Penerapan Algoritma C4.5 untuk Klasifikasi Customer Churn pada Perusahaan Perbankan - Mohammad Aulia Riftiarraafi; Dira Ernawati (Institut Nalanda, 2024)
In the fast-paced digital era, companies must continue to innovate to survive. Especially in banks, retaining customers is the main strategy to be able to project business continuity. The topic of customer retention pays more attention to studying customer patterns that have a tendency to survive. This is very difficult to do because the observed data is generally very complex and amounts to a very large amount. Therefore, computers are a technology that is very suitable to solve these problems. Decision tree is a method that is currently being widely used for research. Moreover, with various versions that continue to be developed such as the C4.5 algorithm, it is a guarantee that this algorithm is still relevant for use in today's industry. Even so, there is still no customer retention prediction research with banking industry case studies. The results of this research test, prove that using the C4.5 algorithm, successfully predict customer churn with an accuracy of 99.77%.