Analysis of Open Unemployment Rates in Indonesia Based on GRDP and the Percentage of Poor Population Using Nonparametric B-Spline Regression
DOI:
https://doi.org/10.20956/j.v22i2.48355Keywords:
GDRP, Nonparametric B-Spline Regression, Open Unemployment Rate, The Percentage of Poor PopulationAbstract
Open Unemployment Rate (OUR) is a crucial indicator of the condition of the job market and the economy in Indonesia. This research is to modeling and analyzes the impact of GRDP and the percentage of poor population to the OUR in Indonesia using nonparametric B-Spline regression. The study applied B-Spline model due to the model’s property of handling non-linear associations without imposing any distributional assumptions. The research a used secondary data sourced from BPS Indonesia in 2024, which included 38 provinces in Indonesia. The analysis outcomes show that optimal model is achieved when the order was set at 2 for both GRDP and the percentage of poor population with one knot set at GRDP (1.055) and two knots set at the percentage of poor population (6.813333 and 11.583333) which gave a minimum GCV produced at 1.577369. The model’s coefficient of determination value of 0.7454 indicates that the model can explain 74.54% of the variation in the OUR is explained by GRDP and the percentage of poor population, with the remaining 25.46% is impacted by factors beyond the model.
References
[1] Amaliah, K. L. N., Amalya, D., Selviana, N., Afrilita, M., Putri, D. S. A., & Sulistiana, I., 2025. Analisis Tingkat Pengangguran Terbuka Berdasarkan Indikator Sosial di Provinsi Kepulauan Bangka Belitung Menggunakan Pendekatan Regresi B-Spline. Jurnal Gaussian. Vol. 14, No. 2, 401–410. https://doi.org/10.14710/j.gauss.14.2.401-410
[2] Ariesta, D., Gusriani, N., & Parmikanti, K., 2021. Estimasi Parameter Model Regresi Nonparametrik B-Spline Pada Angka Kematian Maternal. Jurnal Matematika UNAND. Vol 10, No. 3, 342–354.
[3] Azizah, L. N., Pasaribu, J. R. S., Hutagulung, I., Purba, A. A., & Sinaga, S. A., 2023. Analisis Pengaruh PDRB dan Pengangguran Terhadap Kemiskinan di Indonesia Tahun 2018-2022. JoSES: Journal of Sharia Economic Scholar. Vol. 2 No. 1, 25–32.
[4] Badan Pusat Statistik. 2024. Keadaan Angkatan Kerja di Indonesia Agustus 2024. Badan Pusat Statistik.
[5] Badan Pusat Statistik. 2025. Tingkat Pengangguran Terbuka Menurut Provinsi (Persen), 2024. Badan Pusat Statistik.
[6] Budiantara, I. N., Suryadi, F., Otok, B. W., & Guritno, S., 2006. Pemodelan B-Spline Dan MARS pada Nilai Ujian Masuk Terhadap IPK Mahasiswa Jurusan Disain Komunikasi Visual UK. PETRA Surabaya. Jurnal Teknik Industri. Vol 8, No. 1, 1–13. https://doi.org/10.9744/jti.8.1.1-13
[7] de Boor, C. 2001. A Practical Guide to Splines (Revised Ed). Springer-Verlag, New York.
[8] Erlangga, L. T. 2019. Analisis Tingkat Pengangguran Terbuka di Indonesia menggunakan Regresi Nonparametrik B-spline. Universitas Muhammadiyah Semarang, Semarang.
[9] Husain, H., Dewi, A. F., & Wardani, A. E., 2024. Pemodelan Prevalensi Stunting Indonesia Menggunakan Regresi Nonparametrik Spline Truncated. Journal of Analytical Research, Statistics and Computation. Vol. 3, No. 1, 1–13.
