Spatial Clustering for Narcotics-Related Arrests in Malaysia

Authors

  • ‘Ulya Abdul Rahim Deanery Office, Faculty of Medicine, Universiti Kebangsaan Malaysia, MALAYSIA
  • Razik Ridzuan Mohd Tajuddin Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, MALAYSIA
  • Lim Choong Wei Narcotics Crime Investigation, Department Royal Malaysia Police Headquarters, MALAYSIA
  • Ahmad Azwan Amin Nordin Narcotics Crime Investigation, Department Royal Malaysia Police Headquarters, MALAYSIA
  • Mohammad Kassim Department of Chemical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, MALAYSIA
  • Mohd Firdaus-Raih Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, MALAYSIA

DOI:

https://doi.org/10.17576/jqma.22si.2026.01

Keywords:

crime distribution pattern, Getis-Ord Gi*, hot spots analysis, Moran’s I index, narcotics arrests, spatial autocorrelation

Abstract

Malaysia’s proximity to the Golden Triangle has made it highly susceptible to narcotics crimes. Thus, the purpose of this research is to identify the spatial clustering and the hot spots of narcotics-related offences – distribution, possession, and positive urine. Using over 100,000 arrest records obtained from the Royal Malaysia Police for the year 2022, spatial autocorrelation was analyzed using Moran’s  and Getis-Ord . The results indicated significant positive spatial autocorrelation for all three offences, and among them, the distribution offences tended to cluster more than the other two offences. Furthermore, the hot spots for the distribution and possession offences were concentrated in the northern as well as central regions of Peninsular Malaysia, while the hotspots for positive urine offences were primarily located in the east coast region of Peninsular Malaysia. Sabah and Sarawak exhibited weak or insignificant clustering, suggesting limited spatial concentration of arrests for all three offences. These findings highlight the need for geographically targeted enforcement strategies and provide spatial intelligence that supports data-driven decision-making in narcotics prevention and rehabilitation policy planning.

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Published

31-05-2026

How to Cite

Rahim, ‘Ulya A., Tajuddin, R. R. M., Wei, L. C., Nordin, A. A. A., Kassim , M., & Firdaus-Raih, M. (2026). Spatial Clustering for Narcotics-Related Arrests in Malaysia. Journal of Quality Measurement and Analysis, 22(SI), 1–12. https://doi.org/10.17576/jqma.22si.2026.01