The Application of Fuzzy-Rough Set Decision Tree for Credit Rating
Abstract
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. Â 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.
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References
Han, J. and Kamber, M. (2011). Data Mining Concepts and Techniques. Morgan Kaufman: USA.
Aprianti, Winda and Imam Mukhlash (2014), The application of rough set and fuzzy rough set based algorithm to classify incomplete meteorological data, Proceedings of International Conference on Data and Software Engineering (ICoDSE), http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7062674
Olaru, C. and Wehenkel, L. (2003). A Complete Fuzzy Decision Tree Technique. Journal of Fuzzy Sets and Systems.
Hullermeier, E. and Vanderlooy, S. (2010). Why Fuzzy Decision Trees are Good Rankers. Fuzzy Systems paper in IEEE.
Lahsasna, A., Ainon, R.N. and Wah, T.Y. (2010). Credit Scoring Models Using Soft Computing Methods: A Survey. The International Arab Journal of Information Technology. 7( 2).
Wahyu, D. and Widyanto, M.R. (2011). Studi Perbandingan Metode Pohon Keputusan dan Pohon Keputusan Fuzzy pada Klasifikasi Penutup Lahan. Jurnal Ilmiah KURSOR. 6(1).
Zhai, J.H. (2010). Fuzzy Decision Tree Based on Fuzzy-rough Technique. Fuzzy Systems paper in Springer.
Smith III and James, F. (2010). Fuzzy Logic Resource Manager: Evolving Fuzzy Decision Tree Structure that Adapts in Real-Time. Naval Research Laboratory. Code 5741. Washington, D.C.
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