OPTIMASI RANDOM FOREST TERHADAP DATA TELCO CUSTOMER CHURN MENGGUNAKAN FIREFLY ALGORITHM - Abril Muhammad Fikar Wijaya, (2024)
Customer churn is the percentage of customers who have stopped or switched using a product/service periodically. The telecommunications industry experiences an average annual churn rate of 30-35%, and acquiring new customers is 5-10 times more expensive than retaining existing ones. Predicting churn can be used to help companies identify churners earlier before customer defection occurs. The objective of this research is to perform classification using the Random Forest method combined with the Firefly Algorithm to enhance accuracy. The classification evaluation results using the confusion matrix show an accuracy of 80,48%, precision of 77%, recall of 82,7%, and an F1-score of 79,71% before optimization. After optimization using the Firefly Algorithm, the accuracy increased to 82,08%, precision to 77,7%, recall to 86,2%, and F1-score to 81,6%.