IMPLEMENTATION OF WEIGHTED PRODUCT METHOD IN DETERMINING SELECTION THE BEST MUSIC STREAMING SERVICE APPLICATION

  • Lilyani Asri Utami (1*) Universitas Nusa Mandiri
  • Kaffah Febriningrum (2) Universitas Nusa Mandiri

  • (*) Corresponding Author
Keywords: Weighted Product, Sistem Penunjang Keputusan, streaming musik

Abstract

At this time, the music streaming service is a platform that is often easily found on every device, either through downloads from the Playstore and Appstore or the default application from the device itself. Many companies in the world are competing to create platforms and applications that provide the most complete songs. For example, several well-known music streaming service applications in Indonesia have their own innovations and characteristics, such as Spotify, Joox, Youtube Music, Apple Music, SoundCloud, and so on. This causes users to have difficulties because of several considerations in deciding how to use the application according to their needs. This study aims to assist in providing solutions to music streaming service subscribers by recommending several music streaming service applications according to the ranking results, which are the best choice for the user version of the application through a Decision Support System using the Weighted Product method based on 5 criteria: subscription rates, available features, streaming quality, music, application design, and application efficiency. The final result of this study is the ranking of applications that have the highest score in accordance with the criteria provided, namely that in first place with a value of 0.415 is Spotify as a recommendation for the best music streaming service application, and Apple Music ranks last out of the 6 alternatives that have been provided.

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Published
2023-03-16
How to Cite
Utami, L., & Febriningrum, K. (2023). IMPLEMENTATION OF WEIGHTED PRODUCT METHOD IN DETERMINING SELECTION THE BEST MUSIC STREAMING SERVICE APPLICATION. Jurnal Techno Nusa Mandiri, 20(1), 31 - 40. https://doi.org/10.33480/techno.v20i1.3126
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