Household Climate Resilience Index and Its Determinants: An Empirical Study in DKI Jakarta
Abstract
Climate change has intensified environmental pressures in urban coastal areas, particularly in DKI Jakarta, where recurrent flooding, tidal inundation, and heat extremes threaten urban sustainability. This study developed a Household Climate Resilience Index (HCRI) to assess the resilience of urban households to climate-related hazards using a robust principal analysis (RPCA) framework. The analysis was based on household survey data from 221 respondents across 17 urban villages in Jakarta, encompassing four resilience dimensions: exposure, sensitivity, incremental adaptation, and transformational adaptation. RPCA with a minimum covariance determinant estimator was applied to minimize the influence of outliers and ensure stable component estimation. The results reveal clear spatial heterogeneity in resilience, characterized by a distinct north–south gradient: northern coastal areas such as Kamal, Koja, and Pluit show the lowest resilience due to high flood exposure and land subsidence, whereas central and southern areas exhibit stronger adaptive capacity. The key determinants of resilience include flood frequency, household education levels, per-family expenditure, and proactive adaptation behaviors. The Kendall correlation test (τ = 0.518, p = 0.015) confirmed a significant positive association between flood occurrence and low resilience levels. The developed HCRI provides a robust, data-driven framework to support targeted climate adaptation policies and urban resilience planning in Jakarta, Indonesia. HCRI outputs, together with the identified key determinants (flood frequency, education, per-family expenditure, and proactive adaptation), can guide the prioritization of urban environmental management and adaptation investments in the most vulnerable urban villages, including drainage upgrading, land subsidence control, and coastal protection.
Full text article
References
1. Schipper, E.L.F.; Revi, A.; Preston, B.L.; Carr, E.R.; Eriksen, S.H.; Fernandez-Carril, L.R.; Glavovic, B.; Hilmi, N.J.M.; Ley, D.; Mukerji, R. Climate Resilient Development Pathways. In; Cambridge University Press, 2022 ISBN 0521775728.
2. Reduction, U.N.O. for D.R. Global Assessment Report on Disaster Risk Reduction 2022: Our World at Risk: Transforming Governance for a Resilient Future; UN, 2022; ISBN 9210015053.
3. Fazey, I.; Carmen, E.; Chapin, F.S.; Ross, H.; Rao-Williams, J.; Lyon, C.; Connon, I.L.C.; Searle, B.A.; Knox, K. Community Resilience for a 1.5°C World. Curr. Opin. Environ. Sustain. 2018, 31, 30–40, doi:https://doi.org/10.1016/j.cosust.2017.12.006.
4. Lee, H.; Calvin, K.; Dasgupta, D.; Krinner, G.; Mukherji, A.; Thorne, P.; Trisos, C.; Romero, J.; Aldunce, P.; Barret, K. IPCC, 2023: Climate Change 2023: Synthesis Report, Summary for Policymakers. Contribution of Working Groups i, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, h. Lee and j. Romero (Eds.)]. IPC. 2023.
5. Subiyanto, A.; Boer, R.; Aldrian, E.; Kinseng, R. Climate Resilience: Concepts, Theory and Methods of Measuring. EnvironmentAsia 2020, 13.
6. (IPCC), I.P. on C.C. Summary for Policymakers. In Climate Change 2022 – Impacts, Adaptation and Vulnerability: Working Group II Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; (IPCC), I.P. on C.C., Ed.; Cambridge University Press: Cambridge, 2023; pp. 3–34 ISBN 9781009325837.
7. Lanlan, J.; Sarker, M.N.I.; Ali, I.; Firdaus, R.B.R.; Hossin, M.A. Vulnerability and Resilience in the Context of Natural Hazards: A Critical Conceptual Analysis. Environ. Dev. Sustain. 2024, 26, 19069–19092, doi:10.1007/s10668-023-03440-5.
