CHURN ANALISIS PADA DATA PELANGGAN TELEKOMUNIKASI MENGGUNAKAN ENSEMBLE LEARNING - Muthia Nadhira Faladiba; Rizqi Haryastuti (Math Program, Math and Science faculty, Pamulang University, 2023)
Intense competition in broadband services will create high opportunities for consumers to switch providers, such as conditions that arise in competition for SMS, telephone, and internet services. The churn rate is the percentage of consumers who stop subscribing to the service. Ideally, this churn percentage is only 5% – 10%, and if it exceeds this figure, it indicates the company's inability to retain customers. A high churn rate indicates a decline in the cellular operator's market share and affects the company's revenue. Based on these problems, it is necessary to analyze the churn behavior of broadband subscribers to determine the dissatisfaction factors of cellular telecommunications consumers. Then predictions are made for customers who tend to churn from provider companies and determine the characteristics of churn and stay customers. The ensemble method is used to detect churn, which consists of several methods, including random forest, boosting, and super learner. Random Forest is proven to produce the best classification method with an excellent ability to predict customer churn, which is 80.1%, with an average usage time of 3 years.