Data Mining for Potential Customer Segmentation in the Marketing Bank Dataset

Data Mining for Potential Customer Segmentation in the Marketing Bank Dataset Fitriani Maulida Ayu Primary Author mixed material bibliography Purwokerto Universitas Muhammadiyah Purwokerto 2021 e English hlm : 25-32 JUITA : Jurnal Informatika Abstract Direct marketing is an effort made by the Bank to increase sales of its products and services, but the Bank sometimes has to contact a customer or prospective customer more than once to ascertain whether the customer or prospective customer is willing to subscribe to a product or service. To overcome this ineffective process several data mining methods are proposed. This study compares several data mining methods such as Naïve Bayes, K-NN, Random Forest, SVM, J48, AdaBoost J48 which prior to classification the SMOTE pre-processing technique was done in order to eliminate the class imbalance problem in the Bank Marketing dataset instance. The SMOTE + Random Forest method in this study produced the highest accuracy value of 92.61%. Informatika JUITA 20869398 Perpustakaan Teknik UPI YAI JUITA V9N1 Mei 2021 JUITA5a-004 Perpustakaan FT UPI YAI JUITA V9N1 Mei 2021 JUITA5b-004 Perpustakaan FT UPI YAI JUITA V9N1 Mei 2021 JUITA5c-004 Perpustakaan FT UPI YAI JUITA V9N1 Mei 2021 juita.png.png 58427 2022-12-08 14:30:42 2023-01-12 14:20:19 machine generated