Urban Violent Crime Dynamics in Kuala Lumpur and Putrajaya: Utilizing Spatial Temporal Techniques
DOI:
https://doi.org/10.23917/forgeo.v39i1.6456Keywords:
Mean Center (MC), Spatial Analysis, Spatial Autocorrelation, Standard Deviational Ellipse (SDE), Urban Crime Patterns, Violent CrimeAbstract
This paper investigates the patterns of violent crime in Kuala Lumpur and Putrajaya between 2015 and 2020 using advanced spatial analysis techniques, including Spatial Autocorrelation, Standard Deviational Ellipse (SDE), and Mean Centre (MC). The study analyzes the spatial distribution and temporal dynamics of violent crimes, tracks shift in crime hotspots and examines the influence of socio-economic factors on these patterns. Findings reveal that violent crimes predominantly occur in the late afternoon and night, with peak incidents at 3:00 PM (1,830 cases, 8.28%). The study highlights notable shifts in crime hotspots, initially concentrated in commercial districts and gradually expanding to transportation networks and emerging urban areas. The Moran Index values indicate a transition from a near-random pattern in 2015 (-0.002668) to a mild clustering in 2018 (0.032962). Additionally, socio-economic factors, including population density, economic conditions, and the COVID-19 pandemic, significantly impacted crime patterns, leading to changes in crime rates and hotspot locations. These findings are crucial for law enforcement and urban planning, emphasizing the need for adaptive crime prevention strategies that respond to evolving urban challenges, and demonstrating the importance of integrating socio-economic data into spatial crime analysis for comprehensive crime mitigation.
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Copyright (c) 2025 Mr. Mohd Sofian Redzuan, Prof. Gs. Dr. Tarmiji Masron, Ts. Syahrul Nizam Junaini, Prof. Dr. Yoshinari Kimura, Assoc. Prof. Dr. Mohamad Hardyman Barawi, Assoc. Prof. Dr. Mohamad Suhaidi Salleh, Prof. Gs. Dr. Ruslan Rainis, Gs. Azizul Ahmad, Dr. Adibah Yusuf
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