Pengelompokan Lagu Populer untuk Musik Gym Menggunakan Metode K-Means Clustering
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 K-Means 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.
Keywords: Spotify, K-Means, Gym, Purity, Popular Song, Music Information Retrieval
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