The Application of Fuzzy-Rough Set Decision Tree for Credit Rating
Sarah Tahira Soetrisno, Grizelda Wahyuningtyas, Imam Mukhlash · 2015
Fuzzy decision tree is a data mining method which is a combination of fuzzy logic and decision tree. Integration of fuzzy logic concept in the decision tree intended to represent an uncertain condition and a very complex model. Construction of fuzzy decision tree using fuzzy rough techniques was done by looking under the value and significance levels for each factor to be analyzed. The problems discussed is to predict the potential success of a prospective customer credit through fuzzy decision tree by using the history data of existing credit customers. Parameters used are the amount of the credit, loan, mortgage interest (rate), customer turn over, and the long passage of the customer's business. From the simulation results, it is obtained a fuzzy decision tree model with an accuracy of 83%. With this application, a decision maker can determine the potential of prospective customers and prevent the occurrence of credit fail.