DATA MINING UNTUK ANALISA TINGKAT KEJAHATAN JALANAN DENGAN ALGORITMA ASSOCIATION RULE METODE APRIORI (Studi Kasus Di Polsekta Medan Sunggal)

Abstract

Data mining, or often referred to as knowledge discovery in databases (KDD) is acollection of activities that include, the use of historical data to discoverregularities,patterns or relationships in large data. In this thesis data mining is used to analyze the level of street crime. This technique aims to provide information about the area and the potential for street crime that can assist the police in anticipation of a crime that often appears, was done by using analysis of habit how often do street crimes. Detection of crime which often occur simultaneously called association rule (association rules). Algorithm that can be used to find Apriori association rule is. Apriori algorithm is the association rule mining through multiple scan data sets, find a relationship between the variables and present a strong rule in a large database. The data is taken as a case study of street crime data Polsekta Sunggal Medan. Test data using data mining software Tanagra and Microsoft Excel for data storage. Results from a combination of patterns and rules obtained to provide information that could be followed up or contain important information that can be utilized to enhance the security and sensitivity of street crime.