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All Journal Jurnal Pengabdian Masyarakat dan Riset Pendidikan
Prakoso, Adhimas
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Humanities Education Languange, Linguistic, Communication & Media Mathematics Other

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Prediksi Churn Pelanggan Telekomunikasi Menggunakan Metode Supervised Learning dengan Random Forest dan XGBoost: Penelitian Prakoso, Adhimas; Nugroho, Sandra Bagus; Nugraha, Naufal Aqiil; Ferdiansyah, Fendi; Budiawan, Imam; Desmulyanti, Desmulyanti
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 3 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 3 (Januari 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i3.5079

Abstract

Customer churn is a major challenge in the telecommunications industry, resulting in revenue losses. Therefore, the ability to predict customers at risk of churn is crucial for preventative measures. This study developed and compared ensemble-based churn prediction models, namely Random Forest and XGBoost, using historical customer data covering demographics, service, and usage aspects, through pre-processing, training, and model evaluation stages. The results show that both models perform well, but XGBoost excels in AUC and F1-Score metrics, indicating better discriminatory ability and precision-recall balance. Feature importance analysis identified key churn factors, such as Monthly Charges and Tenure, which provide a basis for companies to design more focused and effective retention strategies.
Co-Authors Desmulyanti, Desmulyanti Ferdiansyah, Fendi Imam Budiawan Nugraha, Naufal Aqiil Nugroho, Sandra Bagus