There had been an enormous increase in the crime in the recent past. Crimes are a common social p... more 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 o...
Information shared is exposed to threats of confidentiality, integrity and availability needed fo... more Information shared is exposed to threats of confidentiality, integrity and availability needed for decision making in organizations. A case study was carried out at Kabale District local Government where interviews and questionnaires were administered to purposively selected elements of the study. The findings revealed that the information shared within the organization is exposed to potential threats that can put the organization’s information at a risk of being accessed by unauthorized users. The following factors for securing information were identified and used in the development of a secure application for information sharing in organizations. These factors include; denying unauthorized staff and other individuals from gaining access to personal data, passwords to be treated as private to the individual, secure disposal of information, paper files to store in secure locations and only accessed by those who need to use them. In this application, the information is encoded using ...
Law Enforcement agencies are faced with a problem of effectively predicting the likelihood of cri... more Law Enforcement agencies are faced with a problem of effectively predicting the likelihood of crime happening given the past crime data which would otherwise help them to do so. There is a need to identify the most efficient algorithm that can be used in crime prediction given the past crime data. In this research, Business intelligence techniques considered was based on supervised learning (Classification) techniques given that labeled training data was available. 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). Manual method of attribute selection was used; this is because it works well when there is large number of attributes. The dataset was acquired from UCI machine learning repository website with a title ‘Crime and Comm...
—There had been an enormous increase in the crime in the recent past. Crimes are a common social ... more —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.
Law Enforcement agencies are faced with a problem of effectively predicting the likelihood of cri... more Law Enforcement agencies are faced with a problem of effectively predicting the likelihood of crime happening given the past crime data which would otherwise help them to do so. There is a need to identify the most efficient algorithm that can be used in crime prediction given the past crime data. In this research, Business intelligence techniques considered was based on supervised learning (Classification) techniques given that labeled training data was available. 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). Manual method of attribute selection was used; this is because it works well when there is large number of attributes. The dataset was acquired from UCI machine learning repository website with a title 'Crime and Communities'. The data set had 128 attributes of which 13 were selected for the study. The study revealed that the accuracy of J48, Naïve bayes, Multilayer perceptron and Support Vector Machine (SMO) is approximately 100%, 89.7989%, 100% and 92.6724%, respectively for both training and test data. Also the execution time in seconds of J48, Naïve bayes, Multilayer perceptron and SVO is 0.06, 0.14, 9.26 and 0.66 respectively using windows7 32 bit. Hence, Decision Tree (J48) out performed Naïve bayes, Multilayer perceptron and Support Vector Machine (SMO) algorithms, and manifested higher performance both in execution time and in accuracy. The scope of this project was to identify the most effective and accurate Business intelligence technique that can be used during crime data mining to provide accurate results.
Information shared is exposed to threats of confidentiality, integrity and availability needed fo... more Information shared is exposed to threats of confidentiality, integrity and availability needed for decision making in organizations. A case study was carried out at Kabale District local Government where interviews and questionnaires were administered to purposively selected elements of the study. The findings revealed that the information shared within the organization is exposed to potential threats that can put the organization's information at a risk of being accessed by unauthorized users. The following factors for securing information were identified and used in the development of a secure application for information sharing in organizations. These factors include; denying unauthorized staff and other individuals from gaining access to personal data, passwords to be treated as private to the individual, secure disposal of information, paper files to store in secure locations and only accessed by those who need to use them. In this application, the information is encoded using crypto-graphical methods that cannot be easily intercepted, such that only the intended recipient is able to receive it in its original format for decoding. This makes information shared secure. The application was tested and validated by a range of stakeholders and it was found secure. For the future work, a survey will be carried out in a range of organizations in order to develop an improved application for information sharing.
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Papers by Ivan Niyonzima