Implementation of The Logistic Regression Algorithm to Analyze Poverty Factors in Aceh Province

Authors

  • Mursyidah Mursyidah Department of Informatics, Faculty of Engineering, Universitas Malikussaleh, Aceh, Indonesia
  • Rozzi Kesuma Dinata Department of Informatics, Faculty of Engineering, Universitas Malikussaleh, Aceh, Indonesia
  • Zara Yunizar Department of Informatics, Faculty of Engineering, Universitas Malikussaleh, Aceh, Indonesia

DOI:

https://doi.org/10.30871/jaic.v9i4.9715

Keywords:

Aceh, Logistic regression, Multicollinearity, Poverty, Prediction

Abstract

Aceh Province continues to face a high poverty rate despite its abundant natural resources. This study aims to analyze the factors influencing poverty status in Aceh Province by applying a binary logistic regression algorithm. The research specifically focuses on an inferential analytical approach to reveal significant relationships among socioeconomic variables. Secondary data were obtained from the Aceh Provincial Statistics Agency (Badan Pusat Statistik/BPS) for the period 2019–2023. Inferential analysis was conducted using the entire dataset through the statsmodels library to identify variables that are statistically significant to poverty status. In addition, a classification approach was implemented using scikit-learn, with a data split between training data (2019–2022) and testing data (2023), yielding an accuracy of 0.70, precision of 0.81, recall of 0.70, F1-score of 0.66, and AUC of 0.69. These findings provide empirical evidence that improving access to education and equitable infrastructure development in densely populated areas can serve as effective policy focuses in efforts to alleviate poverty in Aceh Province.

Downloads

Download data is not yet available.

Author Biographies

Rozzi Kesuma Dinata, Department of Informatics, Faculty of Engineering, Universitas Malikussaleh, Aceh, Indonesia

Lecturer, Department of Informatics, Faculty of Engineering, Universitas Malikussaleh.

Zara Yunizar, Department of Informatics, Faculty of Engineering, Universitas Malikussaleh, Aceh, Indonesia

Lecturer, Department of Informatics, Faculty of Engineering, Universitas Malikussaleh.

References

[1] U. Hasanah and L. Safrina, “Determinan tingkat kemiskinan di Provinsi Aceh,” I-Finance: A Research Journal on Islamic Finance, vol. 10, no. 1, pp. 138–154, 2024.

[2] E. Salong, M. Bugis, I. T. Matitaputty, and F. Ramly, “The effect of education, health and per capita income on poverty rate in Maluku Province,” Daengku: Journal of Humanities and Social Sciences Innovation, vol. 4, no. 3, pp. 457–464, 2024, doi: 10.35877/454RI.daengku2567.

[3] I. Azis, I. M. Sumertajaya, S. S. Purwaningsih, and S. S. Tjahjawati, “Penentuan faktor kemiskinan Indonesia menggunakan regresi logistik,” Journal of Mathematics, Computations, and Statistics, vol. 6, no. 1, pp. 61–65, 2023.

[4] A. N. Aini, A. U. O. Ashar, T. I. Lestari, I. M. Nur, and R. Wasono, “Pemodelan tingkat kemiskinan di Papua Barat dengan pendekatan binary logistic regression,” Square: Journal of Mathematics and Mathematics Education, vol. 5, no. 2, pp. 113–120, 2023, doi: 10.21580/square.2023.5.2.17169.

[5] I. A. Doherty and M. E. Wells, “Sleep disparities in the United States: Comparison of logistic and linear regression with stratification by race,” Sleep Epidemiology, vol. 5, Art. no. 100106, 2025, doi: 10.1016/j.sleepe.2025.100106.

[6] V. Ratnasari, Purhadi, M. Rifada, and A. T. R. Dani, “Explore poverty with statistical modeling: The bivariate polynomial binary logit regression (BPBLR),” MethodsX, vol. 14, Art. no. 103099, 2025, doi: 10.1016/j.mex.2024.103099.

[7] D. F. Silaban, F. A. Simanjuntak, I. O. Lumbantobing, R. Napitupulu, and Arnita, “Analisis faktor-faktor yang mempengaruhi peluang penerimaan pelamaran kerja menggunakan metode regresi logistik biner,” Trigonometri: Jurnal Matematika dan Ilmu Pengetahuan Alam, vol. 5, no. 1, pp. 1–10, Dec. 2024, doi: 10.8734/trigo.v1i2.365.

[8] B. W. Kusuma and A. S. Widawati, “Analisis determinasi tingkat kemiskinan di Provinsi Aceh,” JIMEA: Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi), vol. 8, no. 1, pp. 2211–2228, Apr. 2024.

[9] I. Hartika, “Analisis kemiskinan di Provinsi Aceh,” Brilliant: Journal of Islamic Economics and Finance, vol. 2, no. 1, pp. 14–29, Jun. 2024.

[10] W. S. Nainggolan, Z. M. Pulungan, A. Faradhila, and G. T. Sinaga, “Analisis klasifikasi dan regresi logistik biner untuk menilai faktor-faktor yang memengaruhi kepuasan pelanggan,” Trigonometri: Jurnal Matematika dan Ilmu Pengetahuan Alam, vol. 5, no. 2, pp. 50–60, Dec. 2024, doi: 10.8734/trigo.v1i2.365.

[11] R. K. Dinata, Fajriana, Z. Zulfa, and N. Hasdyna, “Klasifikasi Sekolah Menengah Pertama/sederajat wilayah Bireuen menggunakan algoritma K-Nearest Neighbors berbasis web,” CESS (Journal of Computer Engineering System and Science), vol. 5, no. 1, pp. 33–37, Jan. 2020.

[12] M. Maulita and N. Nurdin, “Pendekatan data mining untuk analisa curah hujan menggunakan metode regresi linear berganda (studi kasus: Kabupaten Aceh Utara),” IDEALIS: Indonesian Journal of Information System, vol. 6, no. 2, pp. 99–106, Jul. 2023.

[13] D. R. Sahputra et al., “Model regresi logistik pada indeks kedalaman kemiskinan di Provinsi Jawa Timur tahun 2021,” in Prosiding Seminar Nasional Matematika, Statistika, dan Aplikasinya, Terbitan III, Samarinda, Indonesia, pp. 1–9, Aug. 2023.

[14] A. I. Nurrizqi, Erfiani, Indahwati, A. Fitrianto, and R. Amelia, “Pemodelan regresi logistik berbasis backward elimination untuk mengetahui faktor yang memengaruhi tingkat kemiskinan di Indonesia tahun 2021,” Jurnal Statistika dan Aplikasinya, vol. 6, no. 2, pp. 160–169, Dec. 2022.

[15] N. P. N. Hendayanti and M. Nurhidayati, “Regresi logistik biner dalam penentuan ketepatan klasifikasi tingkat kedalaman kemiskinan provinsi-provinsi di Indonesia,” Sainstek: Jurnal Sains dan Teknologi, vol. 12, no. 2, pp. 63–70, Dec. 2020.

Downloads

Published

2025-08-05

How to Cite

[1]
M. Mursyidah, R. Kesuma Dinata, and Z. Yunizar, “Implementation of The Logistic Regression Algorithm to Analyze Poverty Factors in Aceh Province”, JAIC, vol. 9, no. 4, pp. 1451–1462, Aug. 2025.

Issue

Vol. 9 No. 4 (2025): August 2025

Section

Articles

License

Copyright (c) 2025 Mursyidah Mursyidah, Rozzi Kesuma Dinata, Zara Yunizar

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 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 (Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) ) 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).