Fire hydrant availability for fire safety.  Reducing inundation spots and increasing the capacity also the quality of drainage in the settlements 4. Financial Capital Capital access improvement. Capital access improvement. 5. Natural Capital Pond protection using APO (wave breaker equipment) House protection through mangrove cultivation on the side shore. 4. Conclusion Slum upgrading as a program to improve the environmental quality of slum settlements area should consider various aspects such as physical, social, and economic aspects. However, besides these three aspects, it is necessary to observe human resource quality in the area and also natural resource availability which could be used for the community interests. Pentagon asset analysis was used in this study to assess those five aspects based on the existing condition in the research location. Based on the analysis result, it showed that there was a difference in the characteristic of Mangkang Wetan village in Mangkang village and Trimulyo village in Genuk subdistrict. The vulnerability level of the coastal area community toward climate change, social capital, and human capital in Mangkang Wetan village was relatively higher than Trimulyo village. This result was affected by various programs which had been performed to handle the effect of climate change along with intensive involvement of the community in Mangkang Wetan village. https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 36 Therefore, slum upgrading can be conducted by concerning the improvement of human resource quantity and quality and making social relation in the community more intensively to the community of Trimulyo village. Physical quality improvement of the environment may be established by repairing and refining houses in Mangkang Wetan village as there are still 30% non-permanent houses. Meanwhile, drainage quality network improvement is necessary for both villages since the drainage function is not optimal yet because of the silting which causes inundation formation. Previous studies have discussed more the resilience of coastal communities, but have not yet been concerned about how the resilience of these communities affects the efforts to improve slum settlements. However, through this research, the output of the analysis shows that differences in community characteristics, including the community's response to the disasters they face in coastal areas, will affect the efforts to improve the quality of life. 5. Acknowledgments The authors would like to express their gratitude to UNDIP Vocational School which has funded this research. 6. References Baker, J. L., & Gadgil, G. U. (2017). East Asia and Pacific Cities: Expanding opportunities for the urban poor. World Bank Publications. Bappenas. (2017). Rencana Pembangunan Jangka Menengah Nasional 2015-2019. Bappenas. BKM. (2017). Neighborhood Upgrading Action Plan Mangkang Wetan 2016. Semarang. Boer, R. (2012). Ruang Lingkup Kajian Kerentanan: Antara Teori Dan Praktek. CCROM-SEAP IPB. 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The Location Distribution of Slum Settlements in Mangkang Wetan Village (BKM, 2017) No. Slum Area (RW/RT) Slum Wide (Ha) Population Poor Population House Building* House- hold People House- hold People Number Slum 1. RW.05 1 3.81 74 252 43 171 35 4 2 62 216 31 123 35 6 3 49 177 18 70 38 3 4 44 162 13 51 30 2 5 44 162 13 52 19 2 2 RW.06 1 4.34 39 147 8 32 23 1 2 43 159 12 47 22 3 3 41 153 10 40 20 1 4 36 138 5 18 25 1 5 43 159 12 46 40 3 6 42 156 11 42 27 3 3 RW.07 1 5.43 41 153 10 39 22 5 2 48 174 17 67 23 4 3 39 177 8 32 27 2 4 44 162 13 51 23 3 5 52 186 21 83 31 6 6 57 201 26 104 39 18 7 61 213 30 119 39 8 8 49 177 21 85 30 11 9 40 150 9 37 24 7 Total 13.59 948 3474 331 1309 572 91 *) Slum building is a house that is not a decent place to stay review by the main building construction (roof, floor, and building wall) Appendix 2. The Location Distribution of Slum Settlements in Trimulyo Village (BKM, 2017) No. Slum Area (RW/RT) Slum Wide (Ha) Population Poor Population House Building* Household People Household People Number 1. 03/03 0.64 138 138 19 100 33 2. 03/04 0.68 136 136 23 103 47 Total 3.55 415 415 66 286 117 https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 39 Appendix 3. Exposure Level of Mangkang Wetan and Trimulyo Villages (analysis, 2018) No Indicator Mangkang Wetan Trimulyo 1 Occupation 20.83% 12.50% 2 Fishpond ownership 6.55% 4.17% 3 Fishpond productivity 5.65% 8.33% 4 Fishpond is stricken by flood 7.44% 4.17% 5 Houses are stricken by flood 5.95% 8.33% 6 Frequency of houses stricken by flood 3.27% 8.10% 7 Duration of houses stricken by flood 7.74% 9.49% 8 Source of clean water 7.44% 7.41% 9 Family member amount 11.31% 11.34% Number of Exposure 76 % 74% Appendix 4. Sensitivity Level of Mangkang Wetan and Trimulyo Villages (analysis, 2018) No Indicators Mangkang Wetan Trimulyo 1 Monthly income 12.34% 13.64% 2 Monthly outcome 19.48% 15.66% 3 Asset ownership (Land, House, Boat, Fishpond, Etc.) 5.56% 2.72% 4 Capital access/ loan 16.88% 17.17% Number of Sensitivity 54% 49% https://doi.org/10.14710/geoplanning.8.1.23-40 Astuti et al. / Geoplanning: Journal of Geomatics and Planning, Vol 8, No 1, 2021, 23-40 DOI: 10.14710/geoplanning.8.1.23-40 40 Appendix 5. Adaptation capability Level of Mangkang Wetan and Trimulyo Villages (analysis, 2018) No Indicators Mangkang Wetan Trimulyo 1 Group program 2.22% 2.22% 2 Group program involvement 7.46% 8.89% 3 Skill training involvement 3.33% 2.47% 4 Training advantages 3.65% 2.47% 5 Training result utilization for income resource alternative 3.17% 2.22% 6 Routine meeting involvement 3.17% 1.98% 7 Routine meeting frequency 4.29% 4.07% 8 Routine meeting benefits 6.03% 4.44% 9 Information media (group meeting, meeting RT/RW, Radio, SMS) 4.29% 4.44% 10 Information media 4.29% 4.44% 11 Group meeting 6.67% 8.64% 12 Meeting (RT/RW) 7.46% 6.67% 13 Radio 2.22% 2.22% 14 SMS/Whatsapp text messaging 4.44% 2.47% 15 Information media usage 4.29% 4.44% 16 Weather information needs 4.44% 4.44% 17 Media used to spread the information 2.38% 2.22% Number of Adaptation Capability 74% 69% https://doi.org/10.14710/geoplanning.8.1.23-40