Property Crime in Java Island 2022 based on Demography and Socioeconomic Aspects using Spatial Analysis Approach

Property crime is the most common type of crime in Indonesia with the most rapid increasing in 2022. Java is the island with the highest magnitude of 65.85% if it is compared to the previous year and accounts for more than one third of the total cases in Indonesia. This study aims to determine an overview of these types of criminal offenses and the variables that affect them spatially. The analysis method uses in this study is descriptive analysis which will followed by inferential analysis, namely spatial analysis using Geographically Weighted Negative Binomial Regression (GWNBR). Based on this research, it is found that there are four regional groupings with variables that significantly affect all regions, namely life expectancy and Gini ratio. Meanwhile, there are variables that affect some regions, namely mean years schooling and total population. In addition, it is found that Geographically Weighted Negative Binomial Regression is better used than negative binomial regression in modeling property crime in Java Island in 2022.

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Publication Details

Journal
Limits Journal of Mathematics and Its Applications
Published
2025-03-26
DOI
https://doi.org/10.12962/limits.v22i1.3371
Primary Topic
Crime Patterns and Interventions
Type
article
Field-Weighted Citation Impact
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article

Property Crime in Java Island 2022 based on Demography and Socioeconomic Aspects using Spatial Analysis Approach

Timbang Sirait, Fabian La Wima Vallessy
Limits Journal of Mathematics and Its Applications
Crime Patterns and Interventions
article

Property Crime in Java Island 2022 based on Demography and Socioeconomic Aspects using Spatial Analysis Approach

Timbang Sirait, Fabian La Wima Vallessy
article en

Abstract

Property crime is the most common type of crime in Indonesia with the most rapid increasing in 2022. Java is the island with the highest magnitude of 65.85% if it is compared to the previous year and accounts for more than one third of the total cases in Indonesia. This study aims to determine an overview of these types of criminal offenses and the variables that affect them spatially. The analysis method uses in this study is descriptive analysis which will followed by inferential analysis, namely spatial analysis using Geographically Weighted Negative Binomial Regression (GWNBR). Based on this research, it is found that there are four regional groupings with variables that significantly affect all regions, namely life expectancy and Gini ratio. Meanwhile, there are variables that affect some regions, namely mean years schooling and total population. In addition, it is found that Geographically Weighted Negative Binomial Regression is better used than negative binomial regression in modeling property crime in Java Island in 2022.

Limits Journal of Mathematics and Its ApplicationsVol. 22(1)
Openalex Percentile: Top 92%
Crime Patterns and Interventions
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