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Atsa’am DD, Gbaden T, Wario R. Association Rules on Attributes of Illicit Drugs, Suspect’s Demographics and Offence Categories. JOURNAL OF DRUG ISSUES 2022. [DOI: 10.1177/00220426221140010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Association rules mining technique was employed to extract 6 rules that show the co-occurrences of the attributes on illicit drug types, suspects’ demographics, and categories of drug offences. A dataset on 262 arrestees of various drug offences was utilized for rules extraction using the apriori algorithm. The rules reveal the different levels of involvement with various illicit drugs by suspects of varying ages. The established rules provide a form of drug suspects segmentation which could guide how drug control and intervention programs are designed and deployed. Further, the rules could serve as a reference tool for security agents when dealing with drug suspects and offenders.
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Affiliation(s)
- Donald Douglas Atsa’am
- Department of Computer Science and Informatics, Faculty of Natural and Agricultural Sciences, University of the Free State, South Africa
| | - Terlumun Gbaden
- Department of Computer Science, College of Physical Sciences, Joseph Sarwuan Tarka University, Makurdi, Nigeria
| | - Ruth Wario
- Department of Computer Science and Informatics, Faculty of Natural and Agricultural Sciences, University of the Free State, South Africa
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