UNP Journal of Statistics and Data Science
Vol. 4 No. 1 (2026): UNP Journal of Statistics and Data Science

Spatial Autoregressive Model to Factors Poverty Gap Index in West Java, 2023

Rahmat Kurniawan (Unknown)
Figo Rahmatullah (Universitas Negeri Padang)
Fauzan Gustiandra (Universitas Negeri Padang)
Tessy Octavia Mukhti (Universitas Negeri Padang)

Article Info

Publish Date
16 Mar 2026

Abstract

Spatial analysis is the analysis of data with spatial effects. The spatial autoregressive is used when the effect of the dependent variable at one location is influenced by the value of the dependent variable at nearby or neighboring locations. The spatial autoregressive model is more appropriate to model the factors influencing the poverty depth index in West Java in 2023. Based on the Spatial Autoregressive modeling, the variables that influence the Poverty Depth Index in West Java are Population Density, Open Unemployment Rate, and economic growth. The SAR modeling produces a higher coefficient of determination compared to the linear model, which is 68.88% with an AIC value of 18.6149.

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Journal Info
UNP Journal of Statistics and Data Science
Website

Abbrev

ujsds

Publisher

Universitas Negeri Padang

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

Description

UNP Journal of Statistics and Data Science is an open access journal (e-journal) launched in 2022 by Department of Statistics, Faculty of Science and Mathematics, Universitas Negeri Padang. UJSDS publishes scientific articles on various aspects related to Statistics, Data Science, and its ...