CLASSIFICATION OF CUSTOMERS BASED ON BEHAVIOR, USING DATA MINING TECHNIQUES

Trần Thị Xuân; Nguyễn Văn Núi

doi:10.34238/tnu-jst.4954

CLASSIFICATION OF CUSTOMERS BASED ON BEHAVIOR, USING DATA MINING TECHNIQUES

About this article

Received: 08/09/21 Revised: 09/11/21 Published: 10/11/21

Authors

1. Tran Thi Xuan, TNU - University of Economics and Business Administration
2. Nguyen Van Nui , TNU - University of Information and Communication Technology

Abstract

Data mining (DM) is a popular technique, and has been used to extract useful information from existing data, thereby assisting in making decisions that benefit the future. In this paper, the authors focus on the problem of customer classification, thereby helping to find a group of potential customers using Decision Tree J48, Naïve Bayes Classification and Random Forest. The results show that the model based on the Decision Tree gives highest accuracy and feasibility in predicting customer behavior. This result is expected to be an effective suggestion for an approach that can effectively help researchers related to finding a group of potential customers in the banking field.

Keywords

Customer classification; Data mining; CMR; Naïve Bayes Classification; Decision Tree; Random Forest

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References

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DOI: https://doi.org/10.34238/tnu-jst.4954

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