MODEL DEPENDENSI SPASIAL DETERMINAN INDEKS PEMBANGUNAN MANUSIA DI JAWA TIMUR MENGGUNAKAN SPATIAL LAG MODEL

Authors

  • Yudha Hadi Gunawan Herman Program Studi Statistika Universitas Hamzanwadi
  • Deshira Azzahra Cahyani Program Studi Statistika Universitas Hamzanwadi
  • Zahra Annisa Nadirah Program Studi Statistika Universitas Hamzanwadi
  • Laili Yuliarti Program Studi Statistika Universitas Hamzanwadi
  • Bq. Tia Azhari Program Studi Statistika Universitas Hamzanwadi
  • Zizia Aletha Program Studi Statistika Universitas Hamzanwadi
  • Septiana Program Studi Statistika Universitas Hamzanwadi

DOI:

https://doi.org/10.29408/eksbar.v3i1.34045

Keywords:

Human Development Index, Spatial Dependence, Spatial Lag Model, East Java

Abstract

This study aims to analyse the spatial dependence of the Human Development Index (HDI) determinants across districts and cities in East Java Province using the Spatial Lag Model (SLM). The research employs a quantitative spatial econometrics approach with secondary data obtained from Statistics Indonesia (BPS) and spatial boundary data in shapefile format. The variables used include HDI as the dependent variable, and population, open unemployment rate (TPT), regional gross domestic product (PDRB), and labour force participation rate (TPAK) as explanatory variables. Spatial dependence was tested using Moran’s I and Lagrange Multiplier tests. The results indicate a significant positive spatial autocorrelation of HDI, implying that regions with high HDI tend to cluster geographically. The estimation of the Spatial Lag Model shows that the spatial lag parameter (ρ) is positive and significant (ρ = 0.4313), revealing strong spatial dependence among neighbouring regions. The SLM also performs better than the classical OLS model, with a lower AIC (193.3610) and higher R-squared (0.7266). These findings suggest that the HDI of a region is influenced not only by socioeconomic factors but also by spill-over effects from adjacent areas. Therefore, spatial-based development policies are recommended to enhance human development more equitably across regions.

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Published

2026-06-29