A Geospatial Analysis of Crimes Patterns in Niger Republic Using Hotspots and K-Means Cluster
DOI:
https://doi.org/10.56919/usci.2542.018Keywords:
Niger Republic, Crime, Hotspot, Cluster, Elbow curve, k-meansAbstract
Study’s Excerpt:
• Crime patterns in Niger were analyzed using crime maps and k-means clustering techniques.
• 61.53% of crime hotspots are in the west, bordering Mali, Burkina Faso, and Benin Republic.
• Southern regions (33.33%) face crimes like rebellion and counterfeiting near Nigeria's border.
• Northern hotspots (15.38%) show illegal arms and corruption near Libya, Chad, and Algeria.
• Study suggests cross-border security and optimized law enforcement in high-crime clusters.
Full Abstract:
This study is an investigation of some crimes in the Niger Republic. The methods consist of determining the crime patterns using crime maps and cluster analysis (k-means). It was observed from the hotspot analysis that 61.53% of the crimes like violence or assault, narcotics, rebellion, murder, counterfeit money, scam, stealing, and abuse of confidence are observed in the western part of the country that has a border with Mali Republic, Burkina Faso, Benin republic. 33.33% of the hotspots are observed in the southern part of the country with a border with Nigeria and concern crimes like recels, rebellion, counterfeit money, and criminal association. 15.38% of the hotspots are observed in the north that have borders with Libya, Chad, and Algeria and are concerned with crimes like Illegal arms possession and corruption. For the k-means cluster, the optimum clusters were determined first using the elbow method. It was observed that most clusters have optimum numbers of four and five except the embezzlement crime type, which has three clusters. Based on the above, there is a need to strengthen cross-border security collaboration, optimize resource allocation in high-risk regions, and enhance law enforcement efforts.
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