Pemodelan Ruang dan Masa Kes Jenayah Harta Benda dan Kekerasan di Wilayah Persekutuan Kuala Lumpur dan Wilayah Persekutuan Putrajaya
| dc.contributor.author | Azizul bin Ahmad | |
| dc.date.accessioned | 2026-07-15T02:56:19Z | |
| dc.date.issued | 2025 | |
| dc.description | This research analyzes property crime and violent crime data over a period of six years, from year 2015 to year 2020. It covers the jurisdiction of the Kuala Lumpur Contingent Police Headquarters (IPKKKL) which covers the Federal Territory of Kuala Lumpur (WPKL) and the Federal Territory of Putrajaya (WPP). This study uses Geographic Information System (GIS) technology to identify crimes through detailed records that include the penal code, location, and time of the incident. It reveals the spatial and temporal distribution of crime incidents, identifies hotspots, and models the relationship between crime and land use and demographic factors. The problems of this study are divided into three, namely (i). Dynamics of property and violent crime cases; (ii). Cases of property crime and violence in the space-time context; and (iii). The relationship between demographic factors and land use with property and violent crime cases. The objectives of the study are divided into three, namely (i). Identifying trends and spatial distribution of property and violent crime cases in the study area. (ii). Analyzing the variation of the clustering pattern of property and violent crime cases in terms of space and space-time in the study area based on the land use involved. and (iii). Modeling the relationship between demographic factors and land use with cases of property crime and violence in the study area. The analysis methods used in this study are Descriptive Analysis, Spatial Autocorrelation (Global Moran's I Index), Emerging Hot Spot Analysis (EHSA), Mean Center (MC), Standard Deviational Ellipse (SDE) and Linear Regression (LR). The analysis revealed significant spatial autocorrelation in property crime incidents, especially in 2016, which indicated a viii clustering pattern. On the other hand, violent crime shows a more complex distribution with significant clustering observed only in 2018. The EHSA analysis with property and violent crime shows transport and road land use and housing and residential showing the most significant values. Linear regression shows that transportation and road land use factors and residential and housing have a strong correlation for property crime while violent crime has a strong correlation with industrial land use and water bodies. Demographic factors show that the male population and the female population have a strong correlation with property crime and violence. These findings emphasize the dynamic nature of crime patterns, influenced by urban development, population, and socio-economic disparities. The implications of the study are divided into five, namely (i). increasing the effectiveness of the hotspots strategy (hotspots policing), (ii). more strategic land use planning, (iii). demographic management in risk areas, (iv). socio-economic impact and community well-being and (v). data-based monitoring and evaluation for crime prevention policies. In conclusion, this study found that property and violent crimes in Kuala Lumpur and Putrajaya show different spatio-temporal distribution patterns, influenced by land use and demographic factors. The use of GIS shows a strong relationship between property crime and transportation and residential land use, while violent crime is more related to industrial land use and water bodies. These results emphasize the importance of data-based crime prevention strategies as well as more strategic land use planning and population management in high-risk areas. | |
| dc.identifier.uri | https://scholarhub.unimas.my/handle/123456789/1181 | |
| dc.language.iso | Bahasa Melayu | |
| dc.publisher | UNIVERSITI MALAYSIA SARAWAK | |
| dc.relation.ispartofseries | Faculty of Social Sciences and Humanities | |
| dc.subject | Emerging hot spot analysis (EHSA), geographic information systems (GIS), linear regression (LR), mean center (MC), property crime, spatial autocorrelation (global moran's i index), standard deviation ellipse (SDE), violent crime | |
| dc.title | Pemodelan Ruang dan Masa Kes Jenayah Harta Benda dan Kekerasan di Wilayah Persekutuan Kuala Lumpur dan Wilayah Persekutuan Putrajaya | |
| dc.type | PhD |