Sistem Rekomendasi Musik Berdasarkan Playlist dengan Collaborative Filtering
DOI:
https://doi.org/10.55606/jitek.v5i3.8039Keywords:
collaborative filtering, hybrid model, music recommendation, personalization playlist, recommendation systemAbstract
Modern music streaming platforms offer millions of songs, creating a challenge for users in discovering content that matches their tastes. This research addresses this problem by designing a music recommendation system using a Hybrid Collaborative Filtering approach. This method combines the strengths of Item-Based (track similarity) and User-Based (playlist similarity) filtering for higher accuracy. Utilizing 100,000 playlists from Spotify's Million Playlist Dataset (MPD), the system was developed through data preprocessing, cosine similarity calculation, and weighted score combination. The evaluation was designed using metrics like Precision@K and Hit Ratio. The results demonstrate that the hybrid model can provide thematically relevant song recommendations based on an input playlist, proving its effectiveness in personalizing the music discovery experience for users.
References
[1] P. Venil, G. Vinodhini, and R. Suban, “A State Of The Art Survey On Cold Start Problem In A Collaborative Filtering System,” International Journal of Scientific & Technology Research, vol. 9, no. 4, pp. 3755–3759, Apr. 2020. [Online]. Available: https://www.ijstr.org/final-print/apr2020/A-State-Of-The-Art-Survey-On-Cold-Start-Problem-In-A-Collaborative-Filtering-System.pdf
[2] C.-W. Chen, P. Lamere, M. Schedl, and H. Zamani, “RecSys Challenge 2018: Automatic Music Playlist Continuation,” in Proc. 12th ACM Conf. Recommender Systems (RecSys '18), Vancouver, Canada, Oct. 2018, pp. 527–528. doi: 10.1145/3240323.3240342
[3] D. Nugraha, T. W. Purboyo, and R. A. Nugrahaeni, “Sistem Rekomendasi Film Menggunakan Metode User Based Collaborative Filtering,” e-Proceeding of Engineering, vol. 8, no. 5, pp. 6765–6772, Oct. 2021. [Online]. Available: https://openlibrary.telkomuniversity.ac.id/pustaka/files/172291/jurnal_eproc/sistem-rekomendasi-film-menggunakan-metode-user-based-collaborative-filtering.pdf
[4] I. Yoshua and H. Bunyamin, “Pengimplementasian Sistem Rekomendasi Musik Dengan Metode Collaborative Filtering,” Jurnal Strategi, vol. 3, no. 1, pp. 1–7, May 2021. [Online]. Available: https://strategi.it.maranatha.edu/index.php/strategi/article/view/220
[5] M. I. F. Robani Amin, M. R. Amartharizqi, F. A. Sofi, A. Anggraini, and P. Sari, “Sistem Rekomendasi Musik Berdasarkan Preferensi Pengguna Dengan Menggunakan Metode Natural Language Processing (NLP),” *Santika*, vol. 3, pp. 129–133, Nov. 2023. [Online]. Available: https://santika.upnjatim.ac.id/submissions/index.php/santika/article/view/213]
[6] M. V. Anggoro and M. Izzatillah, “Sistem Rekomendasi Musik dengan Metode Collaborative Filtering Berbasis Android,” STRING (Satuan Tulisan Riset dan Inovasi Teknologi), vol. 7, no. 1, pp. 32–41, Aug. 2022. doi: 10.30998/string.v7i1.10300
[7] A. I. Putra and R. R. Santika, “Implementasi Machine Learning dalam Penentuan Rekomendasi Musik dengan Metode Content-Based Filtering,” Edumatic, vol. 4, no. 1, pp. 121–130, Jun. 2020. doi: 10.29408/edumatic.v4i1.2162
[8] P. Nastiti, “Penerapan Metode Content Based Filtering Dalam Implementasi Sistem Rekomendasi Tanaman Pangan,” Teknika, vol. 8, no. 1, pp. 1–10, Jun. 2019. doi: 10.34148/teknika.v8i1.139
[9] A. D. Hartono and J. Sutopo, “Implementasi Algoritma Upper Confidence Bound Untuk Sistem Rekomendasi Musik,” Jurnal Algoritma, vol. 21, no. 2, pp. 82–90, Nov. 2024. doi: 10.33364/algoritma/v.21-2.2095
[10] G. A. V. M. Giri, M. L. Radhitya, M. A. Raharja, and I. W. Supriana, “Sistem Rekomendasi Musik Berdasarkan Data Konteks Pada Listening History Musik dan Keterkaitan Artis Indonesia,” Jurnal Resistor, vol. 5, no. 1, pp. 86–93, Apr. 2022. doi: 10.31598/jurnalresistor.v5i1.1044
