Spatial Autoregressive Quantile Regression untuk Pemodelan Angka Harapan Hidup di Provinsi Sumatera Utara

Wenni Marlina; Rina Filia Sari

doi:10.37905/euler.v13i2.32367

Spatial Autoregressive Quantile Regression untuk Pemodelan Angka Harapan Hidup di Provinsi Sumatera Utara

Wenni Marlina, Rina Filia Sari

Abstract

Life Expectancy (LE) is a key indicator for assessing the level of public health. North Sumatra Province still faces challenges in improving its LE, which remains below the national average. This study aims to compare three spatial models, namely: SAR, RSAR, and SARQR to model HLI in North Sumatra. Secondary data from 2023 for 33 districts/cities were obtained from the North Sumatra Provincial Statistics Agency, with HLI as the dependent variable and seven independent variables. The analysis began with multiple linear regression and classical assumption tests, followed by the formation of a spatial queen contiguity matrix, spatial effect tests (Moran's Index and Lagrange Multiplier), and modeling using the three spatial regression approaches. The results indicate that SARQR at the 0.1 quantile is the best model with the lowest AIC value (23.7764) and superiority in addressing spatial outliers. Therefore, SARQR at the 0.1 quantile is recommended as the optimal model for modeling AHH in North Sumatra.

Keywords

Life Expectancy; Spatial Quantile Regression; Spatial Autoregressive Model

Full Text:

PDF

References

P. R. Arum, R. P. Gautama, I. Fitriani, dan F. Naza, “Identifying Factors that Influence Life Expectancy in Central Java Using Spatial Regression Models,” J. Ilm. Toeri dan Apl. Stat., vol. 16, no. 2, hal. 606–613, 2023, doi: https://doi.org/10.36456/jstat.vol16.no2.a8375.

H. I. Zebua dan I. G. N. M. Jaya, “Spatial autoregressive model of tuberculosis cases in Central Java Province 2019,” CAUCHY J. Mat. Murni dan Apl., vol. 7, no. 2, hal. 240–248, 2022, doi: https://doi.org/10.18860/ca.v7i2.13451.

M. S. Nur, P. R. Arum, F. A. Adani, C. A. D. Aryani, dan A. Maulana, “Pemodelan Spatial Autoregressive (SAR) untuk Persentase Kemiskinan di Jawa Barat Tahun 2021,” J. MSA (Matematika dan Stat. serta Apl., vol. 12, no. 1, hal. 8–14, 2024, doi: https://doi.org/10.24252/msa.v12i1.39449.

A. Aswi dkk., “Childhood stunting in Indonesia: assessing the performance of Bayesian spatial conditional autoregressive models,” Geospat. Health, vol. 19, no. 2, hal. 9, 2024, doi: 10.4081/gh.2024.1321.

M. Kumalasari dan D. Poerwono, “Analisis Pertumbuhan Ekonomi, Angka Harapan Hidup, Angka Melek Huruf, Rata Rata Lama Sekolah, Pengeluaran Perkapita dan Jumlah Penduduk terhadap Tingkat Kemiskinan Di Jawa Tengah,” eprints.undip.ac.id, 2011.

H. Musyarofah, H. Yasin, dan T. Tarno, “Robust spatial autoregressive untuk pemodelan angka harapan hidup provinsi jawa timur,” J. Gaussian, vol. 9, no. 1, hal. 26–40, 2020, doi: https://doi.org/10.14710/j.gauss.9.1.26-40.

Bphn.go.id, “Hasil Penyelarasan Naskah Akademik Rancangan Undang-Undang Tentang Perubahan Kedua Atas Undang-Undang Nomor 21 Tahun 2001 Tentang Otonomi Khusus Bagi Provinsi Papua.”

H. Yasin, A. R. Hakim, dan B. Warsito, “Development life expectancy model in Central Java using robust spatial regression with M-estimators,” Commun. Math. Biol. Neurosci., vol. 2020, no. 2, hal. 1–15, 2020.

BPS, “Angka Harapan Hidup (AHH) Menurut Provinsi dan Jenis Kelamin - Tabel Statistik - Badan Pusat Statistik Indonesia,” 2023. [Daring]. Tersedia pada: https://www.bps.go.id/id/statistics-

D. Aryani, Perkembangan Kota Dan Permasalahan Lingkungan Perkotaan. 2024.

F. Yanuar, T. Abrari, dan I. R. HG, “The construction of unemployment rate model using SAR, quantile regression, and SARQR model,” Pakistan J. Stat. Oper. Res., vol. 19, no. 3, hal. 447–458, 2023, doi: http://dx.doi.org/10.18187/pjsor.v19i3.4241.

F. Yanuar, T. Abrari, I. R. HG, dan A. Zetra, “Spatial autoregressive quantile regression with application on open unemployment data,” Sci. Technol. Indones., vol. 8, no. 2, hal. 321–329, 2023, doi: https://doi.org/10.26554/sti.2023.8.2.321-329.

