PENERAPAN KLASIFIKASI BACKPROPAGATION TERHADAP DATA TELCO CUSTOMER CHURN DENGAN SELEKSI FITUR FORWARD SELECTION - Deby Rianasari (2022)
This research is motivated by the impact of the Covid 19 pandemic which encourages people to carry out activities from home or Work From Home (WFH). So that increasingly intensive internet usage will result in dynamic customer churn to switch services from one internet connection service provider to another that is more profitable. The purpose of this research is to classify the telco customer churn data. The dataset used is from Kaggle.com. This research uses backpropagation algorithm for classification and confusion matrix for evaluation. This research also applies forward selection to get the relevant features. In this study, an accuracy of 78.79%, precision of 82.51%, and recall of 81.10% of 15 relevant features resulted.