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All Journal Sainteks JUITA : Jurnal Informatika Proceedings Series on Physical & Formal Sciences
Maulida Ayu Fitriani
Universitas Muhammadiyah Purwokerto
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Mechanical Engineering Medicine & Pharmacology

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Journal : JUITA : Jurnal Informatika

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Data Mining for Potential Customer Segmentation in the Marketing Bank Dataset Maulida Ayu Fitriani; Dany Candra Febrianto
JUITA : Jurnal Informatika JUITA Vol. 9 No. 1, May 2021
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (845.282 KB) | DOI: 10.30595/juita.v9i1.7983

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%.
Co-Authors Andono Pamungkas Warih Dany Candra Febrianto Lukni Maulana Mohamad Sugeng Pangestu Mr. Harjono, Mr.