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All Journal Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Journal Collabits
rahmadani, Nia putri
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Religion Humanities Computer Science & IT Education Engineering Languange, Linguistic, Communication & Media Nursing Public Health Social Sciences

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Analysis of Spotify Song Popularity Based on Audio Features Using Random Forest Rahmaputri, Anggi Beauty; Putri, Deswita Nindya; Rahmadani, Nia Putri; Soleh, Oleh
Journal Collabits Vol 3, No 1 (2026)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v3i1.37647

Abstract

The rapid growth of digital music streaming platforms such as Spotify has significantly increased competition among songs, making popularity an important yet difficult aspect to predict. Understanding the factors that influence song popularity is essential for musicians, producers, and digital platforms in developing effective promotion strategies and recommendation systems. This study aims to analyze the relationship between Spotify audio features and song popularity using a data science approach. The dataset used in this study consists of songs described by various audio features, including danceability, energy, loudness, tempo, acousticness, instrumentalness, valence, and track duration, with popularity serving as the target variable. An exploratory data analysis (EDA) was conducted to examine the distribution of popular and non-popular songs, analyze correlations among audio features, and visualize the relationships between selected audio features and popularity. The results show that the dataset is highly imbalanced, with non-popular songs dominating the overall distribution. Correlation analysis indicates strong relationships between certain audio features, particularly between energy and loudness, while the linear correlation between individual audio features and popularity is relatively weak. Scatter plot visualizations suggest that popular songs tend to have higher levels of danceability, energy, and loudness compared to non-popular songs. However, no single feature can adequately explain popularity on its own, suggesting that a combination of multiple audio characteristics influences song popularity. This research provides an initial insight into the relationship between Spotify audio features and song popularity and serves as a foundation for future studies applying machine learning models, such as Random Forest, for popularity prediction.
Peningkatan Literasi Kesehatan Digital Melalui Media Komik Untuk Pencegahan Kecanduan Game Online pada Siswa SMP Negeri 4 Takalar Suriah, Suriah; Nasrah, Nasrah; Azizah, Shofura; Yusdalifa, Yusdalifa; Yusuf , Andi Muh. Al Aqsa; Rahmadani, Nia Putri; Kristiani, Anjelica; Palompengi, Aqilah Nazhwa; Afdah, Afdah; Rafika, Andi
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 6 No. 3 (2026): Mei 2026 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/altifani.v6i3.1126

Abstract

  Perkembangan teknologi digital yang pesat meningkatkan penggunaan internet pada remaja, khususnya melalui permainan daring. Penggunaan game online secara berlebihan dan tidak terkontrol dapat menyebabkan kecanduan yang berdampak negatif terhadap kesehatan fisik, mental, sosial, serta prestasi akademik siswa. Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan literasi kesehatan digital dan kesadaran siswa dalam pencegahan kecanduan game online melalui edukasi kesehatan menggunakan komik pada siswa SMP di Kabupaten Takalar. Metode yang digunakan adalah edukatif dan partisipatif dengan pengukuran pengetahuan menggunakan pre test dan post test. Sebanyak 20 siswa berpartisipasi dalam kegiatan ini. Materi meliputi pengertian kecanduan game online, faktor penyebab, dampak, serta strategi pengendalian diri dan pemanfaatan waktu luang secara produktif. Hasil menunjukkan peningkatan pengetahuan yang signifikan, ditandai dengan kenaikan kategori pengetahuan tinggi dari 40% pada pre test menjadi 95% pada post test. Kegiatan ini efektif mendukung perilaku digital sehat dan seimbang pada siswa melalui pendekatan preventif berkelanjutan yang melibatkan peran aktif guru sekolah dan orang tua siswa.
Co-Authors Afdah, Afdah Azizah, Shofura Kristiani, Anjelica Nasrah, Nasrah Oleh Soleh, Oleh Palompengi, Aqilah Nazhwa Putri, Deswita Nindya Rafika, Andi Rahmaputri, Anggi Beauty Suriah Suriah Yusdalifa, Yusdalifa Yusuf , Andi Muh. Al Aqsa