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All Journal Siyasatuna Jurnal Ilmiyah Mahasiswa Siyasah Syariyyah JT-IBSI (Jurnal Teknik Ibnu Sina) Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat
Dahnial
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Journal : JT-IBSI (Jurnal Teknik Ibnu Sina)

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PERBANDINGAN METODE JARINGAN SYARAF TIRUAN DAN POHON KEPUTUSAN UNTUK PREDIKSI CHURN Dahnial
Jurnal Teknik Ibnu Sina (JT-IBSI) Vol. 8 No. 02 (2023): JT-IBSI (Jurnal Teknik Ibnu Sina)
Publisher : Fakultas Teknik Universitas Ibnu Sina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36352/jt-ibsi.v8i02.725

Abstract

Churn is a customer's behaviour to quit using product or service and then move to another company. Customer churn is serious problem that must be handled to keep company survive. Handling of churn customers starts from predicting which customers will churn. One approach in predicting customer churn is data mining. This study compares two classification methods in data mining namely artificial neural networks and decision trees in banking industry case. The result showed that the artificial neural network has accuracy 86% and precision 71%, which is better than the decision tree. However, the decision tree has a better recall value than the artificial neural network, which is 58%..
Co-Authors Deffi Haryani Dita Marisa Putri Kurniati Kurniati Marina Malian