Churn Prediction Analysis Of Customer Ferry Operator "Batamfast" Using Machine Learn-Ing With Supervised Classification Model - Ryan Tri Pamungkas; Nenden Siti Fatonah; Gerry Firmansyah; Budi Tjahjono (Eduvest - Journal of Universal Studies, 2025)
BatamFast is the first ferry operator in Batam and has been serving international routes to Singapore and Malaysia since 1985. Until 2010, BatamFast was the only ferry operator in Batam. However, since 2011, competitors such as Sindo Ferry, Horizon Ferry, and Majestic have emerged, increasing competition to four ferry operators in Batam by 2024. This study aims to measure the churn rate of BatamFast customers and identify the factors causing it using machine learning prediction models such as Random Forest, XGBoost, and Gradient Boosting. In addition to churn prediction, feature importance analysis was conducted to determine the significant features influencing customer decisions. The results indicate that XGBoost is the best model compared to Random Forest and Gradient Boosting. Key factors for churn are customer category, payment method, and booking mode. These findings are expected to help BatamFast reduce churn, improve customer satisfaction, and strengthen its competitive position in the international ferry market.