Nonparametric Model For Poverty Data: The Effect of Internal Factors Using Multi-Predictor Spline Regression in Indonesia
DOI:
https://doi.org/10.24252/msa.v13i2.60319Keywords:
Poverty, GCV, Nonparametrik, SplineAbstract
Poverty, as a multidimensional issue affecting national welfare and development, is the main focus of this research. This study investigates the impact of demographic and educational factors on the percentage of the poor population in Indonesia using a nonparametric Spline regression approach. The variables studied include the average population growth rate, the availability of schools in villages, and school enrollment rates. The best model, selected based on the lowest Generalized Cross Validation (GCV) value (0.204) and a high coefficient of determination (94.67%) is a nonparametric Spline regression model with an optimal combination of knot points. The analysis shows that all three predictor variables significantly influence the poverty rate. The model also meets standard statistical assumptions. These findings highlight the vital role of education and demographic factors in addressing poverty, thus strengthening education and controlling population growth should be a priority in poverty alleviation policies in Indonesia.
References
Ruliana, I. N. Budiantara, B. W. Otok, and W. Wibowo, “Parameter estimation of nonlinear structural model sem using spline approach,” Applied Mathematical Sciences, vol. 9, no. 149, pp. 7439–7451, 2015.
D. Amaliah, “Pengaruh partisipasi pendidikan terhadap persentase penduduk miskin,” Faktor: Jurnal Ilmiah Kependidikan, vol. 2, no. 3, 2016.
A. Hadi, “Pengaruh rata-rata lama sekolah kabupaten/kota terhadap persentase penduduk miskin kabupaten/kota di provinsi jawa timur tahun 2017,” Media Trend, vol. 14, no. 2, pp. 148–153, 2019.
D. Desmawan, F. Fitrianingsih, N. A. Drajat, N. W. Diani, and S. Marlina, “Pengaruh jumlah penduduk terhadap pertumbuhan ekonomi di kabupaten tangerang tahun 2019-2020,” Jurnal Penelitian Ekonomi Manajemen dan Bisnis, vol. 2, no. 2, pp. 150–157, 2023.
A. Azulaidin, “Pengaruh pertumbuhan penduduk terhadap pertumbuhan ekonomi,” Juripol (Jurnal Institusi Politeknik Ganesha Medan), vol. 4, no. 1, pp. 30–34, 2021.
J. Setiawan, R. Jaenudin, and S. Fatimah, “Pengaruh biaya pendidikan dan fasilitas pendidikan terhadap hasil belajar mata pelajaran ekonomi peserta didik sma bukit asam tanjung enim,” Jurnal Profit, vol. 2, no. 1, pp. 14–27, 2015.
R. M. Shari and J. Abubakar, “Pengaruh pertumbuhan penduduk, angka partisipasi sekolah dan tingkat partisipasi angkatan kerja terhadap pertumbuhan ekonomi pada 5 provinsi di indonesia,” Jurnal Ekonomi Regional Unimal, vol. 5, no. 2, pp. 20–32, 2022.
R. Hidayat, I. N. Budiantara, B. W. Otok, and V. Ratnasari, “The regression curve estimation by using mixed smoothing spline and kernel (mss-k) model,” Communications in Statistics-Theory and Methods, vol. 50, no. 17, pp. 3942–3953, 2021.
R. Hidayat, M. Ilyas, and Y. Yuliani, “Spline model in the case of cervical cancer patient resilience,” Trends in Sciences,
vol. 20, no. 8, pp. 6170–6170, 2023.
N. Syamsualam and R. Hidayat, “Application of truncated spline nonparametric regression in modeling traffic accident rate in palopo city,” Journal of Applied Mathematics and Computation, vol. 7, no. 2, pp. 185–196, 2022.
R. Hidayat, M. Ilyas, Y. Yuliani, S. Sifriyani, and D. Denysia, “Mathematical model of the unemployment rate with multiple spline regression,” in AIP Conference Proceedings, vol. 3235, no. 1, 2024, p. 020003.
R. Hidayat, I. N. Budiantara, B. W. Otok, and V. Ratnasari, “A reproducing kernel hilbert space approach and smoothing parameters selection in spline-kernel regression,” Journal of Theoretical and Applied Information Technology, vol. 97, no. 2, pp. 465–475, 2019
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