Predicting Customer Loyalty by Using Na?ve Bayes
Abstract: The effort to increase customer loyalty is by predicting whether the customer is loyal or not. To carry out company development, a customer development strategy is needed, while to carry out customer development strategies can be done using a data mining approach including classification of customers with the method of naive bayes. This study aims to predict consumer loyalty to telecommunication service products. the method used is CRIPS-DM through the stages of business understanding, understanding data, data preparation, modeling, evaluation and development. The algorithm used for prediction is the Naive Bayes algorithm. The results obtained from this study are customer classification models that can help in customer loyalty.
Keywords: Nave Bayes, CRISP-DM, Customer Loyalty, Prediction
How to Cite?: Teguh Iman Hermanto, Muhamad Agus Sunandar, "Predicting Customer Loyalty by Using Na?ve Bayes", Volume 9 Issue 1, January 2020, International Journal of Science and Research (IJSR), Pages: 1064-1067, https://www.ijsr.net/getabstract.php?paperid=ART20204202, DOI: https://dx.doi.org/10.21275/ART20204202