A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry - Nilam Nur Amir, Sjarif; Muhammad Rusydi, Mohd Yusof; Doris Hooi, Ten Wong; Suraya, Ya’akob; Roslina, Ibrahim; Mohd Zamri, Osman (Soft Computing Research Group, UTM Malaysia, 2019)
Customer churn in telecommunication industry is actually a serious issue. The Telco company needs to have a churn prediction model to prevent their customer from moving to another telco. Therefore, the objective of this paper is to propose the customer churn prediction using Pearson Correlation and K Nearest Neighbor algorithm. The algorithm is validated via training and testing dataset with the ratio 70:30. Based on experiment, the result shows that the K Nearest Neighbor algorithm performs well compared to the others with the accuracy for training is 80.45% and testing 97.78%.