8. Bao, Z. Evaluating Megacity Resilience to Pandemics: The Case of China. Risk Anal. 2025, n/a-n/a, doi:10.1111/risa.70102.
9. Khan, M.A. Vision of a Sustainable, Smart, and Resilient City BT - Cities and Mega Risks: COVID-19 and Climate Change. In; Khan, M.A., Ed.; Springer International Publishing: Cham, 2022; pp. 295–338 ISBN 978-3-031-14088-4.
10. de Pereira, G.A.; Charvet, E. United Nations Department of Economic and Social Affairs (UN DESA). This meticulously Organ. AZ Guid. arrives a crucial moment our Glob. Purs. Sustain. Dev. It strikes an Excell. Balanc. between Theor. depth Pract. Appl. What sets this B. apart is its Access. clea 164.
11. Patel, N.; Jänicke, B.; Burghardt, R.; Vulova, S.; Otto, F. Assessing Progress in Urban Climate Adaptation: A Review of Indicators for Heat‐ and Water‐Sensitive Urban Development. Clim. Resil. Sustain. 2025, 4, doi:10.1002/cli2.70009.
12. Yessoufou, A.N.-D.; Kumar, S.; Houessionon, P.; Worou, O.N.; Wane, A.; Whitbread, A. Vulnerability and Resilience in the Face of Climate Changes in Senegal’s Drylands: Measurement at the Household Level and Determinant Assessment. Front. Clim. 2024, Volume 6-, doi:10.3389/fclim.2024.1330025.
13. Boer, R.; Dasanto, B.D.; Wijayanti, P.; Jadmiko, S.D.; Rafuddin, A.; Anggraeni, L.; Hidayati, R. Kajian Dampak Perubahan Iklim Terhadap Lingkungan, Sosial, Ekonomi Dan Kesehatan Di Provinsi DKI Jakarta; Bogor, 2022;
14. Dinas Lingkungan Hidup (DLHK) Provinsi DKI Jakarta Pelaksanaan Adaptasi Dalam Rangka Memperkuat Ketahanan Iklim Provinsi DKI Jakarta; Jakarta, 2021;
15. Muta’al, M.R.; Widayanti, P.W. Community-Based City Resilience in Facing Climate Change through the Program Kampung Iklim (Proklim) in the Surakarta. In Proceedings of the E-Proceeding Conference: Indonesia Social Responsibility Award; 2024; Vol. 2.
16. Suárez, M.; Benayas, J.; Justel, A.; Sisto, R.; Montes, C.; Sanz-Casado, E. A Holistic Index-Based Framework to Assess Urban Resilience: Application to the Madrid Region, Spain. Ecol. Indic. 2024, 166, 112293, doi:https://doi.org/10.1016/j.ecolind.2024.112293.
17. Mosisa, G.; Bedadi, B.; Dale, G.; Abate, N.T. Nature-Based Solutions for Urban Climate Resilience: Implementation, Contribution, and Effectiveness. Nature-Based Solut. 2025, 8, 100245, doi:10.1016/j.nbsj.2025.100245.
18. Pellerey, V.; Torabi Moghadam, S.; Lombardi, P. A Systematic Review of Justice Integration to Climate Resilience: Current Trends and Future Directions. Urban Clim. 2025, 59, 102250, doi:https://doi.org/10.1016/j.uclim.2024.102250.
19. Ferrario, F.; Mourato, J.M.; Rodrigues, M.S.; Dias, L.F. Evaluating Nature-Based Solutions as Urban Resilience and Climate Adaptation Tools: A Meta-Analysis of Their Benefits on Heatwaves and Floods. Sci. Total Environ. 2024, 950, 175179, doi:https://doi.org/10.1016/j.scitotenv.2024.175179.
20. Mitu Akter, M.; Hosen, M.I.; Nasher, N.M.R. Assessing Household Resilience to Climate Extremes Using Indicator-Based Index in Hazard-Prone Areas; Evidence from Bangladesh. Environ. Challenges 2024, 15, 100957, doi:https://doi.org/10.1016/j.envc.2024.100957.
