Spatial hotspot patterns of a home burglary in Penang
This study is based on property crime cases in the Northeast of Penang using GIS application for crime prevention. Studies based on the spatial elements showed that GIS application was able to reduce the crime issues. The purpose of this study is to identify the hotspots of home burglary based on...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2020
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| Online Access: | http://journalarticle.ukm.my/15813/ http://journalarticle.ukm.my/15813/1/37724-127892-1-PB.pdf |
| Summary: | This study is based on property crime cases in the Northeast of Penang using GIS application
for crime prevention. Studies based on the spatial elements showed that GIS application was
able to reduce the crime issues. The purpose of this study is to identify the hotspots of home
burglary based on time incident in Penang using GIS spatial statistics. Based on the report of
house burglary cases from 2013 until 2015. Getis Ord Gi* was used to identify the high-risk
areas of home burglary cases based on z-scores and p-values. The analysis shows that the
areas of the hot spot cases of home burglary are the same for night and day incidents. In
2013, the hot spot areas at night were 7 areas, and during the day only 1 incident was
identified. Hot spot increases in 2014 to 9 areas for nighttime incidents while daytime events
also increased to 10 areas. While 2015 showed that the number of hot spots that occurred at
night reduced to 5 areas and daytime incidents also recorded the same number of hot spots
during the night incidents. Hot spot areas also frequently identified in urban areas and high
population density such as Jelutong, Dato Keramat, Tanjung Tokong dan Sungai Nibong. The
result showed that hotspots of home burglary are more concentrated in residential areas with
good road network accessibility. This study can assist the authorities such as the Royal
Malaysia Police (RPM) in preventing and reducing the crime index by using GIS
applications. |
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