DOI: https://doi.org/10.14710/j.gauss.12.4.581-592

PERBANDINGAN SAR DAN SARQR PADA PEMODELAN INDEKS PEMBANGUNGAN MANUSIA DI JAWA TENGAH TAHUN 2022

*Alfisyahrina Hapsery orcid scopus  -  Universitas pgri adi buana, Surabaya, Indonesia
Elvira Mustikawati Putri Hermanto orcid scopus  -  Universitas pgri adi buana, Surabaya, Indonesia
Yohanita Uniyantri Aprilia  -  Universitas pgri adi buana surabaya, Indonesia
Open Access Copyright 2024 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

Citation Format:
Abstract
The Human Development Index (HDI) is one of the indicators created to measure the success of human quality of life. Central Java is one of the provinces that has experienced a significant increase in HDI in recent years. However, the rankings of its regencies/cities have not shown significant changes. This study aims to model the HDI in Central Java based on the factors that influence it. The data used for modeling the HDI are secondary data obtained from the Central Statistics Agency (BPS) of Central Java, encompassing 35 regencies/cities in Central Java. The analysis in this study employs spatial analysis, specifically Spatial Autoregressive (SAR). Given the potential spatial effects at certain quantiles of the independent variables, the appropriate analysis is Spatial Autoregressive Quantile Regression (SARQR), which combines the SAR method with quantile regression. The best model from the study results is the SAR model, with factors influencing the HDI in Central Java including Population Percentage, Labor Force Participation Rate, Crime Rate, and Average Non-Food Expenditure. The cities of Semarang, Salatiga, and Surakarta have the highest HDI values at each quantile, ranging from the 0.10 quantile to the 0.90 quantile.

Note: This article has supplementary file(s).

Fulltext View|Download |  common.other
Perbandingan SAR dan SARQR Pada Pemodelan Indeks Pembangungan Manusia di Jawa Tengah Tahun 2022
Subject SAR dan SARQR
Type Other
  Download (1MB)    Indexing metadata
Keywords: Indeks Pembangunan Manusia; SAR; Kuantil Regresi; SARQR.

Article Metrics:

Article Info
Section: Articles
Language : ID
Recent articles
ANALISIS KEPUASAN TERHADAP LAYANAN APLIKASI DOLTINUKU DENGAN MENGGUNAKAN METODE STRUCTURAL EQUATION MODELING-PARTIAL LEAST SQUARE (SEM-PLS) PERAMALAN PEREDARAN UANG KARTAL DI INDONESIA MENGGUNAKAN MODEL HYBRID SARIMAX-NEURAL NETWORK ANALISIS SENTIMEN KEBIJAKAN PENYELENGGARA SISTEM ELEKTRONIK LINGKUP PRIVAT MENGGUNAKAN PENALIZED LOGISTIC REGRESSION DAN SUPPORT VECTOR MACHINE More recent articles
  1. Badan Pusat Statistik. (2022). Indeks Pembangunan Manusia. In Badan Pusat Statistik
  2. Fauziyyah, S., Tarihoran, N., & Sunardi, D. (2022). Pengaruh Indeks Pembangunan Gender, Tingkat Kemiskinan dan Pengeluaran Per Kapita Terhadap Indeks Pembangunan Manusia dalam Perspektif Ekonomi Islam Di Provinsi Banten Periode Tahun 2013 -2020. Jurnal Simki Economic, 5(2), 187–198. https://doi.org/10.32678/qathruna.v7i2.3145
  3. Hapsery, A., & Tribhuwaneswari, A. B. (2021). Monte Carlo Simulation in Quantile Regression Parameter for Sparsity Estimate. Journal of Physics: Conference Series, 2123(1). https://doi.org/10.1088/1742-6596/2123/1/012027
  4. Haryono, S., Murti, W., & Yolanda. (2023). FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS PEMBANGUNAN MANUSIA DAN DAMPAKNYA PADA PERTUMBUHAN EKONOMI DI PULAU JAWA. Journal of Applied Business and Economic (JABE), 9(3), 336–352
  5. Ibrahim, Z. (2016). Pengantar Ekonomi Makro. Koperasi Syariah Baraka
  6. Pemprov. (2023). Indeks Pembangunan Manusia Jateng Membaik. Pemerintah Provinsi Jawa Tengah
  7. Rahmawati, D., & Bimanto, H. (2021). Perbandingan Spatial Autoregressive Model dan Spatial Error Model dalam Pemodelan Indeks Pembangunan Manusia di Provinsi Jawa Timur. Jurnal Statistika Dan Aplikasinya, 5(1), 41–50. https://doi.org/10.21009/jsa.05104
  8. Shah, A. U. M., Reayat, N., & Shah, S. A. A. (2020). Relationship Between Unemployment, Poverty And Crime: An Empirical Cross-Sectional Analysis of Peshawar. International of Management Research And Emerging Science, 10(1), 111–117. https://doi.org/https://doi.org/10.56536/ijmres.v10i1.67
  9. Tribhuwaneswari, A. B., Hapsery, A., & Rahayu, W. K. (2022). Spatial autoregressive quantile regression as a tool for modelling human development index factors in 2020 East Java. AIP Conference Proceedings, 2668. https://doi.org/10.1063/5.0112828
  10. UNDP. (2022). Human Development Report 2021/2022
  11. Wardhani, A. P., & Yanti, T. S. (2021). Pemodelan Spatial Autoregressive Quantile Regression (SARQR) pada Data Gizi Buruk Balita di Kota Bandung. Prosiding Statistika, 606–612. https://doi.org/http://dx.doi.org/10.29313/.v0i0.2922
  12. Yanuar, F., Abrari, T., Izzati Rahmi, H. G., & Zetra, A. (2023). Spatial Autoregressive Quantile Regression with Application on Open Unemployment Data. Science and Technology Indonesia, 8(2), 321–329. https://doi.org/10.26554/sti.2023.8.2.321-329

Last update:

No citation recorded.

Last update:

No citation recorded.