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Information Journal Paper

Title

CLASSIFICATION OF INTERNET BANKING CUSTOMERS USING DATA MINING ALGORITHMS

Pages

  71-90

Abstract

 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 an 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 comparison with the 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 discovered patterns in order to have a better understanding of what customers really desire.

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    Cite

    APA: Copy

    RADFAR, REZA, NEZAFATI, NAVID, & YOUSEFI ASLI, SAEID. (2014). CLASSIFICATION OF INTERNET BANKING CUSTOMERS USING DATA MINING ALGORITHMS. JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT, 6(1), 71-90. SID. https://sid.ir/paper/140429/en

    Vancouver: Copy

    RADFAR REZA, NEZAFATI NAVID, YOUSEFI ASLI SAEID. CLASSIFICATION OF INTERNET BANKING CUSTOMERS USING DATA MINING ALGORITHMS. JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT[Internet]. 2014;6(1):71-90. Available from: https://sid.ir/paper/140429/en

    IEEE: Copy

    REZA RADFAR, NAVID NEZAFATI, and SAEID YOUSEFI ASLI, “CLASSIFICATION OF INTERNET BANKING CUSTOMERS USING DATA MINING ALGORITHMS,” JOURNAL OF INFORMATION TECHNOLOGY MANAGEMENT, vol. 6, no. 1, pp. 71–90, 2014, [Online]. Available: https://sid.ir/paper/140429/en

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