Architecture of Decision Support System for Crime Visualization

Recently, crime rate in Malaysia is increasing from day to day. If this situation is not monitored and there is no drastic action taken, it may cause many serious problems. Therefore, crime prevention is one of the important components of an overall strategy to reduce crime and to strengthen public security. However, the main challenge faced by all law-enforcement and intelligence-gathering organizations is to analyze the growing volumes of crime data accurately and efficiently in order to make decision for crime prevention. Due to difficulty in decision making for crime prevention, Decision Support System (DSS) and data mining approach can be used to resolve the problem. Now-a-days, data mining approach has been exposed to be a practical decision-support concept in predicting and preventing crime. As a result, we propose architecture of DSS using visualization technique because it can represent crime data into more comprehensible presentation. The results from this proposed architecture can support the security authority in assessing more suitable law enforcement strategies, increasing the accuracy of selection decision making, as well as improving the use of security authority duty deployment for crime prevention.