Sistem Rekomendasi Musik Spotify Berbasis Pendekatan Hybrid Alternating Least Square Dan Content-Based Filtering

Andy Hermawan ; Akbar Kanugraha ; Indira Faisa Afgani ; Khaerun Nisa’Tri Safaati ; Mutiara Ayu Alzahra Ramadhani
Modem : Jurnal Informatika dan Sains Teknologi 📅 2026 Vol 4, No 2 🔗 DOI: 10.62951/modem.v4i2.869
Abstract
The exponential growth of digital music catalogs on streaming platforms such as Spotify has made personalized recommendation systems crucial for enhancing user experience. This study develops a hybrid music recommendation system that addresses both warm-user and cold-user scenarios by combining Alternating Least Squares (ALS) collaborative filtering with content-based filtering (CBF) augmented by a popularity component. The dataset consists of 8,549,544 user-track interactions and a master file of 1,204,025 tracks with ten audio features. After preprocessing, users were segmented into 14,880 warm users and 723 cold users based on a five-interaction threshold. The ALS model was trained on the user-item implicit feedback matrix and tuned through grid search over factors, alpha, and regularization. CBF was implemented using cosine similarity on normalized audio features, while popularity scores were applied for new users with insufficient history. Evaluation used Precision@10, Recall@10, and NDCG@10. The final ALS configuration achieved NDCG@10 of 0.1116, representing a 30% improvement over baseline, while the hybrid CBF improved NDCG@10 for cold users from 0.0070 to 0.0201. Findings indicate that adaptive routing among ALS, CBF, and popularity reliably handles different user states, providing a practical foundation for production-grade music recommendation systems.
Keywords
Cold Start; Collaborative Filtering; Content-Based; Hybrid Recommender; Music Streaming
How to Cite

Andy Hermawan, et al. (2026). Sistem Rekomendasi Musik Spotify Berbasis Pendekatan Hybrid Alternating Least Square Dan Content-Based Filtering. Modem : Jurnal Informatika dan Sains Teknologi, 4(2). https://doi.org/10.62951/modem.v4i2.869

Andy Hermawan; Akbar Kanugraha; Indira Faisa Afgani; Khaerun Nisa’Tri Safaati; Mutiara Ayu Alzahra Ramadhani, "Sistem Rekomendasi Musik Spotify Berbasis Pendekatan Hybrid Alternating Least Square Dan Content-Based Filtering," Modem : Jurnal Informatika dan Sains Teknologi, vol. 4, no. 2, 2026.

Andy Hermawan; Akbar Kanugraha; Indira Faisa Afgani; Khaerun Nisa’Tri Safaati; Mutiara Ayu Alzahra Ramadhani. "Sistem Rekomendasi Musik Spotify Berbasis Pendekatan Hybrid Alternating Least Square Dan Content-Based Filtering." Modem : Jurnal Informatika dan Sains Teknologi, vol. 4, no. 2, 2026.

Andy Hermawan; Akbar Kanugraha; Indira Faisa Afgani; Khaerun Nisa’Tri Safaati; Mutiara Ayu Alzahra Ramadhani. "Sistem Rekomendasi Musik Spotify Berbasis Pendekatan Hybrid Alternating Least Square Dan Content-Based Filtering." Modem : Jurnal Informatika dan Sains Teknologi 4, no. 2 (2026).

Andy Hermawan, et al. (2026) 'Sistem Rekomendasi Musik Spotify Berbasis Pendekatan Hybrid Alternating Least Square Dan Content-Based Filtering', Modem : Jurnal Informatika dan Sains Teknologi, 4(2). doi: 10.62951/modem.v4i2.869.

Andy Hermawan; Akbar Kanugraha; Indira Faisa Afgani; Khaerun Nisa’Tri Safaati; Mutiara Ayu Alzahra Ramadhani. Sistem Rekomendasi Musik Spotify Berbasis Pendekatan Hybrid Alternating Least Square Dan Content-Based Filtering. Modem : Jurnal Informatika dan Sains Teknologi. 2026;4(2).

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