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

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...

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Autores principales:	Imanudin Nurhuda, I Gede Nyoman Mindra Jaya
Formato:	article
Lenguaje:	EN
Publicado:	Department of Mathematics, UIN Sunan Ampel Surabaya 2018
Materias:	Geographically Weigthed Regression (GWR), Spatial, Criminalitas Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/bc4672f051bd47168522445b044e0f2f
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spelling	oai:doaj.org-article:bc4672f051bd47168522445b044e0f2f2021-12-02T17:15:30ZPemodelan Kriminal di Jawa Timur dengan Metode Geographically Weighted Regression (GWR)2527-31592527-316710.15642/mantik.2018.4.2.150-158https://doaj.org/article/bc4672f051bd47168522445b044e0f2f2018-10-01T00:00:00Zhttp://jurnalsaintek.uinsby.ac.id/index.php/mantik/article/view/296https://doaj.org/toc/2527-3159https://doaj.org/toc/2527-3167Criminality 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.Imanudin NurhudaI Gede Nyoman Mindra JayaDepartment of Mathematics, UIN Sunan Ampel SurabayaarticleGeographically Weigthed Regression (GWR), Spatial, CriminalitasMathematicsQA1-939ENMantik: Jurnal Matematika, Vol 4, Iss 2, Pp 150-158 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Geographically Weigthed Regression (GWR), Spatial, Criminalitas Mathematics QA1-939
spellingShingle	Geographically Weigthed Regression (GWR), Spatial, Criminalitas Mathematics QA1-939 Imanudin Nurhuda I Gede Nyoman Mindra Jaya Pemodelan Kriminal di Jawa Timur dengan Metode Geographically Weighted Regression (GWR)
description	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.
format	article
author	Imanudin Nurhuda I Gede Nyoman Mindra Jaya
author_facet	Imanudin Nurhuda I Gede Nyoman Mindra Jaya
author_sort	Imanudin Nurhuda
title	Pemodelan Kriminal di Jawa Timur dengan Metode Geographically Weighted Regression (GWR)
title_short	Pemodelan Kriminal di Jawa Timur dengan Metode Geographically Weighted Regression (GWR)
title_full	Pemodelan Kriminal di Jawa Timur dengan Metode Geographically Weighted Regression (GWR)
title_fullStr	Pemodelan Kriminal di Jawa Timur dengan Metode Geographically Weighted Regression (GWR)
title_full_unstemmed	Pemodelan Kriminal di Jawa Timur dengan Metode Geographically Weighted Regression (GWR)
title_sort	pemodelan kriminal di jawa timur dengan metode geographically weighted regression (gwr)
publisher	Department of Mathematics, UIN Sunan Ampel Surabaya
publishDate	2018
url	https://doaj.org/article/bc4672f051bd47168522445b044e0f2f
work_keys_str_mv	AT imanudinnurhuda pemodelankriminaldijawatimurdenganmetodegeographicallyweightedregressiongwr AT igedenyomanmindrajaya pemodelankriminaldijawatimurdenganmetodegeographicallyweightedregressiongwr
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Pemodelan Kriminal di Jawa Timur dengan Metode Geographically Weighted Regression (GWR)

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