[10] Kemnaker. 2023. Rencana Tenaga Kerja Jangka Panjang: Menuju Indonesia Emas 2045. Satudata Kemnaker. https://satudata.kemnaker.go.id/publikasi/118. [11 November 2025]
[11] Muhgni, M., Fadly, F., Adnan, A., & Harison., 2020. Pemodelan Tingkat Pengangguran Terbuka di Pulau Sumatera dengan Menggunakan Regresi Nonparametrik Spline. Jurnal Sains Matematika Dan Statistika. Vol. 6, No. 1.
[12] Nasir, R. S., Wahid, M. A., Padang, D. R. A., Anna, I., & Raupong., 2024. Analisis Kemiskinan di Sulawesi Selatan dengan Regresi Nonparametrik Berbasis B-Spline. Indonesian Journal of Applied Statistics. Vol. 7, No. 1, 27–40. https://doi.org/10.13057/ijas.v7i1.80716
[13] Prayogo, S. A., & Satria, D., 2020. Analisis faktor – faktor yang memengaruhi tingkat penganguran terbuka kabupaten/kota di provinsi jawa timur tahun 2014-2018. Jurnal Ilmiah Mahasiswa FEB. Vol. 8, No. 2.
[14] Rahmawati, A. S., Ispriyanti, D., & Warsito, B., 2017. Pemodelan Kasus Kemiskinan di Jawa Tengah Menggunakan Regresi Nonparametrik Metode B-Spline. Jurnal Gaussian. Vol. 6, No. 1, 11–20. http://ejournal-s1.undip.ac.id/index.php/gaussian
[15] Romhadhoni, P., Faizah, D. Z., & Afifah, N., 2018. Pengaruh Produk Domestik Regional Bruto ( PDRB ) Daerah Terhadap Pertumbuhan Ekonomi dan Tingkat Pengangguran Terbuka di Provinsi DKI Jakarta. Jurnal Matematika Integratif. Vol. 14, No. 2, 115–121. https://doi.org/10.24198/jmi.v14.n2.2018.115-121
[16] Ruppert, D., Wand, M. P., & Carrol, R. J., 2003. Semiparametric Regression. In Regression Modeling. Cambridge University Press. https://doi.org/10.1017/CBO9780511755453
[17] Wardani, P. K., & Ratna, M., 2022. Pemodelan Terhadap Faktor-Faktor yang Mempengaruhi Pertumbuhan Ekonomi di Nusa Tenggara Timur Menggunakan Pendekatan Regresi Nonparametrik Spline. Jurnal Sains Dan Seni ITS. Vol. 11, No. 3, 2337–3520. https://doi.org/10.12962/j23373520.v11i3.77735
[18] Wijaya, A. F. H., 2018. Analisis Faktor-Faktor Yang Mempengaruhi Tingkat Pengangguran Terbuka (TPT) Di Provinsi Aceh dengan Regresi Nonparametrik Spline Truncated. Institut Teknologi Sepuluh Nopember, Surabaya. https://api.semanticscholar.org/CorpusID:126778402
[19] Wulan, P. R., & Rifai, N. A. K., 2023. Penerapan Regresi Nonparametrik B-Spline pada Model Tingkat Pengangguran Terbuka Berdasarkan Tingkat Partisipasi Angkatan Kerja dan PDRB di Provinsi Jawa Barat. Bandung Conference Series: Statistics. Vol. 3, No. 2, 294–302. https://doi.org/10.29313/bcss.v3i2.8095
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Jurnal Matematika, Statistika dan Komputasi

This work is licensed under a Creative Commons Attribution 4.0 International License.

This work is licensed under a Creative Commons Attribution 4.0 International License.
Jurnal Matematika, Statistika dan Komputasi is an Open Access journal, all articles are distributed under the terms of the Creative Commons Attribution License, allowing third parties to copy and redistribute the material in any medium or format, transform, and build upon the material, provided the original work is properly cited and states its license. This license allows authors and readers to use all articles, data sets, graphics and appendices in data mining applications, search engines, web sites, blogs and other platforms by providing appropriate reference.




