Implementasi Business Intelligence Berbasis Data Warehouse dan OLAP untuk Analisis Pola Peminjaman Buku Perpustakaan

Authors

  • Imam Waluyo Putra Universitas Krisnadwipayana
  • Wargijono Utomo Universitas Krisnadwipayana

DOI:

https://doi.org/10.59024/jumek.v4i2.787

Keywords:

Business Intelligence, Dashboard, Data Warehouse, Library, OLAP

Abstract

Libraries generate large volumes of borrowing transaction data every day, but most of the data has not been optimally utilized as strategic information for decision making. This study aims to design a data warehouse and implement Online Analytical Processing (OLAP) to analyze book borrowing patterns through a Business Intelligence Dashboard. The research method used is system development with the Kimball approach consisting of requirement analysis, dimensional modeling, ETL process, OLAP implementation, and Dashboard visualization. The data used are borrowing transactions from the library system during the 2024–2025 period. The results show that the implemented data warehouse is able to integrate borrowing data effectively and support multidimensional analysis based on time, category, study program, and borrowing intensity. OLAP implementation successfully accelerates the analytical process and Dashboard visualization assists librarians and management in identifying borrowing trends and making strategic decisions related to book collections and library services. The developed system contributes to improving the effectiveness of data-driven library management.

References

Abu-Alsondos, I. A. (2023). The impact of business intelligence system (BIS) on quality of strategic decision-making. International Journal of Data and Network Science, 7(4), 1901–1912. https://doi.org/10.5267/j.ijdns.2023.7.003.

Angkasa & Nasution, (2025) Angkasa, P., & Nasution, M. I. P. (2025). Penerapan Business Intelligence dalam Pengambilan Keputusan. Jurnal Penelitian Ilmu-Ilmu Sosial, 02(June), 554–558. https://doi.org/10.24843/JIK.2023.v16.i01.p07.

Anshari, S. F., & Retno, S. (2023). Penerapan Metode Nine-Step Kimball Dalam Pengolahan Data History Menggunakan Data Warehouse dan Business Intelligence.

Chaudhuri, S., Dayal, U., & Narasayya, V. (2011). An Overview of Business Intelligence Technology. Communications of the ACM, 54(8), 88–98https://doi.org/10.1145/1978542.1978562.

Codd, E. F., Codd, S. B., & Salley, C. T. (1993). Providing OLAP to User-Analysts: An IT Mandate. Codd & Date Report.

Connolly, T., & Begg, C. (2015). Database Systems: A Practical Approach to Design, Implementation, and Management. Pearson.

Dhaouadi et al. (2022). Implementasi Business Intelligence guna Optimasi Manajemen Inventaris Perpustakaan Perguruan Tinggi. Telkom University Repository.

Fauzi, M., & Rahman, A. (2023). Kajian Penerapan Arsitektur Data Warehouse dalam Bisnis Intelijen pada Pengambilan Keputusan Bisnis. Jurnal Ekonomi Manajemen Sistem Informasi.

Firdaus, H., Firmansyah, E., Desianti, V., & York, N. (2025). Optimasi Model Data Warehouse Menggunakan Skema Bintang untuk Mendukung Analisis Multidimensi Kredit Usaha Rakyat Syariah Optimizing a Data Warehouse Model Using a Star Schema to Support Multidimensional Analysis of Kredit Usaha Rakyat ( KUR ) Syariah. 5(10), 3146–3162.

Fitria, A., & Yadi, llman Z. (2022). Pemanfaatan Business Intelligence Untuk Visualisasi Data Dan Pemetaan Kasus Gizi Buruk Dan Gizi Kurang Menggunakan TableAu. Jurnal Mantik, 6(3), 3436–3445.

Golfarelli, M., & Rizzi, S. (2009). Data Warehouse Design: Modern Principles and Methodologies. McGraw-Hill.

Hakim, L., & Sari, M. (2022). Pemodelan Data Warehouse Perpustakaan Fakultas Tarbiyah dan Ilmu Keguruan. Jurnal Sistem Informasi dan Teknologi.

Hermanto, A. (2024). Analisis Perbandingan Penerapan Business Intelligence di Indonesia Menggunakan Systematic Literature Review. Djtechno: Jurnal Teknologi Informasihttps://doi.org/10.46576/djtechno.v4i2.3412.

Inmon, W. H. (2005). Building the Data Warehouse (4th Edition). Wiley.

Kimball, R., & Ross, M. (2013). The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling (3rd Edition). Wiley.

Nugroho, A. W., & Utama, A. A. G. S. (2025). Business Intelligence Systems and Their Impact on Organizational Decision-Making and Performance Outcomes: Literature Review. Owner, 9(2), 1269–1284. https://doi.org/10.33395/owner.v9i2.2646.

Senduk, F. K., Waluyo, R., & Isnaini, K. N. (2025). Data Analysis using Business Intelligence and Tableau for Visualizing Indonesia’s Poverty Line. Sistemasi, 14(3), 1122. https://doi.org/10.32520/stmsi.v14i3.4993.

Tahir et al. (2023). Pembangunan Dashboard Business Intelligence Data Akademik Smpn 1 Nguling. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 9(9), 1–10. http://j-ptiik.ub.ac.id

Thenata, A. P. (2025). Perancangan Dan Analisis Data Warehouse Menggunakan Nine Step Design Pada Perusahaan Sky Data Warehouse Design and Analysis Using Nine Step Design At Sky Company. 01, 781–791. http://dx.doi.org/10.30813/j-alu.v2i2.8250

Turban, E., Aronson, J. . ., & Peng Liang, T. (2018). Decision Support Systems and Intelligent Systems - Sistem Pendukung Keputusan dan Sistem Cerdas. 802.

Downloads

Published

2026-04-30

How to Cite

Imam Waluyo Putra, & Wargijono Utomo. (2026). Implementasi Business Intelligence Berbasis Data Warehouse dan OLAP untuk Analisis Pola Peminjaman Buku Perpustakaan. Jurnal Manajemen Dan Ekonomi Kreatif, 4(2), 407–425. https://doi.org/10.59024/jumek.v4i2.787

Similar Articles

<< < 12 13 14 15 16 17 18 19 > >> 

You may also start an advanced similarity search for this article.