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Due to the advancements in ICT, there's huge amount of data amount of data collected in organizations and law enforcement agencies especially police is not an exception. Therefore this book explores how law enforcement agencies especially those in developing countries can utilize open source Business Intelligence tools to respond to the current issue of big data in their departments which can be utilized to assist them in making data driven decisions for crime management. The researchers developed a Business Intelligence System prototype using Apache Hadoop framework. Also, four different…mehr

Produktbeschreibung
Due to the advancements in ICT, there's huge amount of data amount of data collected in organizations and law enforcement agencies especially police is not an exception. Therefore this book explores how law enforcement agencies especially those in developing countries can utilize open source Business Intelligence tools to respond to the current issue of big data in their departments which can be utilized to assist them in making data driven decisions for crime management. The researchers developed a Business Intelligence System prototype using Apache Hadoop framework. Also, four different classification algorithms that is; decision tree (J48), Naïve Bayes, Multilayer Perceptron and Support Vector Machine were compared to find the most effective algorithm for crime prediction. The study used classification models generated using Waikato Environment for Knowledge Analysis (WEKA). Therefore, this study acts as the benchmark for the implementation of low cost business intelligence and predictive systems in organizations especially police by utilizing open source Business Intelligence tools.
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Autorenporträt
Ahishakiye Emmanuel works as a graduate fellow in the department of computer science at Kyambogo University in Kampala, Uganda. He is a graduate of Msc. Computational Intelligence (UoN) and Bachelor of Information Technology & Computing with first class honors (KYU). He is interested in Big Data, Machine learning and its applications and BI&A.