Pemodelan Kriminal di Jawa Timur dengan Metode Geographically Weighted Regression (GWR)

  • Imanudin Nurhuda Universitas Padjadjaran
  • I Gede Nyoman Mindra Jaya Universitas Padjadjaran
Keywords: Geographically Weigthed Regression (GWR), Spatial, Criminalitas

Abstract

Criminality constitutes all kinds of actions that are economically and psychologically harmful in violation of the law applicable in the state of Indonesia as well as social and religious norms, while the criminal data is the number of cases reported to the police institution. The higher the number of complainants the higher the number of criminals in the region. The greater the risk the community represents the more insecure a region is. This study aims to obtain the best model affecting crime or crime in East Java. The number of crimes in this study is limited to the number of theft cases (whether ordinary theft, theft by force, theft with theft, and the theft of motor vehicles). In this study, we use the Geographically Weighted Regression (GWR) model because this method is quite effective in estimating data that has spatial heterogeneity (uniformity in location / spatial). In essence, the model parameters in GWR can be calculated at the observation location with the dependent variable and one or more independent variables that have been measured at the sites where the location is known, where criminal acts in the research conducted in East Java involves the effects of spatial heterogeneity, with fixed kernel weighting function. The results showed that the variables affecting criminality in East Java Province are population density, economic growth, Gini Ratio, and poverty.

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Published
2018-10-31
How to Cite
Nurhuda, I., & Jaya, I. G. N. (2018). Pemodelan Kriminal di Jawa Timur dengan Metode Geographically Weighted Regression (GWR). Jurnal Matematika "MANTIK", 4(2), 150-158. https://doi.org/10.15642/mantik.2018.4.2.150-158
Section
Articles