A Comparison of Multivariate Adaptive Regression Spline and Spline Nonparametric Regression on Life Expectancy in Indonesia
Abstract
Keywords
Full Text:
DOWNLOAD [PDF]References
Ali, P., & Younas, A. (2021). Understanding and interpreting regression analysis. Evidence Based Nursing, 24(4), 116–118. https://doi.org/10.1136/ebnurs-2021-103425
Badan Pusat Statistik. (2023). Angka Harapan Hidup Tahun 2021-2023. BPS Provinsi Sulawesi Barat.
Badan Pusat Statistik. (2024). Umur Harapan Hidup Saat Lahir (UHH). BPS RI. bps.go.id
Bangun, R. H. (2019). Analisis Determinan Angka Harapan Hidup Kabupaten Mandailing Natal(Life Expectations Determinants Analysis In Mandailing Natal Regency). Jurnal Akuntansi Dan Ekonomi, 4(3), 22–31. https://doi.org/10.29407/jae.v4i3.13257
Bekar Adiguzel, M., & Cengiz, M. A. (2023). Model selection in multivariate adaptive regressions splines (MARS) using alternative information criteria. Heliyon, 9(9). https://doi.org/10.1016/j.heliyon.2023.e19964
Erlyn, P., Hidayat, B., Cahyo, A., & Saksono, H. (2022). Investment in Human Resources to Increase Achievement Levels of Sustainable Development. Jurnal Bina Praja, 14(1), 135–146. https://doi.org/10.21787/jbp.14.2022.135-146
Friedman, J. H. (1991). Multivariate Adaptive Regression Splines. The Annals of Statistics, 19(1), 1–141.
Ghozali, I. (2016). Aplikasi Analisis Multivariete Dengan Program IBM SPSS 23. Edisi 8. Badan Penerbit Universitas Diponegoro.
Hasanah, U. (2017). Pengaruh Ketimpangan Pendapatan, Pendapatan per Kapita, dan Pengeluaran Pemerintah di Bidang Kesehatan Terhadap Sektor Kesehatan di Indonesia. Jurnal Ilmu Ekonomi Terapan, 2(1), 30–43. https://doi.org/10.20473/jiet.v2i1.5504
Kuncoro, M. (2019). Metode Riset Untuk Bisnis dan Ekonomi (Edisi ke-3). Erlangga.
Lembang, F. K., Patty, H. W. M., & Maitimu, F. (2019). Analisis Kemiskinan di Kabupaten Maluku Tenggara Barat Menggunakan Pendekatan Multivariate Adaptive Regression Spline (MARS). MEDIA STATISTIKA, 12(2), 188. https://doi.org/10.14710/medstat.12.2.188-199
Maharani, M., & Saputro, D. R. S. (2021). Generalized Cross Validation (GCV) in Smoothing Spline Nonparametric Regression Models. Journal of Physics: Conference Series, 1808(1), 1–6. https://doi.org/10.1088/1742-6596/1808/1/012053
Mahmoud, H. F. F. (2021). Parametric Versus Semi and Nonparametric Regression Models. International Journal of Statistics and Probability, 10(2), 90–108. https://doi.org/10.5539/ijsp.v10n2p90
Mattalunru, M. R., Annas, S., & Aidid, M. K. (2022). Aplikasi Multivariate Adaptive Regression Splines (MARS) untuk Mengetahui Faktor yang Mempengaruhi Curah Hujan di Kota Makassar. VARIANSI: Journal of Statistics and Its Application on Teaching and Research, 4(1), 9–19. https://doi.org/https://doi.org/10.35580/variansiunm2
Mukrom, M. H., Yasin, H., & Hakim, A. R. (2021). Pemodelan Angka Harapan Hidup Provinsi Jawa Tengah menggunakan Robust Spatial Durbin Model. Jurnal Gaussian, 10(1), 44–54. https://doi.org/https://doi.org/10.14710/j.gauss.10.1.44-54
Nurhuda, G. N., Wasono, W., & Nohe, D. A. (2022). Nonparametric Regression Modeling Based on Spline Truncated Estimator on Simulation Data. Jurnal Matematika, Statistika Dan Komputasi, 19(1), 172–182. https://doi.org/10.20956/j.v19i1.21534
Pratama, Y. M., Fernandes, A. A. R., Wardhani, N. W. S., & Hamdan, R. (2024). Nonparametric Smoothing Spline Approach in Examining Investor Interest Factors. JTAM (Jurnal Teori Dan Aplikasi Matematika), 8(2), 425–440. https://doi.org/10.31764/jtam.v8i2.20192
Purnama, D. I. (2020). A Comparison between Nonparametric Approach: Smoothing Spline and B-Spline to Analyze The Total of Train Passangers in Sumatra Island. EKSAKTA: Journal of Sciences and Data Analysis, 1(1), 73–80. https://doi.org/10.20885/EKSAKTA.vol1.iss1.art11
Risambessy, S., Aulele, S. N., & Lembang, F. K. (2022). Misclassification Analysis of Elementary School Accreditation Data in Ambon City Using Multivariate Adaptive Regression Spline. Jurnal Matematika, Statistika Dan Komputasi, 18(3), 394–406. https://doi.org/10.20956/j.v18i3.19451
Ritonga, N. A. R., & Sutarman. (2023). Estimation of Multivariate Adaptive Regression Splines (MARS) Model Parameters by Using Generalized Least Square (GLS) Method. JMEA : Journal of Mathematics Education and Application, 2(2), 62–72. https://doi.org/10.30596/jmea.v2i2.13106
Wicaksono, W., Wilandari, Y., & Suparti. (2014). Pemodelan Multivariate Adaptive Regression Splines (MARS) pada Faktor-Faktor Resiko Angka Kesakitan Diare (Studi Kasus : Angka Kesakitan Diare di Jawa Tengah, Jawa Timur dan Daerah Istimewa Yogyakarta Tahun 2011). Jurnal Gaussian, 3(2), 253–262. https://doi.org/https://doi.org/10.14710/j.gauss.3.2.253%20-%20262
Worldometer. (2024). Life Expectancy of the World Population. https://www.worldometers.info/demographics/life-expectancy/
Yasmirullah, S. D. P., Otok, B. W., Purnomo, J. D. T., & Prastyo, D. D. (2021). Parameter Estimation of Multivariate Adaptive Regression Spline (MARS) with Stepwise Approach to Multi Drug-Resistant Tuberculosis (MDR-TB) Modeling in Lamongan Regency. Journal of Physics: Conference Series, 1752(1), 1–9. https://doi.org/10.1088/1742-6596/1752/1/012017
DOI: https://doi.org/10.31764/jtam.v9i3.29413
Refbacks
- There are currently no refbacks.
Copyright (c) 2025 Bagas Shata Pratama, Suliyanto, M. Fariz Fadillah Mardianto, Sediono

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
_______________________________________________
JTAM already indexing:
_______________________________________________
![]() | JTAM (Jurnal Teori dan Aplikasi Matematika) |
_______________________________________________
_______________________________________________
JTAM (Jurnal Teori dan Aplikasi Matematika) Editorial Office: