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Radfar, Reza, Nezafati, Navid, Yousefi Asli, Saeid. (1393). Classification of Internet banking customers using data mining algorithms. , 6(1), 71-90. doi: 10.22059/jitm.2014.50051
Reza Radfar; Navid Nezafati; Saeid Yousefi Asli. "Classification of Internet banking customers using data mining algorithms". , 6, 1, 1393, 71-90. doi: 10.22059/jitm.2014.50051
Radfar, Reza, Nezafati, Navid, Yousefi Asli, Saeid. (1393). 'Classification of Internet banking customers using data mining algorithms', , 6(1), pp. 71-90. doi: 10.22059/jitm.2014.50051
Radfar, Reza, Nezafati, Navid, Yousefi Asli, Saeid. Classification of Internet banking customers using data mining algorithms. , 1393; 6(1): 71-90. doi: 10.22059/jitm.2014.50051

Classification of Internet banking customers using data mining algorithms

Journal of Information Technology Management
مقاله 4، دوره 6، شماره 1، تیر 2014، صفحه 71-90    اصل مقاله (480.19 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/jitm.2014.50051
نویسندگان
Reza Radfar1؛ Navid Nezafati2؛ Saeid Yousefi Asli* 3
1Associate Prof., Faculty of Management and Economics, Science and Research Branch Islamic Azad University, Tehran, Iran
2Assistant Prof., Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran
3MSc. in Information Technology Management, Azad University, E Campus, Tehran, Iran.
چکیده
Classifying customers using data mining algorithms, enables banks to keep old customers loyality while attracting new ones. Using decision tree as a data mining technique, we can optimize customer classification provided that the appropriate decision tree is selected. In this article we have presented an appropriate model to classify customers who use internet banking service. The model is developed based on CRISP-DM standard and we have used real data of Sina bank’s Internet bank. In compare to other decision trees, ours is based on both optimization and accuracy factors that recognizes new potential internet banking customers using a three level classification, which is low/medium and high. This is a practical, documentary-based research. Mining customer rules enables managers to make policies based on found out patterns in order to have a better perception of what customers really desire.
کلیدواژه‌ها
Data Mining؛ Decision Tree؛ Classification؛ E-Banking
آمار
تعداد مشاهده مقاله: 5,241
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