The Implementation of hybrid methods in data mining for Predicting customer churn in the telecommunications sector

Restu Herdian Herdian (Bina Nusantara University, Indonesia)
Abba Suganda Girsang (Bina Nusantara University, Indonesia)

Jurnal Mantik
Vol. 7 No. 1 (2023): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)

In recent years, the telecommunication industry is growth and become very competitive where has reached the point maintaining customer is very essential than acquiring new customer. And the two key factor for maintaining customer, the first is defining the segment of customer want to churn and the second is accuracy of predictive model. In this article we propose the hybrid model based on decision tree and artificial neural network (ANN) with the two stages of process to answer the problem of maintaining customer, the first is a segmentation phase with decision rules and the second is a prediction phase with artificial neural network (ANN). Our finding in benchmarked against the previous algorithms (decision tree and ANN) with the AUC metrics show the proposed model or hybrid achieves better accuracy and with the comprehensive information of what a drive customer churn