Crime Prediction Using Decision Tree (J48) Classification Algorithm.
There had been an enormous increase in the crime in the recent past. Crimes are a common social problem affecting the quality of life and the economic growth of a society. With the increase of crimes, law enforcement agencies are continuing to demand advanced systems and new approaches to improve cr...
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International Journal of Computer and Information Technology
2018
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| Online Access: | http://hdl.handle.net/20.500.12493/113 |
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| author | Ivan, Niyonzima Emmanuel Ahishakiye Elisha Opiyo Omulo Danison Taremwa |
| author_facet | Ivan, Niyonzima Emmanuel Ahishakiye Elisha Opiyo Omulo Danison Taremwa |
| author_sort | Ivan, Niyonzima |
| collection | KAB-DR |
| description | There had been an enormous increase in the crime in the recent past. Crimes are a common social problem affecting the quality of life and the economic growth of a society. With the increase of crimes, law enforcement agencies are continuing to demand advanced systems and new approaches to improve crime analytics and better protect their communities. Decision tree (J48) applied in the context of law enforcement and intelligence analysis holds the promise of alleviating such problem. Data mining is a way to extract knowledge out of usually large data sets; in other words it is an approach to discover hidden relationships among data by using artificial intelligence methods of which decision tree (J48) is inclusive. The wide range of machine learning applications has made it an important field of research. Criminology is one of the most important fields for applying data mining. Criminology is a process that aims to identify crime characteristics. This study considered the development of crime prediction prototype model using decision tree (J48) algorithm because it has been considered as the most efficient machine learning algorithm for prediction of crime data as described in the related literature. From the experimental results, J48 algorithm predicted the unknown category of crime data to the accuracy of 94.25287% which is fair enough for the system to be relied on for prediction of future crimes. |
| format | Article |
| id | oai:idr.kab.ac.ug:20.500.12493-113 |
| institution | KAB-DR |
| publishDate | 2018 |
| publisher | International Journal of Computer and Information Technology |
| record_format | dspace |
| spelling | oai:idr.kab.ac.ug:20.500.12493-1132024-01-17T04:45:41Z Crime Prediction Using Decision Tree (J48) Classification Algorithm. Ivan, Niyonzima Emmanuel Ahishakiye Elisha Opiyo Omulo Danison Taremwa crime prediction; machine learning; decision tree; J48; artificial intelligence; Classification Algorithms. There had been an enormous increase in the crime in the recent past. Crimes are a common social problem affecting the quality of life and the economic growth of a society. With the increase of crimes, law enforcement agencies are continuing to demand advanced systems and new approaches to improve crime analytics and better protect their communities. Decision tree (J48) applied in the context of law enforcement and intelligence analysis holds the promise of alleviating such problem. Data mining is a way to extract knowledge out of usually large data sets; in other words it is an approach to discover hidden relationships among data by using artificial intelligence methods of which decision tree (J48) is inclusive. The wide range of machine learning applications has made it an important field of research. Criminology is one of the most important fields for applying data mining. Criminology is a process that aims to identify crime characteristics. This study considered the development of crime prediction prototype model using decision tree (J48) algorithm because it has been considered as the most efficient machine learning algorithm for prediction of crime data as described in the related literature. From the experimental results, J48 algorithm predicted the unknown category of crime data to the accuracy of 94.25287% which is fair enough for the system to be relied on for prediction of future crimes. Kabale University 2018-11-01T09:29:13Z 2018-11-01T09:29:13Z 2017 Article Niyonzima, I. Crime Prediction Using Decision Tree (J48) Classification Algorithm .Journal of Computer and Information Technology (ISSN: 2279 – 0764) Volume 06 – Issue 03, May 2017 http://hdl.handle.net/20.500.12493/113 application/pdf International Journal of Computer and Information Technology |
| spellingShingle | crime prediction; machine learning; decision tree; J48; artificial intelligence; Classification Algorithms. Ivan, Niyonzima Emmanuel Ahishakiye Elisha Opiyo Omulo Danison Taremwa Crime Prediction Using Decision Tree (J48) Classification Algorithm. |
| title | Crime Prediction Using Decision Tree (J48) Classification Algorithm. |
| title_full | Crime Prediction Using Decision Tree (J48) Classification Algorithm. |
| title_fullStr | Crime Prediction Using Decision Tree (J48) Classification Algorithm. |
| title_full_unstemmed | Crime Prediction Using Decision Tree (J48) Classification Algorithm. |
| title_short | Crime Prediction Using Decision Tree (J48) Classification Algorithm. |
| title_sort | crime prediction using decision tree j48 classification algorithm |
| topic | crime prediction; machine learning; decision tree; J48; artificial intelligence; Classification Algorithms. |
| url | http://hdl.handle.net/20.500.12493/113 |
| work_keys_str_mv | AT ivanniyonzima crimepredictionusingdecisiontreej48classificationalgorithm AT emmanuelahishakiye crimepredictionusingdecisiontreej48classificationalgorithm AT elishaopiyoomulo crimepredictionusingdecisiontreej48classificationalgorithm AT danisontaremwa crimepredictionusingdecisiontreej48classificationalgorithm |