Mapping the Property Crime Spatial Pattern in Selangor using Social Media Data Mining and GIS

Authors

  • Siti Hawa Mat Sapuan SWM Environment Sdn. Bhd., No. 3&3A, Jalan Kencana 1 A/25, Taman Pura Kencana, 83300 Batu Pahat, Johor, Malaysia
  • Nafisah Khalid Studies for Surveying Science and Geomatics, Faculty of Built Environment, Universiti Teknologi MARA,40450 Shah Alam, Selangor, Malaysia
  • Maisarah Abdul Halim Studies for Surveying Science and Geomatics, Faculty of Built Environment, Universiti Teknologi MARA,40450 Shah Alam, Selangor, Malaysia
  • Nabilah Naharudin Studies for Surveying Science and Geomatics, Faculty of Built Environment, Universiti Teknologi MARA,40450 Shah Alam, Selangor, Malaysia
  • Ainon Nisa Othman Studies for Surveying Science and Geomatics, Faculty of Built Environment, Universiti Teknologi MARA,40450 Shah Alam, Selangor, Malaysia

DOI:

https://doi.org/10.24191/bej.v22i2.5935

Keywords:

Property Crime, Data Mining, Hotspot Analysis, GIS

Abstract

The previous studies had shown that the information extracted from social media can be utilised in locating offenders, establishing probable cause for warrants, and identifying potential witnesses. By integrating social media data mining with Geographic Information System (GIS) techniques, it is possible to map property crime hotspots based on user-generated content. This approach can provide valuable insights to complement officially reported crime data. Through GIS-based spatial analysis, patterns and distributions of crime can be identified, enabling the detection of high-crime areas or hotspots. The ability of hotspot analysis to present crime concentration across a geographical landscape makes it a powerful and practical tool for law enforcement and urban planning. From this study, the total property crime geocoded data that managed to collect is 488 cases consisting of the snatch, burglary, theft, and car theft crime in Selangor. Each crime case has been analysed for its spatial pattern and distribution where for both snatch and burglary crime exhibits clustering while theft crime gives pattern and distribution of random across the study area. The spatial pattern of each crime show that the southern part of Selangor has more crime cases as compared to northern part of Selangor. The red zones show the areas with a very high value of z score indicate significant spatial clustering The findings would be beneficial to the relevant authorities regarding the underreporting of crime cases.

Author Biographies

Siti Hawa Mat Sapuan, SWM Environment Sdn. Bhd., No. 3&3A, Jalan Kencana 1 A/25, Taman Pura Kencana, 83300 Batu Pahat, Johor, Malaysia

Siti Hawa Mat Sapuan holds a Bachelor’s degree in Surveying Science and Geomatics (Honours) from Universiti Teknologi MARA (UiTM), where she developed a strong foundation in geospatial analysis and land surveying. Currently, she is serving at SWM Environment Sdn. Bhd. She can be contacted by email at hawasapuan97@gmail.com.

Nafisah Khalid, Studies for Surveying Science and Geomatics, Faculty of Built Environment, Universiti Teknologi MARA,40450 Shah Alam, Selangor, Malaysia

Nafisah Khalid is a senior lecturer at the College of Built Environment, Universiti Teknologi MARA (UiTM), Malaysia. She earned her Ph.D. in Built Environment from UiTM in 2017. Her research focuses on applying geospatial technologies to tackle environmental challenges, with particular emphasis on forest management, urban tree mapping, and aboveground biomass estimation. She can be contacted by email at nafisahkhalid@uitm.edu.my.

 

Maisarah Abdul Halim, Studies for Surveying Science and Geomatics, Faculty of Built Environment, Universiti Teknologi MARA,40450 Shah Alam, Selangor, Malaysia

Maisarah Abdul Halim brings over 10 years of experience in the field of Geographic Information Systems (GIS) and surveying, specializing in GIS analysis, spatio-temporal analytics, and data visualization. She holds an MSc in Geographic Information Science from University College London and a Bachelor of Surveying Science and Geomatics (Honors) from Universiti Teknologi MARA, Malaysia. Maisarah's expertise includes developing web-based GIS applications, conducting research in GIS and spatio-temporal analytics, and providing professional training in GIS and surveying. She can be contacted by email at maisarahhalim@uitm.edu.my.

 

Nabilah Naharudin, Studies for Surveying Science and Geomatics, Faculty of Built Environment, Universiti Teknologi MARA,40450 Shah Alam, Selangor, Malaysia

Nabilah Naharudin is currently a Senior Lecturer at the School of Geomatics Science and Natural Resources, College of Built Environment, Universiti Teknologi MARA, Malaysia. Her research interests include GIS, geospatial analysis, Spatial-MCDA and AHP-ANP. She can be contacted by email at nabilahnaharudin1290@uitm.edu.my.

Ainon Nisa Othman, Studies for Surveying Science and Geomatics, Faculty of Built Environment, Universiti Teknologi MARA,40450 Shah Alam, Selangor, Malaysia

Ainon Nisa Othman is a Senior Lecturer at College of Built Environment, Universiti Teknologi MARA specializing in Geographic Information Systems (GIS), remote sensing, underground utility mapping, and multi-criteria decision-making (MCDM). She has published research on various topics including landslide hazard zonation using GIS and MCDM techniques. She can be contacted by email at ainonnisa6941@uitm.edu.my.

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Published

01-07-2025

How to Cite

Mat Sapuan, S. H. ., Khalid, N., Abdul Halim, M., Naharudin, N. ., & Othman, A. N. . (2025). Mapping the Property Crime Spatial Pattern in Selangor using Social Media Data Mining and GIS. Built Environment Journal, 22(2). https://doi.org/10.24191/bej.v22i2.5935

Issue

Vol. 22 No. 2 (2025): Built Environment Journal

Section

Articles

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Copyright (c) 2025 Siti Hawa Mat Sapuan, Nafisah Khalid, Maisarah Abdul Halim, Nabilah Naharudin, Ainon Nisa Othman

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