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Fersellia, Fersellia
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Prediction Customer Loyalty Using Random Forest Algorithm on Shopee Reviews Saputra, Ferdi; Fersellia, Fersellia
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 1 (2025): March 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v27i1.7940

Abstract

This research develops a Shopee customer loyalty prediction model using Random Forest algorithm, utilizing customer reviews from Google Play Store. One of the key issues in e-commerce is maintaining customer loyalty amidst intense competition, so it is important to identify loyal customers and understand the factors that influence their commitment. This study involves data collection through web scraping, data cleaning, loyalty labeling, and Random Forest-based prediction model building and evaluation. The evaluation process was conducted using a confusion matrix to measure accuracy, precision, recall, and F1-score. The model classified customers into loyal, neutral, and disloyal categories, with an overall accuracy of 97%. The model showed precision, recall, and F1-score of 0.98 for loyal customers, and 0.99, 1.00, and 0.99 for disloyal customers. However, identification of neutral customers is still a challenge, with precision, recall, and F1-score of 0.92, 0.85, and 0.88, respectively. The results of this study provide strategic insights for Shopee in improving customer retention strategies and demonstrate the effectiveness of the Random Forest algorithm in analyzing review data.
Co-Authors AA Sudharmawan, AA Anggoro, Tri Citra Wuladari Ema Utami Endang Wahyuningsih Endang Wahyuningsih Fachri, Fahmi Fadjeri, Akhmad Fahmi Fachri, Fahmi Fachri Fina Hanifa Hidayati Idris, Achmad Choerul Umam Nur Lutfiyani, Anisa Muflih, Ghufron Zaida Mustikaningsih, Ajar Nugroho, Mei Aldi Nurchayati, Anisa Dwi Rizki Yanuar Rokhayati, Rani Salikhan, Salikhan Saputra, Ferdi Sofiyah, Elfa Sulma Safinatus Taufik Hidayat