Analysis of Factors Influencing Poverty in South Sumatra Using the Poisson Regression Model

Authors

  • Jolius Saut Mangaraja Manik Universitas Sriwijaya
  • Fitri Maya Puspita Universitas Sriwijaya
  • Sisca Octarina Universitas Sriwijaya

DOI:

https://doi.org/10.32493/sm.v8i1.54763

Keywords:

Poisson Regression, Poverty, South Sumatra

Abstract

Poverty remains a key development issue for the government, including in South Sumatra Province. This study aims to analyze the factors influencing poverty levels at the district/city level using a Poisson regression model. The independent variables used include the open unemployment rate, education level, Gross Regional Domestic Product (GRDP) per capita, and the percentage of the population working in the informal sector. The data used are secondary data obtained from the Central Statistics Agency (BPS) for the most recent available year. The analysis shows that several variables significantly influence the number of poor people in South Sumatra, where increasing open unemployment and a high proportion of informal workers tend to increase the number of poor people. Conversely, increasing education and GRDP per capita contribute to reducing poverty levels. The Poisson regression model proved appropriate for modeling the number of incidents (count) data in this study. These findings are expected to provide input for local governments in formulating more targeted poverty alleviation policies.

References

1. Selatan BPSSS. 8 Mei 2024. 2024 [cited 2025 Nov 15]. p. 1 No Title. Available from: https://sumsel.bps.go.id/id/statistics-table/2/MjYyIzI=/undefined

2. Kemiskinan T, Provinsi DI. Analisis faktor-faktor yang mempengaruhi tingkat kemiskinan di provinsi banten. 2020;1(4):259–74.

3. Tisniwati B, Daerah P, Tenggara N. Analisis faktor-faktor yang mempengaruhi tingkat kemiskinan di indonesia.

4. Jawa DI, Tahun T. MEMPENGARUHI KEMISKINAN. 2010;

5. Ekonomika JS, Utami FP, Lubis I, Utara US. ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KEMISKINAN. 2022;6(1):1–9.

6. Manoppo JJE, Engka DSM, Tumangkeng SYL, Pembangunan JE, Ekonomi F, Ratulangi US. Analisis faktor-faktor yang mempengaruhi kemiskinan di kota manado. 2018;18(02):216–25.

7. Priseptian L, Primandhana WP. Analisis faktor-faktor yang mempengaruhi kemiskinan. 2022;24(1):45–53.

8. No Title. 2023;3(3):677–97.

9. glmbook.pdf.

10. Sumberbrantas DID. No Title. 2022;4(2):106–17.

11. No Title. 2016;

12. Matematika J, Andalas U, Unand K, Manis L, Poisson R. Analisis faktor risiko angka kematian ibu dengan pendekatan regresi poisson. 2014;VII(2):126–31.

13. Timur J, Statistika J, Matematika F, Alam P. Analisis Faktor Risiko Kematian Ibu dan Kematian. 2015;4(2):2–7.

14. Yang AF faktor, Stunting M, Di B, Gorontalo K, Regresi M. Jambura journal of probability and statistics. 2021;2.

15. Bayi K, Jawa DI, Menggunakan T, Prahutama A, Mukid MA. Analisis faktor-faktor yang mempengaruhi angka kematian bayi di jawa tengah menggunakan regresi generalized poisson dan binomial negatif 1. 2017;5(2).

16. Faktor-faktor A, Jumlah M, Maluku P, Poisson R. Jurnal EurekaMatika. 2021;9(2):151–8.

17. Agresti A. of Linear and Generalized Linear Models Alan Agresti.

18. Greene WH. Econometric Analysis EIGHTH EDITION.

Downloads

Published

2026-04-30

How to Cite

Manik, J. S. M., Fitri Maya Puspita, & Sisca Octarina. (2026). Analysis of Factors Influencing Poverty in South Sumatra Using the Poisson Regression Model. STATMAT: Jurnal Statistika Dan Matematika, 8(1), 87–92. https://doi.org/10.32493/sm.v8i1.54763

Issue

Section

Articles

Similar Articles

1 2 > >> 

You may also start an advanced similarity search for this article.