Development of a Web-Based Music Recommendation System Based on Facial Expression Using a Convolutional Neural Networks Model

Authors

  • Dimas Aditya Putra Wardhana Department of Robotics and Artificial Intelligence Engineering, Faculty of Engineering, Universitas 17 Agustus 1945 Surabaya
  • Fridy Mandita Department of Robotics and Artificial Intelligence Engineering, Faculty of Engineering, Universitas 17 Agustus 1945 Surabaya
  • Elvianto Dwi Hartono Department of Robotics and Artificial Intelligence Engineering, Faculty of Engineering, Universitas 17 Agustus 1945 Surabaya
  • Dwi Hendra Rosli Department of Information Systems and Technology, Faculty of Engineering, Universitas 17 Agustus 1945 Surabaya
  • Bima Putra Purnawirawan Department of Information Systems and Technology, Faculty of Engineering, Universitas 17 Agustus 1945 Surabaya
  • Muhammad Aldi Syafrillah Hidayat Department of Information Systems and Technology, Faculty of Engineering, Universitas 17 Agustus 1945 Surabaya

DOI:

https://doi.org/10.18196/jet.v9i1.27805

Keywords:

CNN, Face-api.js, Facial expression, Music recommendation, Web

Abstract

This research presents the development of a web-based music recommendation system that uses facial expression recognition to match songs with users' emotional states. Real-time facial detection and expression classification are conducted in the browser using two CNN models implemented via the face-api.js library. Each classified expression is mapped to a specific music genre, and relevant songs are retrieved using the SoundCloud API. The system was evaluated through two aspects, accuracy and user satisfaction. Accuracy was measured using a dichotomous questionnaire, with results showing that 91% of users agreed that the recommended songs reflected their current emotions. User satisfaction was also assessed using a similar questionnaire and reached 86%, indicating a high level of comfort and relevance in the user experience. Compared to previous studies that used Likert scales, this study offers a different yet equally effective evaluation approach. The findings suggest that integrating facial expression recognition into music recommendation systems can provide a practical and user-friendly way to support emotional regulation through music.

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Published

2025-06-30

How to Cite

Wardhana, D. A. P., Mandita, F., Dwi Hartono, E. ., Rosli, D. H., Purnawirawan, B. P., & Hidayat, M. A. S. (2025). Development of a Web-Based Music Recommendation System Based on Facial Expression Using a Convolutional Neural Networks Model. Journal of Electrical Technology UMY, 9(1), 39–44. https://doi.org/10.18196/jet.v9i1.27805

Issue

Vol. 9 No. 1 (2025): June

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Articles

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