Jurnal Nasional Teknologi Informasi dan Aplikasinya
Vol. 2 No. 4 (2024): JNATIA Vol. 2, No. 4, Agustus 2024

Pengelompokan Lagu Populer untuk Musik Gym Menggunakan Metode K-Means Clustering

Pande Nyoman Weda Wesnawa (Unknown)
Made Agung Raharja (Unknown)



Article Info

Publish Date
02 Aug 2024

Abstract

Music streaming has emerged as the primary mode for individuals to enjoy music while exercising at the gym. Spotify, among the largest music streaming platforms, surveyed 2,000 gym users in the US, revealing that 82% utilize Spotify during workouts. Studies indicate music significantly influences workout quality. This study aims to cluster popular Spotify songs of 2023 using KMeans based on audio attributes like tempo, energy, and danceability. Data sourced from Kaggle's 2023 Spotify dataset underwent preprocessing. Utilizing the Elbow method, optimal cluster count determination yielded two clusters: one apt for gym use and another unsuitable. Out of 954 songs, 72.3% were gym appropriate. Visualizations via pie charts and 3D scatter plots depicted clusters based on BPM, energy, and danceability. Purity evaluation scored 1.0, ensuring accurate cluster formation. This research aids gym proprietors in crafting strategies to select motivating music, enhancing members' workout experiences. 

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Journal Info

Abbrev

jnatia

Publisher

Subject

Computer Science & IT Engineering

Description

JNATIA (Jurnal Nasional Teknologi Informasi dan Aplikasinya) adalah jurnal yang berfokus pada teori, praktik, dan metodologi semua aspek teknologi di bidang ilmu komputer, informatika dan teknik, serta ide-ide produktif dan inovatif terkait teknologi baru dan teknologi informasi. Jurnal ini memuat ...