MODELING CRIME IN EAST JAVA USING SPATIAL DURBIN MODEL REGRESSION

  • Yuniar Farida Department of Mathematics, Faculty of Science and Technology, Universitas Islam Negeri Sunan Ampel, Indonesia https://orcid.org/0000-0001-8666-4980
  • Mayandah Farmita Department of Mathematics, Faculty of Science and Technology, Universitas Islam Negeri Sunan Ampel, Indonesia
  • Putroue Keumala Intan Department of Mathematics, Faculty of Science and Technology, Universitas Islam Negeri Sunan Ampel, Indonesia https://orcid.org/0009-0003-9334-0820
  • Hani Khaulasari Department of Mathematics, Faculty of Science and Technology, Universitas Islam Negeri Sunan Ampel, Indonesia https://orcid.org/0000-0002-1360-6744
  • Achmad Teguh Wibowo Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Sunan Ampel, Indonesia https://orcid.org/0000-0003-0593-0277
DOI: https://doi.org/10.30598/barekengvol18iss3pp1497-1508
Keywords: Criminality, Spatial, Spatial Autoregressive, Spatial Durbin Model

Abstract

The high crime rate will create unrest and losses for the community. One of the provinces with high crime rates is East Java. This study aims to analyze the factors that influence criminality in East Java to ensure appropriate crime prevention and control measures can be taken. The factors that potentially influence crime in East Java studied include population density, the number of poor people, unemployment, Human Development Index (HDI), Gross Regional Domestic Product (GRDP), and per Capita Expenditure, which are associated with geographical conditions in each region (regency/city) collected from BPS East Java in 2022. Meanwhile, the number of crimes is collected from the East Java Regional Police. This research uses a statistical method, namely the Spatial Durbin Model (SDM), which is a particular form of the Spatial Autoregressive Model (SAR) method with Queen Contiguity weighting by analyzing geographically (spatial processes). Based on the results of the analysis, it was found that the influential factors were unemployment, HDI, GRDP, and per Capita Expenditure, and the R-square result was obtained at 85.18%. This shows a relationship between spatial accessibility and crime, where unemployment, HDI, GRDP, and per Capita Expenditure in an area can affect regional vulnerability to crime

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Published
2024-07-31
How to Cite
[1]
Y. Farida, M. Farmita, P. Intan, H. Khaulasari, and A. Wibowo, “MODELING CRIME IN EAST JAVA USING SPATIAL DURBIN MODEL REGRESSION”, BAREKENG: J. Math. & App., vol. 18, no. 3, pp. 1497-1508, Jul. 2024.
Issue
Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Section
Articles

Copyright (c) 2024 Yuniar Farida, Mayandah Farmita, Putroue Keumala Intan, Hani Khaulasari, Achmad Teguh Wibowo

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