21. Hayati, R.; Findayani, A.; Amrullah, M.F. CDRI (Climate Disaster Resilience Index) for Analysis of Semarang City’s Resilience to Climate Change Disasters. IOP Conf. Ser. Earth Environ. Sci. 2025, 1479, 12062, doi:10.1088/1755-1315/1479/1/012062.
22. Wired Jakarta Is Sinking. Now Indonesia Has to Find a New Capital. Available online: https://www.wired.com/story/jakarta-is-sinking/ (accessed on 8 September 2025).
23. Badan Penanggulangan Bencana Daerah (BPBD) Infografis Kejadian Bencana Provinsi DKI Jakarta Tahun 2021; Jakarta, 2021;
24. Iskandar, A.; Makarim, C.A.; Chandra, T.K. STUDI KASUS PENURUNAN MUKA TANAH DAN MUKA AIR TANAH DI JAKARTA PUSAT TAHUN 2010-2022. JMTS J. Mitra Tek. Sipil 2025, 549–558.
25. Shah, K.U.; Dulal, H.B.; Johnson, C.; Baptiste, A. Understanding Livelihood Vulnerability to Climate Change: Applying the Livelihood Vulnerability Index in Trinidad and Tobago. Geoforum 2013, 47, 125–137, doi:https://doi.org/10.1016/j.geoforum.2013.04.004.
26. Asmamaw, M.; Mereta, S.T.; Ambelu, A. Exploring Households’ Resilience to Climate Change-Induced Shocks Using Climate Resilience Index in Dinki Watershed, Central Highlands of Ethiopia. PLoS One 2019, 14, e0219393.
27. Chasco, C.; García, I.; Vicéns, J. Modeling Spatial Variations in Household Disposable Income with Geographically Weighted Regression. 2007.
28. Skondras, N.A.; Tsesmelis, D.E.; Vasilakou, C.G.; Karavitis, C.A. Resilience–Vulnerability Analysis: A Decision-Making Framework for Systems Assessment. Sustainability 2020, 12, 9306.
29. Foroutan, E.; Hu, T.; Zhang, F.; Yu, H. Assessing Heat Vulnerability in Philadelphia Using Geographically Weighted Principal Component Analysis (GWPCA): A Geospatial Big Data-Driven Approach. Int. J. Appl. Earth Obs. Geoinf. 2024, 127, 103653, doi:https://doi.org/10.1016/j.jag.2024.103653.
30. Wu, T. Quantifying Coastal Flood Vulnerability for Climate Adaptation Policy Using Principal Component Analysis. Ecol. Indic. 2021, 129, 108006, doi:https://doi.org/10.1016/j.ecolind.2021.108006.
31. Zardo, L.; Cortinovis, C.; Lucertini, G. Prejudices May Be Wrong: Exploring Spatial Patterns of Vulnerability to Energy Poverty in Italian Metropolitan Areas. Sustainability 2024, 16.
32. Aidoo, E.N.; Appiah, S.K.; Awashie, G.E.; Boateng, A.; Darko, G. Geographically Weighted Principal Component Analysis for Characterising the Spatial Heterogeneity and Connectivity of Soil Heavy Metals in Kumasi, Ghana. Heliyon 2021, 7, e08039, doi:10.1016/j.heliyon.2021.e08039.
33. Palma, M.; De Iaco, S.; Cappello, C.; Distefano, V. Tourism Composite Spatial Indicators through Variography and Geographically Weighted Principal Components Analysis. Ann. Oper. Res. 2024, 342, 1687–1705, doi:10.1007/s10479-023-05329-y.
34. Hubert, M.; Debruyne, M.; Rousseeuw, P.J. Minimum Covariance Determinant and Extensions. WIREs Comput. Stat. 2018, 10, doi:10.1002/wics.1421.
