Crime clustering in Yogyakarta: Data analysis 2016-2020 and state responsibility in crime

Crime often occurs. The crime rate in an area will be different from that of other areas according to the characteristics of the area. The clustering carried out in this study is based on the number of reported crime rates. This study aims to cluster crime-prone areas in Yogyakarta City so that they...

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Veröffentlicht in:Jurnal civics Jg. 21; H. 2; S. 245 - 253
Hauptverfasser: Martiana, Aris, Arif, Nursida, Wardana, Amika, Wahab, Norwaliza Abdul
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Universitas Negeri Yogyakarta 21.09.2024
Schlagworte:
clustering
crime
urban
vulnerable areas
ISSN:1829-5789, 2541-1918
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Abstract Crime often occurs. The crime rate in an area will be different from that of other areas according to the characteristics of the area. The clustering carried out in this study is based on the number of reported crime rates. This study aims to cluster crime-prone areas in Yogyakarta City so that they can identify areas to seek to handle them more effectively. The method of this research is ex post facto, which is a quantitative exploratory descriptive. Data was collected through the crime documentation of Yogyakarta City, which has 15 regional units and with crime rates from 2016 to 2020. Clustering is carried out by cluster analysis of the average linkage hierarchy method because the variables are less than 100, so multi-storey clusters are more appropriately used and return to the goal, namely, to identify crime-prone areas. The research results on the crime rate in Yogyakarta City based on data in each reported police unit for five years, namely from 2016, 2017, 2018, 2019, and 2020, show that the unit area is divided into 3 clusters consisting of clusters 1, 2, and 3. Each cluster has members, namely Cluster 1, Yogyakarta City Resort. Cluster 2 consists of Gondomanan, Ngampilan, Gedongtengen, Jetis, Tegalrejo, Wirobrajan, Kraton, Mantrijeron, Mergangsan, Kotagede, Danurajan and Pakualam. Cluster 3 consists of Umbulharjo and Gondokusuman. So, cluster 1, according to the total number of 5 years, is indeed the most, but for clusters 2 and 3, it is different, so in this clustering, the underlying is the similarity between the variables owned. Crime in the city is often encountered due to the heterogeneity of the community from various fields, so practical efforts must be made to deal with it.
AbstractList Crime often occurs. The crime rate in an area will be different from that of other areas according to the characteristics of the area. The clustering carried out in this study is based on the number of reported crime rates. This study aims to cluster crime-prone areas in Yogyakarta City so that they can identify areas to seek to handle them more effectively. The method of this research is ex post facto, which is a quantitative exploratory descriptive. Data was collected through the crime documentation of Yogyakarta City, which has 15 regional units and with crime rates from 2016 to 2020. Clustering is carried out by cluster analysis of the average linkage hierarchy method because the variables are less than 100, so multi-storey clusters are more appropriately used and return to the goal, namely, to identify crime-prone areas. The research results on the crime rate in Yogyakarta City based on data in each reported police unit for five years, namely from 2016, 2017, 2018, 2019, and 2020, show that the unit area is divided into 3 clusters consisting of clusters 1, 2, and 3. Each cluster has members, namely Cluster 1, Yogyakarta City Resort. Cluster 2 consists of Gondomanan, Ngampilan, Gedongtengen, Jetis, Tegalrejo, Wirobrajan, Kraton, Mantrijeron, Mergangsan, Kotagede, Danurajan and Pakualam. Cluster 3 consists of Umbulharjo and Gondokusuman. So, cluster 1, according to the total number of 5 years, is indeed the most, but for clusters 2 and 3, it is different, so in this clustering, the underlying is the similarity between the variables owned. Crime in the city is often encountered due to the heterogeneity of the community from various fields, so practical efforts must be made to deal with it.
Author Martiana, Aris
Wahab, Norwaliza Abdul
Arif, Nursida
Wardana, Amika
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Snippet Crime often occurs. The crime rate in an area will be different from that of other areas according to the characteristics of the area. The clustering carried...
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SubjectTerms clustering
crime
urban
vulnerable areas
Title Crime clustering in Yogyakarta: Data analysis 2016-2020 and state responsibility in crime
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