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All Journal Journal of Advanced Technology and Multidiscipline (JATM)
Reizo Nararya Alinandito
Universitas Airlangga
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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User Preference-Based Movie Recommender System Using Decision Tree Method Yutika Amelia Effendi; Reizo Nararya Alinandito; Muhammad Akmal Rinaldy; Rizka Dwi Nurwicaksanti; Muhammad Daffa Tristan
Journal of Advanced Technology and Multidiscipline Vol. 5 No. 1 (2026): Journal of Advanced Technology and Multidiscipline
Publisher : Faculty of Advanced Technology and Multidiscipline Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jatm.v5i1.85027

Abstract

This study presents the design and implementation of a movie recommendation system aimed at improving content discovery amidst the rapid growth of the film industry. The system utilizes the Decision Tree Algorithm, a non-parametric supervised learning technique known for its hierarchical structure and interpretability, to provide personalized movie suggestions. Empirical evaluation demonstrates the Decision Tree's effectiveness, achieving a Mean Absolute Error (MAE) of 0.942, which outperforms a Collaborative Filtering baseline (MAE 1.242). This research highlights the practical utility of Decision Trees in enhancing recommendation accuracy and efficiency, contributing to transparent and effective AI systems for personalized content discovery.
Co-Authors Muhammad Akmal Rinaldy Muhammad Daffa Tristan Rizka Dwi Nurwicaksanti Yutika Amelia Effendi