Analysing Property Crime Movements in Urban Malaysia: The Role of Standard Deviational Ellipse (SDE) and Mean Centre (MC) Techniques
Property crime poses a significant threat to urban safety, socioeconomic stability, and sustainable development in Malaysia’s rapidly urbanising cities. However, the lack of advanced spatial analyses has limited the understanding of crime pattern evolution. This study investigates the spatial and te...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
UMT Press
2025
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/51176/1/JSSM-V20-N12-Article-3-Draf-2.pdf http://ir.unimas.my/id/eprint/51176/ https://jssm.umt.edu.my/archive/ https://doi.org/10.46754/jssm.2025.12.003 |
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| Summary: | Property crime poses a significant threat to urban safety, socioeconomic stability, and sustainable development in Malaysia’s rapidly urbanising cities. However, the lack of advanced spatial analyses has limited the understanding of crime pattern evolution. This study investigates the spatial and temporal dynamics of 58,130 property crime incidents in Kuala Lumpur and Putrajaya from 2015 to 2020, employing Standard Deviational Ellipse (SDE) and Mean Centre (MC) techniques to map directional trends and identify crime hotspots. The analysis reveals strong diurnal patterns, with peak incidents at 8:00 p.m. (8.12%) and the lowest at 4:00 a.m. (0.61%), consistent with routine activity theory. Spatially, crime shifted from commercial areas (e.g., Jalan Tuanku Abdul Rahman) to transportation corridors (e.g., Jalan Raja Laut) and re-converged in urban commercial hubs (e.g., Pertama Complex) by 2020. The SDE area varied from 100.82 km² to 117.01 km², with increased dispersion and rotation in 2020, reflecting socioeconomic disruptions,
notably from the COVID-19 pandemic. Although comprehensive statistical modelling of socioeconomic variables was limited, observable shifts suggest economic vulnerability and urban development as key drivers. The findings highlight the utility of spatial analytics for predictive policing and evidence-based urban planning, enabling more effective crime
prevention and resilient city design. |
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