35. Prayoga, I.S.; Ahdika, A. Pemodelan Kerugian Bencana Banjir Akibat Curah Hujan Ekstrem Menggunakan EVT Dan Copula. J. Apl. Stat. Komputasi Stat. 2021, 13, 35–46.
36. Susanto, I.; Handajani, S.S. Pengelompokan Rumah Tangga Di Indonesia Berdasarkan Pendapatan per Kapita Dengan Model Finite Mixture. Media Stat. 2020, 13, 13–24.
37. Badan Perencanaan Pembangunan Daerah (Bappeda) RPJMD DKI Jakarta 2017–2022e; Pemerintah Provinsi DKI Jakarta: Jakarta, 2018;
38. BPS Jakarta, B.P.S.J. DKI Jakarta Dalam Angka 2022; Jakarta, 2022;
39. Green, B. The Method of Successive Intervals: A Sourcebook for Behavioral Scientists. In; 2017; pp. 122–128 ISBN 9781315128948.
40. Rousseeuw, P.J.; Van Zomeren, B.C. Unmasking Multivariate Outliers and Leverage Points. J. Am. Stat. Assoc. 1990, 85, 633–639.
41. Adger, W.N.; Brown, K.; Nelson, D.R.; Berkes, F.; Eakin, H.; Folke, C.; Galvin, K.; Gunderson, L.; Goulden, M.; O’Brien, K. Resilience Implications of Policy Responses to Climate Change. Wiley Interdiscip. Rev. Clim. Chang. 2011, 2, 757–766.
42. Intergovernmental Panel on Climate Change Summary for Policymakers. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; Cambridge, United Kingdom and New York, NY, USA, 2014;
43. Subiyanto, A.; Boer, R.; Aldrian, E.; Perdinan;; Kinseng, R. Ketahanan Nasional Dan Resiliensi Iklim, IPB University, 2019.
44. Jolliffe, I.T.; Cadima, J. Principal Component Analysis: A Review and Recent Developments. Philos. Trans. Ser. A, Math. Phys. Eng. Sci. 2016, 374, 20150202, doi:10.1098/rsta.2015.0202.
45. Boudt, K.; Rousseeuw, P.J.; Vanduffel, S.; Verdonck, T. The Minimum Regularized Covariance Determinant Estimator. Stat. Comput. 2020, 30, 113–128.
46. Maronna, R.A.; Martin, R.D.; Yohai, V.J.; Salibián-Barrera, M. Robust Statistics: Theory and Methods (with R); John Wiley & Sons, 2019; ISBN 1119214688.
47. Jolliffe, I.T. Principal Component Analysis, 2nd Edn New York. NY Springer.[Google Sch. 2002.
48. Gaspersz, V. Teknik Analisis Dalam Penelitian Percobaan 1 Dan 2. Bandung: Tarsito 1992.
49. Matandirotya, N.R.; Filho, W.L.; Mahed, G.; Dinis, M.A.P.; Mathe, P. Local Knowledge of Climate Change Adaptation Strategies from the VhaVenda and BaTonga Communities Living in the Limpopo and Zambezi River Basins, Southern Africa. Inl. Waters 2024, 14, 268–280, doi:10.1080/20442041.2024.2437932.
50. Liu, Y.; Yang, H.; Wang, Y.; Liu, Y.; Hu, X. Neighborhood Matters for Informal Workers’ Employment Resilience under Public Health Crisis: Comparative Evidence from Four Asian Developing Countries. Cities 2025, 165, 106150, doi:https://doi.org/10.1016/j.cities.2025.106150.
51. Zou, H.; Hastie, T.; Tibshirani, R. Sparse Principal Component Analysis. J. Comput. Graph. Stat. 2006, 15, 265–286.
Authors
Copyright (c) 2026 Marta Sundari, Kusman Sadik, Aji Hamim Wigena, Anwar Fitrianto, Rizaldi Boer
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Article Details
How to Cite
