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Submitted
March 12, 2021
Accepted
December 29, 2021
Published
February 14, 2022
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Abstract

Poverty has always become a problem in an economic system, started from its detection to its eradication. So as happened in South OKU Regency, even its poverty level was the third lowest in the Province, but the human resources and economic system was not good enough. This led to a tendency that people in South OKU Regency just lived “as enough”, they were living above the poverty line, but so close to it. In the long term, this situation will become a serious problem. The poverty calculation method used by BPS Statistics Indonesia has limitedness as it does not include the aspects of social-economic and cannot calculate someone’s possibility to get into or out of poverty. This research aims to calculate the possibility of someone to become poor in the future and establish the solution to prevent it happens in South OKU Regency. With the vulnerability of expected poverty (VEP) analysis, it was known that there are 19,77 percent or 71.182 populations in South OKU Regency that are vulnerable to poverty. Based on the Decision Tree model created, the variables of per capita expenditure, asset ownership, and the number of household members can be used to classify households in South OKU regency by their poverty status. By detecting vulnerable to poverty households and helping them to sustain their welfare, will prevents the increase of the number of the poor in the future.

Keywords

poverty vulnerability to poverty VEP decision tree

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Author Biography

Rio Triwahyu Saputra, Badan Pusat Statistik

Statistician at BPS Statistics OKU Selatan Regency
How to Cite
Saputra, R. T. (2022). Quantifying Vulnerability to Poverty in the Future in the Local Region. Jurnal Ekonomi Pembangunan, 19(2), 207–222. https://doi.org/10.29259/jep.v19i2.13926
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References

  1. Alwang, J., Siegel. P. B., & Jorgensen. S.L. (2001). Vulnerability: A view from different disciplines. Social Protection Discussion Paper 23304, The World Bank.
  2. Adnyani, A. W., & Sugiharti, L. (2019). Profil dan determinan kerentanan kemiskinan rumah tangga. Jurnal Ilmu Ekonomi & Sosial, 10(2), 100-118.
  3. https://doi.org/10.35724/jies.v10i2.2412
  4. BPS. (2019). Penghitungan dan Analisis Kemiskinan Makro Indonesia. Jakarta: Badan Pusat Statistik
  5. BPS. (2020). Poverty and inequality. Retrieved from https://www.bps.go.id/subject/23/kemiskinan-dan-ketimpangan.html
  6. BPS. (2021). Kabupaten Ogan Komering Ulu Selatan dalam Angka 2021. Muaradua: Badan Pusat Statistik Kabupaten Ogan Komering Ulu Selatan
  7. BPS. (2021). Provinsi Sumatera Selatan dalam Angka 2021. Palembang: Badan Pusat Statistik Provinsi Sumatera Selatan
  8. Chaudhuri, S., Jalan,J., & Suryahadi, A. (2002). Assessing household vulnerability to poverty from cross-sectional data: A methodology and estimates from Indonesia. Department Of Economics Discussion Paper Series. New York: Columbia University. https://doi.org/10.7916/D85149GF
  9. Gujarati, D. N. (2003). Basic econometric fourth edition. New York: McGraw-Hill
  10. Han, J., & Kember, M., (2006). Data mining: Concepts and techniques second edition. San Francisco: Morgan Kaufmann Publishers. University Of Iliois At Urbana-Champaign
  11. Holzmann, R., & S. Jorgensen. (1999). Social protection as social risk management: Conceptual underpinnings for social protection sector strategy paper. Social Protection Discussion Paper. Journal Of International Development. 11(7), 1005-1027. https://doi.org/10.1002/(SICI)1099-1328(199911/12)11:7<1005:AID-JID643>3.0.CO;2-B
  12. Jha, R., & Dang, T. (2008). Vulnerability to poverty in select Central Asian Countries. The European Journal of Comparative Economics. 6(1), 17-50.
  13. Kumala, A.Z., Agustini, H. N., & Rais. (2013). Dinamika kemiskinan dan pengukuran kerentanan kemiskinan dalam upaya melindungi anak-anak dari dampak kemiskinan (studi kasus pada rumah tangga di pulau jawa tahun 2008-2010). Child Poverty and Social Protection Conference. Jakarta, Indonesia.
  14. Larose, D.T. (2005). Discovering knowledge in data: An introduction to data mining. New Jersey: John Wiley & Sons
  15. Mabughi, N., & Selim, T. (2006). Poverty as Social Deprivation: A Survey. Review of Social Economy, 64(2), 181–204. http://www.jstor.org/stable/29770366
  16. Marwa, T., Bashir, A., Thamrin, K. M. H., Azwardi, A., & Asngari, I. (2020). The Socio-Economic Variables Influencing Household Consumption in the Rural Farmers Level. Humanities & Social Sciences Reviews, 8(2), 112-122.
  17. Mowafi, M., & Khawaja, M. (2005). Poverty. Journal of Epidemiology & Community Health, 59 (4), 260-264. http://dx.doi.org/10.1136/jech.2004.022822
  18. Purmini, P., & Rambe, R. A. (2021). Labor and Government Policies on Poverty Reduction in Sumatera Island, Indonesia. Jurnal Ekonomi Pembangunan, 19(1), 61–74. https://doi.org/10.29259/jep.v19i1.13775
  19. Rahman, A., & Wulansari, I. Y. (2018). Kerentanan Kemiskinan: Pendugaan, Pemetaan, Penciri, dan Rekomendasi Kebijkanan pada Data Sampel Kecil. Jurnal Aplikasi Statistika & Komputasi Statistik, 10(2), 55–64. https://doi.org/10.34123/jurnalasks.v10i2.77
  20. Satterthwaite, D., McGranahan, G., & Tacoli, C. (2010). Urbanization and its implications for food and farming. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 365(1554), 2809–2820. https://doi.org/10.1098/rstb.2010.0136
  21. Suhel, S., Asngari, I., Mardalena, M., Hidayat, A., & Bashir, A. (2021). Identifying factors influencing the low-income community in urban slum settlements in South Sumatera, Indonesia. Jurnal Perspektif Pembiayaan dan Pembangunan Daerah, 9(1), 9 - 18. https://doi.org/10.22437/ppd.v9i1.10385
  22. Schweiger, G. (2015). Recognition and poverty. Eidos, (22), 148-168. https://doi.org/10.14482/eidos.22.5095
  23. STIS. (2017). Laporan modul ekonomi 2, studi kemiskinan dan ketimpangan kemiskinan dengan small area estimation: kerentanan kemiskinan di Provinsi Kepulauan Bangka Belitung. Jakarta: Politeknik Statistika STIS
  24. Witten, I. H., Frank, E., & Hall, M. A. (2011). Data mining: Practical machine learning tools and techniques third edition. Burlington: Morgan Kaufmann Publishers