Proceedings of the 7th International Conference on Social and Political Sciences (ICoSaPS 2022)

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Risk Identification and Disaster Management at The Village Level: Principal Component Analysis Approach

Authors
Muhammad Fazri1, *, A. Risdawati AP1, Dian Karinawati Imron2, Marthella Rivera Roidatua3, Adelia Oktarina1, Febrina Elia Nababan1, Cita Pertiwi1
1Directorate of Economy, Employment, and Regional Development Policy, National Research and Innovation Agency, Jakarta Pusat, Indonesia
2Research Center for Social Welfare, Village and Connectivity, National Research and Innovation Agency, Jakarta Pusat, Indonesia
3Directorate of Human Development, Demography, and Culture Policy, National Research and Innovation Agency, Jakarta Pusat, Indonesia
*Corresponding author. Email: muhammad.fazri@brin.go.id
Corresponding Author
Muhammad Fazri
Available Online 30 December 2022.
DOI
10.2991/978-2-494069-77-0_38How to use a DOI?
Keywords
Village; Natural Disaster; Principal Component Analysis
Abstract

Indonesia is one of the countries with a fairly high level of disaster proneness. Based on the results of the 2020 Indonesia Disaster Risk Index (IRBI) published by BNPB, out of the number of 514 districts, there are 237 districts with high risk, while 277 districts with moderate risk. The high number of Indonesian disasters can also be seen from the number of disaster events. So far, disaster identification is limited to the district. The disaster risk index also has an area only up to the district. Whereas each village has different location characteristics so that disaster management cannot be equated. Therefore, this study tried to look at the risk of disaster-prone at the village level. The data used is the 2020 Village Potential data by looking at the number of disaster events and also the number of fatalities in each village from 2019 to March 2020. The method used an analysis description approach through data exploration. In addition, using quantitative methods principal analysis components to create an Index that will classify a village whether prone to disaster or not. The results of identification are still many villages that are prone to disaster. From these results, it is mapped that there are 1,158 villages that have high risk, 27,061 medium risk and 46,446 villages are in low risk. This means that about 38 thousand still have a risk of being prone to disasters.

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 7th International Conference on Social and Political Sciences (ICoSaPS 2022)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
30 December 2022
ISBN
978-2-494069-77-0
ISSN
2352-5398
DOI
10.2991/978-2-494069-77-0_38How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Muhammad Fazri
AU  - A. Risdawati AP
AU  - Dian Karinawati Imron
AU  - Marthella Rivera Roidatua
AU  - Adelia Oktarina
AU  - Febrina Elia Nababan
AU  - Cita Pertiwi
PY  - 2022
DA  - 2022/12/30
TI  - Risk Identification and Disaster Management at The Village Level: Principal Component Analysis Approach
BT  - Proceedings of the 7th International Conference on Social and Political Sciences (ICoSaPS 2022)
PB  - Atlantis Press
SP  - 275
EP  - 282
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-494069-77-0_38
DO  - 10.2991/978-2-494069-77-0_38
ID  - Fazri2022
ER  -