Crime Analysis using K-Means Clustering Algorithm - A Case Study:  Police Departments, Wad Madani, Sudan (2016-2018)

Gais Alhadi Babikir; Tarig Khalid Suliman; Awadallah Mohammed Ahmed

Gais Alhadi Babikir University of Gezira, Wad Madani, Sudan
Tarig Khalid Suliman
Awadallah Mohammed Ahmed Assistant Professor at University of Gezira (Sudan), Computer Science Department

Abstract

In today's world, recently global security is one aspect that has a high priority and importance by politicians and governments around the world, it aims to reduce the occurrence of crimes. Therefore, many studies aimed at knowing the types of crimes, the manner of their occurrence, the search for criminals, study their personal qualities and public behavior since each crime shares the criminals who commit it in certain character traits and patterns. This study aims to find the relationships between crimes and the characteristics of criminals who committed the crimes (such as age, gender, location, and job) in order to help Police Departments to make the right decisions through crime investigation. In this paper, the k-means clustering algorithm has been used as a data mining technique to discover the relationships between crime and criminal characteristics. Where statistical descriptive analysis was used for all processes, also we used WEKA as a tool to implement the k-means algorithm. It should be noted that the data of this study have been collected from three Police Departments in Wad Madani city, Sudan for criminal records for three years (2016, 2017, and 2018). The analysis of the results showed that there are some crimes related to the specific age of criminals. We also found that each region has its own crimes which are different from the other region. Moreover, the most common crimes committed by males: are fraud, scandalous acts, public employee objection, check, and public threat. And, the most common crimes committed by females: are dealing with alcohol, abuse, and slander. Furthermore, the analysis of the result showed that the most common crimes committed by students are sexual, theft, and violence.

Author Biography

Gais Alhadi Babikir, University of Gezira, Wad Madani, Sudan

Dr. Gais Alhadi has completed his PhD from University of Lorraine in Metz, France. He earned a Master’s degree and a Bachelor’s degree in Computer Science from the University of Gezira, Sudan. Currently, Gais is an Assistant Professor at the University of Gezira (Sudan), Computer Science Department and a member of the University Council. He is also the Director of Computer and Information Technology Center - University of Gezira (Sudan) after he was the head of the Computer Science Department and director of the university's website.
Gais has scientific activity in Operational Research. More precisely, his contributions are related to the design of exact and approximate algorithms with guaranteed performance for the NP-hard combinatorial problems. Such problems are mainly related to the scheduling theory. Gais has skills in using a variety of computer programming languages and scripts with particular expertise in database design and management, software development, and website design

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