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All Journal Jurnas Nasional Teknologi dan Sistem Informasi JOIV : International Journal on Informatics Visualization Seminar Nasional Teknologi Informasi Komunikasi dan Industri Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOISIE (Journal Of Information Systems And Informatics Engineering) Journal of Applied Engineering and Technological Science (JAETS) International Journal of Electrical, Energy and Power System Engineering (IJEEPSE) Unri Conference Series: Community Engagement Seandanan: Jurnal Pengabdian pada Masyarakat Journal of Applied Business and Technology
Adiya, M. Hasmil
Institut Bisnis Dan Teknologi Pelita Indonesia
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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PREDICTING RIDE-HAILING CUSTOMER LOYALTY USING RANDOM FOREST AND PRINCIPAL COMPONENT ANALYSIS Viola Viola; Dewi Nasien; M. Hasmil Adiya
JOISIE (Journal Of Information Systems And Informatics Engineering) Vol. 10 No. 1 (2026)
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/joisie.v10i1.5998

Abstract

Customer loyalty is important for ride-hailing companies because users can easily change from one platform to another. This study applied Random Forest to classify the loyalty of ride-hailing users in Pekanbaru, Indonesia, and examined whether Principal Component Analysis (PCA) improved the result. The original dataset contained 200 questionnaire records covering demographic characteristics, trust, innovation, service quality, customer satisfaction, and customer loyalty. After seven duplicate records were removed, 193 records were divided into 154 training records and 39 test records. The baseline model achieved 0.67 accuracy and a weighted F1-score of 0.67. The best PCA model retained 80% of the variance, used seven trees, and achieved 0.69 accuracy with a weighted F1-score of 0.68. Service quality, customer satisfaction, trust, and innovation were the most important predictors. The model performed best for the Loyal class, while the smaller classes were harder to identify. One loyalty category was absent from the test set; therefore, the findings should be treated as an initial result rather than a model ready for operational use.
Co-Authors ahmad kamal, ahmad Ahmad Mulyadi Aldo Erianda, Aldo Alyauma Hajjah Angriawan, Sherkhing Azliza Yacob Azurah A. Samah Baharum, Zirawani Butar-Butar, Rio Juan Hendri Dahliyusmanto, Dahliyusmanto Deny Jollyta Desnelita, Yenny Devi Willeam Anggara Devi Willieam Anggara Dewi Nasien Erlin Fajri Adrianto Farkhan, Mochammad Feri Candra Gustientiedina Helly Aroza Siregar Ihsan, M. Nurul Iis Afrianty Ismail, Shahrinaz Jaber, Mustafa Musa Johan Johan Jubair, Mohammed Ahmed M Noval Dwi Pratama Marlim, Yulvia Nora Masyhuri Hamidi, Masyhuri Mochammad Farkhan Mostafa, Salama A Nadira Nurul Atika Rahmadian Yuliendi, Rangga Rianda, Gilang Rida Rahim Roni Sanjaya Siddik, M. Sirait, Andrio Pratama ST, M.A.B, Okto Fenta Riandi Sukabul, Ahmad Suroyo Suroyo Suroyo Suroyo Ummi Sri Rahmadhani Viola Viola Wicaksono, Mahfuzan Hadi Wilda Susanti Willy Andrio Harefa Yulianti, Deni Yusnita Rahayu Zirawani Baharum