T. A. Taqiyyuddin dan M. Irfan, “Faktor Penyebab Kemiskinan di Provinsi Jawa Barat Menggunakan Spatial Autoregressive Quantile Regression,” J. Sains Mat. dan Stat., vol. 8, no. 1, hal. 59–69, 2022, doi: http://dx.doi.org/10.24014/jsms.v8i1.13185.

A. Hapsery, E. M. P. Hermanto, dan Y. U. Aprilia, “Perbandingan SAR dan SARQR Pada Pemodelan Indeks Pembangungan Manusia di Jawa Tengah Tahun 2022,” J. Gaussian, vol. 12, no. 4, hal. 581–592, 2024, doi: https://doi.org/10.14710/j.gauss.12.4.581-592.

T. Yu, F. Gao, X. Liu, dan J. Tang, “A spatial autoregressive quantile regression to examine quantile effects of regional factors on crash rates,” Sensors, vol. 22, no. 1, hal. 5, 2021, doi: https://doi.org/10.3390/s22010005.

L. Usman, A. Saefuddin, dan A. Djuraidah, “Analisis Data Produk Domestik Regional Bruto Pulau Jawa Menggunakan Pendekatan Regresi Kuantil Spasial,” Estimasi J. Stat. Its Appl., vol. 4, no. 2, hal. 153–164, 2023, doi: https://doi.org/10.20956/ejsa.v4i2.27573.

A. B. Tribhuwaneswari, A. Hapsery, dan W. K. Rahayu, “Spatial autoregressive quantile regression as a tool for modelling human development index factors in 2020 East Java,” AIP Conf. Proc., vol. 2668, no. 1, hal. 1–11, 2022, doi: https://doi.org/10.1063/5.0112828.

M. I. Rizki, H. Q. Sadida, dan A. N. Fauziah, “Pemodelan Spatial Autoregressive Quantile Regression pada Tingkat Kemiskinan di Provinsi Jawa Barat,” E-Prosiding Semin. Nas. Stat. Dep. Stat. FMIPA Univ. Padjadjaran, vol. 10, no. 1, hal. 1–7, 2021.

E. Oktaviana, P. R. Arum, dan M. Al Haris, “Pemodelan Spatial Autoregressive Quantile Regression (SARQR) Menggunakan Pembobot Queen Contiguity Pada Kasus Stunting Balita di Indonesia,” Pros. Semin. Nas. Unimus, vol. 6, no. 2, hal. 411–425, 2023.

M. I. Rizki dan T. Ammar, “Pemodelan Spatial Autoregressive Quantile Regression Pada Faktor Yang Memengaruhi Tingkat Incident Rate Demam Berdarah Dengue di Jawa Barat,” Pros. Semin. Nas. Mat. dan Stat., vol. 2, no. 1, hal. 312–321, 2022.

T. Abrari, F. Yanuar, dan D. Devianto, “Pemodelan Gizi Buruk Balita Di Indonesia Dengan Model Robust Spasial Autoregresif,” J. Sains Mat. dan Stat., vol. 9, no. 2, hal. 97–107, 2023, doi: https://doi.org/10.24014/jsms.v6i2.xxxxx.

H. Yasin, B. Warsito, A. R. Hakim, dan R. N. Azizah, “Life Expectancy Modeling Using Modified Spatial Autoregressive Model,” Media Stat., vol. 15, no. 1, hal. 72–82, 2022, doi: https://doi.org/10.14710/medstat.15.1.72-82.

D. N. Gujarati dan D. C. Porter, “Basic econometrics. mcgraw-hill companies,” in New York, NY, USA, 2009.

D. C. Montgomery, E. A. Peck, dan G. G. Vining, Introduction to linear regression analysis. John Wiley & Sons, 2021.

Z. Martha, A. N. Muharromah, D. Permana, dan T. O. Mukthi, “Analisis Tingkat Kejahatan di Jabodetabek Menggunakan Model SARQR Pada Data Yang Mengandung Outlier,” d’Cartesian J. Mat. dan Apl., vol. 13, no. 2, hal. 69–72, 2024, doi: https://doi.org/10.35799/dc.13.2.2024.57594.

A. Febriyanti, A. Djuraidah, dan A. H. Wigena, “Spatial Autoregressive Quantile Regression Modelling for Gross Domestic Regional Product Data (Case: 113 Districts/Cities in Java in 2010),” Glob. J. Pure Appl. Math., vol. 11, no. 4, hal. 2255–2264, 2015.

H. I. Zebua, “Spatial autoregressive quantile regression pada kasus tuberkulosis di Kota Bandung,” J. Anal. Res. Stat. Comput., vol. 2, no. 2, hal. 1–13, 2023, doi: https://doi.org/10.4590/jarsic.v2i2.24.

DOI: https://doi.org/10.37905/euler.v13i2.32367