Predicting Customer Loyalty Using Data Mining Techniques
نویسندگان
چکیده
This research aimed on prediction of customer loyalty (Non loyal or Loyal) using the application of data mining in microfinance that helps to build a classification model which supports during loan decision making in the organization. In this study a classification model is built based on the loan data obtained from Joshua Multi Purpose Limited Liability Cooperative (JMPLLC). Experiments using ZeroR, Naïve Bayes, and J48 classifier algorithms of the WEKA 3.6.6 software have been conducted using the pre-processed dataset with selected attributes and parameter settings in order to find the optimal model. The classification model J48 with the best accuracy level of 97.83%) is selected to predict customer loyalty class label (Non Loyal or Loyal) and J48 algorithm was employed to generate rules.
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