Implementasi Business Intelligence untuk Menentukan Tingkat Kepopuleran Genre Musik pada Mahasiswa Ilmu Perpustakaan Angkatan 2023

Authors

  • Siwi Pelita Amini Universitas Bina Darma
  • Ahmad Wahidi Universitas Islam Negeri Raden Fatah Palembang
  • Tata Sutabri Universitas Bina Darma

DOI:

https://doi.org/10.55606/jtmei.v4i3.5634

Keywords:

Business Intelligence, Data Visualization, Interactive Dashboard, Music Analysis, Student Preferences

Abstract

Student music preferences are a reflection of the cultural dynamics of the younger generation, which need to be understood comprehensively. The implementation of Business Intelligence (BI) can transform music preference data into strategic information for decision-making. The purpose of this research is to analyze the popularity levels of music genres and to implement a BI dashboard for visualizing the music preferences of the 2023 cohort of Library Science students. The method used is a descriptive quantitative research method with a sample of 66 students. Data was collected through online questionnaires and analyzed using the ETL (Extract, Transform, Load) process, then visualized in an interactive BI dashboard. The results of this study state that the Pop genre is the most popular (57.6%), followed by K-Pop (43.9%) and J-Pop (37.9%). There is a significant difference in preferences based on gender, where females predominantly prefer Pop (62.5%) while males tend to prefer Jazz and Rock (40% each). Spotify is the favorite platform (47%), with the majority of respondents listening to music for <2 hours/day (56%). It can be concluded that the BI implementation successfully mapped student music preferences comprehensively and provides a basis for strategic decision-making in the academic environment.

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References

Chiang, R. H. L. (2022). Business intelligence and analytics: From big data to big impact. https://doi.org/10.2307/41703503

Djamba, Y. K., & Neuman, W. L. (2002). Social research methods: Qualitative and quantitative approaches. Teaching Sociology, 30(3). https://doi.org/10.2307/3211488

Fauzia, Z. U., Maulana, N., & Ibrahim, M. (2023). Analisis penerapan model pembelajaran Project Based Learning (PjBL) pada Kurikulum Merdeka di kelas IV SDN Sumbersari 2 Kota. [Artikel tidak diterbitkan / jurnal tidak dicantumkan].

Ikhtiarti, D., & Sutabri, T. (2023). Analisis IT service management (ITSM) layanan e-learning Universitas Bina Darma menggunakan framework ITIL V3. Jurnal Sistem Informasi, 6, 48–53.

Juni, N. (2024). SENTRI: Jurnal Riset Ilmiah, 3(6), 2741–2756. [Judul artikel tidak tercantum].

Mehta, M., & Pyasi, P. (2024). Music preferences and consumption habits among students of Hyderabad University: A study based on digital music platforms. https://doi.org/10.5281/zenodo.12196220

Novitasari, A., & Sutabri, T. (2023). Analisis kualitas layanan website BKPSDM Kota Palembang menggunakan metode WebQual. Jurnal Teknologi Informasi, 1(2), 88–94.

Nur, Z., & Mukhlash, I. (2014). Implementasi business intelligence pada manajemen report Bank XYZ. Jurnal Sistem Informasi, 3(2), 16–21.

Saragih, Z. C., & Rahmatulloh, A. R. (2024). Music for confidence: Exploring the relationship between music preference and self-esteem in college students. International Conference on Psychology UMBY, 680–687.

Seenivasan, D. (2023). ETL (Extract, Transform, Load) best practices. International Journal of Data Engineering, 71(1), 40–44.

Sugiyono. (2020). Metodologi penelitian kuantitatif, kualitatif, dan R&D. Alfabeta.

Sutabri, T. (2012). Analisis sistem informasi. Andi Publisher.

Taherdoost, H. (2018). Sampling methods in research methodology: How to choose a sampling technique for research. SSRN Electronic Journal, 5(2), 18–27. https://doi.org/10.2139/ssrn.3205035

Tremblay, J., Regnerus, M. D., & Others. (2016). [Judul artikel tidak tersedia]. Educação e Sociedade, 1(1).

Wieder, B., & Ossimitz, M. L. (2015). The impact of business intelligence on the quality of decision making: A mediation model. Procedia Computer Science, 64, 1163–1171. https://doi.org/10.1016/j.procs.2015.08.599

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Published

2025-09-30

How to Cite

Siwi Pelita Amini, Ahmad Wahidi, & Tata Sutabri. (2025). Implementasi Business Intelligence untuk Menentukan Tingkat Kepopuleran Genre Musik pada Mahasiswa Ilmu Perpustakaan Angkatan 2023. Jurnal Teknik Mesin, Industri, Elektro Dan Informatika, 4(3), 01–08. https://doi.org/10.55606/jtmei.v4i3.5634