Authors:

Muhammad Arief Budiman, Gst. Ayu Vida Mastrika Giri

Abstract:

“The development of the music industry is currently growing rapidly, millions of music works continue to be issued by various music artists. As for the technologies also follows these developments, examples are mobile phones applications that have music subscription services, namely Spotify, Joox, GrooveShark, and others. Application-based services are increasingly in demand by users for streaming music, free or paid. In this paper, a music recommendation system is proposed, which the system itself can recommend songs based on the similarity of the artist that the user likes or has heard. This research uses Collaborative Filtering method with Cosine Similarity and K-Nearest Neighbor algorithm. From this research, a system that can recommend songs based on artists who are related to one another is generated.”

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PDF:

https://jurnal.harianregional.com/jlk/full-53174

Published

2020-02-04

How To Cite

BUDIMAN, Muhammad Arief; MASTRIKA GIRI, Gst. Ayu Vida. Song Recommendations Based on Artists with Cosine Similarity Algorithms and K-Nearest Neighbor.JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 8, n. 4, p. 367-374, feb. 2020. ISSN 2654-5101. Available at: https://ojs.unud.ac.id/index.php/JLK/article/view/53174. Date accessed: 08 Jul. 2024. doi:https://doi.org/10.24843/JLK.2020.v08.i04.p01.

Citation Format

ABNT, APA, BibTeX, CBE, EndNote - EndNote format (Macintosh & Windows), MLA, ProCite - RIS format (Macintosh & Windows), RefWorks, Reference Manager - RIS format (Windows only), Turabian

Issue

Vol 8 No 4 (2020): JELIKU Volume 8 No 4, Mei 2020

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License