Construction of social vulnerability index in Indonesia using partial least squares structural equation modeling

  • Abstract
  • Keywords
  • References
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  • Abstract

    Social Vulnerability Index (SoVI) is a valuable tool for comparing differences across communities in their overall capacity to prepare for, respond to and recover from natural hazards. Due to its benefits for policymakers and practitioners, SoVI has been widely applied in many countries. Many researchers utilized Exploratory Factor Analysis (EFA) method in SoVI construction. However, the theory says that data from items for EFA have to be normally distributed. In the heart of statistics, not all data follows the Normal distribution. As normality assumption is not a requirement for using Partial Least Squares Structural Equation Modeling (PLS-SEM) method, therefore, this study tries to show the use of PLS-SEM method for SoVI construction. In this study, we utilized reflective formative second order hierarchy model and revealed that many regencies/municipalities with high levels of social vulnerability which located in the Eastern region of Indonesia. These findings highlight the crucial need for strengthening development in the Eastern region of Indonesia.



  • Keywords

    Social Vulnerability; Natural Hazards; PLS-SEM; Indonesia.

  • References

      [1] S. L. Cutter, “Vulnerability to Environmental Hazards.,” Prog. Hum. Geogr., vol. 20, no. 4, pp. 529–539, 1996.

      [2] R. E. Caraka and H. Yasin, Geographically Weighted Regression (GWR) Sebuah Pendekatan Regresi Geografis, 1st ed. MOBIUS GRAHA ILMU, 2017.

      [3] B. Wisner, P. Blaikie, T. Cannon, and I. Davis, At Risk: Natural Hazards, People’s Vulnerability, and Disasters. Routledge, 2004.

      [4] R. E. Caraka and H. Yasin, Spatial Data Panel, 1st ed. Wade Group, 2018.

      [5] C. S. Holling, “Resilience and Stability of Ecological Systems,” Annu. Rev. Ecol. Syst., vol. 4, no. 1, pp. 1–23, 1973.

      [6] R. E. Caraka, S. A. Bakar, M. Tahmid, H. Yasin, and I. D. Kurniawan, “Neurocomputing Fundamental Climate Analysis,” Telkomnika, vol. 17, no. 4, 2019.

      [7] R. E. Caraka, Supari, and M. Tahmid, “Copula-Based Model for Rainfall and El- Niño in Banyuwangi Indonesia,” J. Phys. Conf. Ser., vol. 1008, no. 1, 2018.

      [8] E. Tate, “Uncertainty Analysis for a Social Vulnerability Index,” Ann. Assoc. Am. Geogr., vol. 103, no. 3, pp. 526–543, 2013.

      [9] B. E. Flanagan, E. W. Gregory, E. J. Hallisey, J. L. Heitgerd, and B. Lewis, “A social vulnerability index for disaster manage-ment.,” J. Homel. Secur. Emerg. Manag., vol. 8, no. 1, 2011.

      [10] P. Utami, “Measuring Social Vulnerability in Volcanic Hazards: The Case Study of Merapi Volcano, Indonesia,” University of Bristol, 2008.

      [11] D. R. Hizbaron, M. Baiquni, J. Sartohadi, R. Rijanta, and M. Coy, “Assessing social vulnerability to seismic hazard through spatial multi-criteria evaluation in Bantul District,” in Tropentag, 2011.

      [12] S. L. Cutter, B. J. Boruff, and W. L. Shirley, “Social vulnerability to environmental hazards.,” Soc. Sci. Q., vol. 84, no. 2, pp. 242–261, 2003.

      [13] S. A. H. Sagala, “System Analysis of Social Resilience against Volcanic Risks Case Studies of Merapi, Indonesia and Mt. Sakurajima,” Kyoto University, 2009.

      [14] J. Rizal, S. Akbar, F. Faisal, and Z. M. Mayasari, “Kajian Persepsi Masyarakat Pesisir Terhadap Bencana Tsunami Bagi Masyarakat Kota Bengkulu.,” Bengkulu, 2014.

      [15] H. M. Diamantopoulos, A. Winklhofer, “Index construction with formative indicators: An alternative to scaling development,” J. Mark. Res., vol. 28, no. 2, 2011.

      [16] S. Spielman, “Cluster Analysis and PCA,” 2015. .