[11] K. R. Putra and M. A. Rachman, “Perbandingan Metode Content-based, Collaborative dan Hybrid Filtering pada Sistem Rekomendasi Lagu,” MIND Journal, vol. 9, no. 2, pp. 179–193, 2024. doi: 10.26760/mindjournal.v9i2.179-193 [Online]. Available: https://ejurnal.itenas.ac.id/index.php/mindjournal/article/view/12447
[12] A. Padila, “Implementasi Metode Hybrid Filtering (Collaborative Filtering dan Content-Based Filtering) dalam Memberikan Rekomendasi Kost,” Undergraduate thesis, Universitas Sulawesi Barat, 2023. [Online]. Available: https://repository.unsulbar.ac.id/id/eprint/1571/
[13] G. V. R. Pake, V. C. Mawardi, and T. Sutrisno, “Penerapan Metode Content Based Filtering dalam Implementasi Sistem Rekomendasi Musik,” J. Sist. dan Teknol. Komput., vol. 1, no. 2, pp. 455–462, Sep. 2023. doi: 10.24912/jsstk.v1i2.31037. [Online]. Available: https://journal.untar.ac.id/index.php/JSSTK/article/view/31037/18332
[14] M. Zuhair, “Sistem Rekomendasi Lagu di Spotify Berdasarkan Kemiripan Lirik Menggunakan Metode Content-Based Filtering,” Undergraduate thesis, Universitas Pakuan, 2023. [Online]. Available:https://eprints.unpak.ac.id/8559/
[15] D. Y. Harjananto, R. K. Dewi, and K. C. Brata, “Pengembangan Sistem Rekomendasi Musik Berdasarkan Waktu Berbasis Android,” J-PTIIK, vol. 5, no. 5, pp. 1729–1733, Apr. 2021. [Online]. Available: https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/8981
[16] H. Februariyanti, A. D. Laksono, J. S. Wibowo, and M. S. Utomo, “Implementasi Metode Collaborative Filtering untuk Sistem Rekomendasi Penjualan pada Toko Mebel,” Khatulistiwa Inform., vol. 9, no. 1, 2021. doi: 10.31294/jki.v9i1.9859. [Online]. Available: https://ejournal.bsi.ac.id/ejurnal/index.php/khatulistiwa/article/view/9859
[17] M. A. Madani, G. Helmi, and Y. Hendra, “Sistem Rekomendasi Musik Menggunakan Machine Learning,” J-Tech, vol. 1, no. 1, pp. 40–49, Feb. 2024. [Online]. Available: https://ojs.adzkia.ac.id/index.php/jtech/article/view/282
[18] S. Safrizal, C. Anwar, A. E. Rayeb, Y. C. Simamora, A. V. Hasugian, and J. A. Alfian, “Sistem Rekomendasi Personalisasi Pembelajaran Mahasiswa untuk Prediksi Karir dan Sertifikasi Kompetensi yang Tepat,” JITEK, vol. 5, no. 2, pp. 01–09, Jun. 2025. doi: 10.55606/jitek.v5i2.5514. [Online]. Available: https://researchhub.id/index.php/jitek/article/view/5514
[19] M. D. Fawzan, C. Setianingsih, and R. A. Nugrahaeni, “Sistem Rekomendasi Lagu Metode Collaborative Filtering Berbasis Website,” e-Proceeding of Engineering, vol. 8, no. 6, pp. 12200–12206, Dec. 2021. [Online]. Available: https://repositori.telkomuniversity.ac.id/pustaka/files/175503/jurnal_eproc/sistem-rekomendasi-lagu-metode-collaborative-filtering-berbasis-website.pdf
[20] E. Jayadi, B. Mulyawan, and M. D. Lauro, “Implementasi Metode Collaborative Filtering untuk Analisis Data Belanja Konsumen Berbasis Website (Studi Kasus Restoran MyKitchen),” JIKSI, vol. 9, no. 1, 2021. doi: 10.24912/jiksi.v9i1.11559. [Online]. Available: https://journal.untar.ac.id/index.php/jiksi/article/view/11559
[21] P. Magron and C. Févotte, "Neural content-aware collaborative filtering for cold-start music recommendation," Data Mining and Knowledge Discovery, vol. 36, pp. 1971–2005, 2022. doi: 10.1007/s10618-022-00859-8.
[22] B. V. Chandrahaas, B. S. Panigrahi, S. D. Pande, and N. K. Swain, “A Hybrid Approach for Mobile Phone Recommendation using Content-Based and Collaborative Filtering”, EAI Endorsed Trans IoT, vol. 10, Dec. 2023.]
[23] V. Phaneendra Bottu, K. Ragavan. "Emotion-Based Music Recommendation System Integrating Facial Expression Recognition and Lyrics Sentiment Analysis," in IEEE Access, vol. 13, pp. 87740-87752, 2025.
[24] Bontempelli, T., et al, "Flow Moods: Recommending Music by Moods on Deezer," in Proceedings of the 16th ACM Conference on Recommender Systems, 2022, pp. 452–455.
[25] B. Basiliyos Tilahun Betru. " Deep Learning Methods on Recommender System: A Survey of State-of-the-art ," in International Journal of Computer Applications , vol. 162 , no. 10 , pp. 17-22 , 2017 .
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