Analisis Data Bank Direct Marketing dengan Perbandingan Klasifikasi Data Mining Berbasis Optimize Selection (Evolutionary)

In determining marketing strategies, the bank performs a classification from customer database, database will be analyzed by decision maker and this is not easy for maker, because of complexity vast data many attributes owned, so that it becomes an obstacle obstacle. in making. This course can have negative effect on company's business processes there delays strategies. Data mining method classify large to determine level accuracy database. overcoming these problems, necessary do analysis owned company. For reason, study process carried out with Bank Direct Marketing dataset taken UCI Machine Learning Repository web, using Naïve Bayes algorithm, K-Nearest Neighbor, Support Vector Optimize Selection (Evolutionary) optimization, calculation application. namely Rapidminer 5.3, find highest value algorithm. Test 10-fold cross validation. study, results were obtained algorithm 90.18%, then Neighbor 86.66%, 89.40%.