      [17] W. . Adger, “Social Vulnerability to Climate Change and Extremes in Coastal Vietnam,” World Dev., vol. 2, no. 27, pp. 249–269, 1999.

      [18] J. Birkmann, Measuring Vulnerability to Promote Disaster-Resilient Societies: Conceptual Framework and Definitions. New York: United Nations University Press, 2006.

      [19] W. Chen, S. L. Cutter, C. T. Emrich, and P. Shi, “Measuring social vulnerability to natural hazards in the Yangtze River Delta region, China,” Int. J. Disaster Risk Sci., vol. 4, no. 4, pp. 169–181, 2013.

      [20] S. L. Cutter and C. Finch, “Temporal and spatial changes in social vulnerability to natural hazards,” Proc. Natl. Acad. Sci., vol. 105, no. 7, pp. 2301–2306, 2008.

      [21] R. E. Caraka and S. Sugiarto, “Path Analysis Terhadap Faktor-Faktor Yang Mempengaruhi Prestasi Siswa,” J. Akuntabilitas Manaj. Pendidik., vol. 5, no. 2, pp. 212–219, 2017.

      [22] K. A. Bollen, Structural Equations with Latent Variables. New York: Wiley, 1989.

      [23] R. E. Caraka et al., “Ecological Show Cave and Wild Cave: Negative Binomial Gllvm’s Arthropod Community Modelling,” Procedia Comput. Sci., vol. 135, pp. 377–384, 2018.

      [24] I. D. Kurniawan, C. Rahmadi, R. E. Caraka, and T. A. Ardi, “Short Communication: Cave-dwelling Arthropod community of Semedi Show Cave in Gunungsewu Karst Area, Pacitan, East Java, Indonesia,” Biodiversitas, vol. 19, no. 3, pp. 857–866, 2018.

      [25] C. M. Ringle, M. Sarstedt, and D. Straub, “A critical look at the use of PLS-SEM in MIS Quarterly.,” 2012.

      [26] I. Ghozali, “Moderated Structural Equation Modeling,” in Model persamaan struktural. Konsep dan aplikasi dengan program AMOS 19.0, 2011, pp. 180–183.

      [27] J. F. Hair, C. M. Ringle, and M. Sarstedt, “PLS-SEM: Indeed a silver bullet,” J. Mark. Theory Pract., vol. 19, no. 2, 2011.

      [28] C. E. Werts, R. L. Linn, and K. G. Jöreskog, “Intraclass Reliability Estimates: Testing Structural Assumptions,” Educ. Psychol. Meas., vol. 34, no. 1, pp. 25–33, 1974.

      [29] T. H. Siagian, P. Purhadi, S. Suhartono, and H. Ritonga, “Social vulnerability to natural hazards in Indonesia: driving factors and policy implications.,” Nat. Hazard, vol. 70, no. 2, pp. 1603–1617, 2014.

      [30] D. Lowe, K. L. Ebi, and B. Forsberg, “Factors increasing vulnerability to health effects before, during and after floods,” Int. J. Environ. Res. Public Health, vol. 10, no. 12, pp. 7015–7067, 2013.

      [31] K. K. K. Wong, “Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS,” Mark. Bull., vol. 24, no. 15.

      [32] C. M. Ringle, S. Wende, and A. Will, “Smart PLS,” SmartPLS GmbH. 2015.

      [33] E. U. N. Sholiha and M. Salamah, “Structural Equation Modeling-Partial Least Square untuk Pemodelan Derajat Kesehatan Kabupaten/Kota di Jawa Timur,” Sains dan Seni, vol. 4, no. 2, 2016.

      [34] BNPB, “Potensi dan Ancaman Bencana,” BNPB, 2017. .

      [35] E. Joakim, “Resilient disaster recovery: A critical assessment of the 2006 Yogyakarta,” University of Waterloo, 2013.

      [36] T. Kidokoro, J. Okata, S. Matsumura, and N. Shima, Vulnerable Cities: Realities, Innovations, and Strategies. Elsevier Inc., 2008.

      [37] R. Djalante and F. Thomalla, “Disaster risk reduction and climate change adaptation in Indonesia,” Int. J. Disaster Resil. Built Environ., vol. 3, no. 2, pp. 166–180, 2012.




Article ID: 24648
DOI: 10.14419/ijet.v7i4.24648

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