Analisis Kemiskinan di Sulawesi Selatan dengan Regresi Nonparametrik Berbasis B-Spline

Rafli Setiawan Nasir, Muhammad Agung Wahid, Domi Rico Arung Padang, Anna Islamiyati, Raupong Raupong

Abstract

Poverty is one of the problems faced by Indonesia, including in the province of South Sulawesi. This study aims to identify and understand the complex relationship between factors influencing poverty in South Sulawesi using nonparametric B-Spline regression. The data used are secondary data obtained from the publication of the Central Statistics Agency in the form of Data and Information on Poverty in Districts/Cities in Indonesia in 2022. The variables used are the percentage of poor people as the dependent variable, and the percentage of per capita expenditure on food, poverty depth index, and poverty severity index as independent variables. The best B-Spline model was obtained using order 2 for each independent variable, and one knot for each independent variable at a certain point. This model provides a Generalized Cross-Validation (GCV) value of 10.199728. The results of the analysis show that the measure of the goodness of the model obtained or R2 which means that the percentage of per capita expenditure on food, poverty depth index, and poverty severity index greatly influences the percentage of poor people in South Sulawesi. The relationship between the independent variables and the dependent variables is non-linear and varies. The B-Spline model can produce an accurate and flexible picture of the relationship pattern and variability in poverty data in South Sulawesi. This study can provide in-depth insights and recommendations for the government in the form of poverty alleviation policies based on local data and non-linear analysis, by targeting specific interventions according to the unique conditions of each region in South Sulawesi to increase the effectiveness of poverty alleviation.

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References

V. D. Ferezagia, ”Analisis tingkat kemiskinan di Indonesia,” Jurnal Sosial Humaniora Terapan, vol. 1, no. 1, pp. 12–31, 2018.

Badan Pusat Statistik, ”Profil Kemiskinan di Indonesia Maret,” 2023.

M. R. Padambo, G. M. V. Kawung, & W. F. I. Rompas, “Analisis pengaruh pertumbuhan ekonomi inflasi dan indeks pebangunan manusia terhadap kemiskinan di Provinsi Sulawesi Selatan,” Jurnal Berkala Ilmiah Efisiensi, vol. 21, no. 5, pp. 15–27, 2021.

Badan Pusat Statistik, ”Profil Kemiskinan di Sulawesi Selatan September 2022,” 2022.

D. Ariesta, N. Gusriani, & K. Parmikanti, ”Estimasi parameter model regresi nonparametrik b-spline pada angka kematian maternal.” Jurnal Matematika UNAND, vol. 10, no. 3, pp. 342–354, 2021.

S. Wulandary, & D. I. Purnama, ”Perbandingan regresi nonparametrik karnel dan b-splines pada pemodelan rata-rata lama sekolah dan pengeluaran perkapita di Indonesia,” Jambura Journal of Probability and Statistics, vol. 1, no. 2, pp. 89–97, 2020. https://doi.org/10.34312/jjps.v1i2.7501

R. Y. Putra, A. Roza, & H. M. Putri, ”Pendekatan multivariate regression splines untuk memodelkan tingkat kemiskinan di Provinsi Sumatera Barat,” MAp Journal, vol. 3, no. 2, pp. 92-98, 2021.

M. Rosalina, S. Martha, & N. I. Intisari, ”Pemodelan regresi nonparametrik birespon spline pada persentase penduduk miskin dan indeks kedalaman kemiskinan,” Buletin Ilmiah Math. Stat dan Terapannya (Bimaster), vol. 12, no. 1, pp. 69–78, 2023.

A. Mahmudah, S. S. Handajani, & H. Pratiwi, ”Analisis regresi nonparametrik b-spline pemodelan jumlah penduduk miskin di Provinsi Papua menggunakan regresi nonparametrik b-spline,” Seminar Nasional Pendidikan Matematika dan Matematika, vol. 8, 2023.

R. Raupong, ”Model b-spline dalam menaksir kurva regresi nonparametrik,” Jurnal Matematika, Statistika, & Komputasi, vol. 6, no. 1, pp. 30-35, 2009. http://journal.unhas.ac.id/index.php/jmsk

Direktorat Statistik Ketahanan Sosial, ”Data dan Informasi Kemiskinan Kabupaten dan Kota di Indonesia,” 2022.

S. P. Wicaksono & M. Hutajulu, “Analisis faktor-faktor yang mempengaruhi kemiskinan di Indonesia tahun 1999-2020,” Bisnis Dan Keuangan Transekonomika, vol. 3, no. 2, pp. 379-390, 2023. https://transpublika.co.id/ojs/index.php/Transekonomika

N. I. Purnama, ”Analisis pengaruh pertumbuhan ekonomi terhadap tingkat kemiskinan di Sumatera Utara,” Jurnal Ekonomikawan, vol. 17, no. 1, pp. 62–70, 2017.

E. D. Igustin & I. N. Budiantara, ”Pemodelan faktor-faktor yang mempengaruhi total fertility rate di indonesia menggunakan regresi nonparametrik spline truncated,” Jurnal Sains Dan Seni ITS, vol. 9, no. 2, pp. 178–185. 2020.

A. R. Devi, M. A. Mukid, & H. Yasin, “Analisis inflasi Kota Semarang menggunakan metode regresi non parametrik b-spline,” Jurnal Gaussian, vol. 3, no. 2, pp. 193–202, 2014. http://ejournal-s1.undip.ac.id/index.php/gaussian

I. G. A. M. V. Dewi, I. G. A. M. Srinadi, & M. Susilawati, “Pemodelan kasus pneumonia pada balita di Provinsi Bali menggunakan metode regresi nonparametrik b-spline,” E-Jurnal Matematika, vol. 9, no. 3, pp. 197, 2020. https://doi.org/10.24843/mtk.2020.v09.i03.p299

A. S. Rahmawati, D. Ispriyanti, & B. Warsito, ”Pemodelan kasus kemiskinan di Jawa Tengah menggunakan regresi nonparametrik metode b-spline,” Jurnal Gaussian, vol. 6, no. 1, pp. 11–20, 2017. http://ejournal-s1.undip.ac.id/index.php/gaussian

N. P. Matahelumual & R. Kawet, ”Pengaruh budaya organisasi dan komitmen organisasi terhadap produktivitas kerja pegawai pada Biro Organisasi Sekretariat Daerah Provinsi Sulawesi Utara,” Jurnal EMBA, vol. 7, no. 1, pp. 641–650, 2019.

DOI: https://doi.org/10.13057/ijas.v7i1.80716

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