Analisis Data Warehouse Pada Perpustakaan Universitas XYZ Untuk Efisiensi Manajemen Menggunakan Metode Kimball 4 Langkah

Badie Uddin, Eneng Mila Lestari Wijayadi, Aprilia zahra Maharani, Kailal Wafa Auladal Barren

Abstract


The XYZ University Library faces recurring book losses that affect the efficiency of library collection management. This study aims to develop a data-driven analysis system to identify loss patterns and support decision-making. The proposed solution uses a Data Warehouse approach with the Kimball Four-Step method and the ETL (Extract, Transform, Load) process. This methodology includes business process selection, grain declaration, dimension identification, and fact determination. Library transaction data from 2022 to 2024 was extracted, transformed, and loaded into a MySQL-based warehouse and visualized using Power BI. The analysis revealed that popular book categories, such as novels, were the most frequently lost. The visualization also enabled trend analysis based on time, book types, and user segments. The findings highlight a significant decline in loss cases, from 27 in 2022–2023 to 13 in 2023–2024, suggesting improved monitoring and management. The study demonstrates that the Data Warehouse approach effectively supports historical data analysis and provides accurate insights for sustainable library policy formulation.


Keywords


Data warehouse, ETL, Kimball 4 Steps, Library.

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References


N. Adila, “Desain Dan Implementasi Data Warehouse Pada Perpustakaan Daerah Provinsi Sumatera Selatan,” 2021.

Perpustakaan Nasional RI, “Jumlah Perpustakaan Terakreditasi Menurut Provinsi, Jenis Perpustakaan, dan Predikat Akreditasi, 2024,” Perpustakaan Nasional Republik Indonesia. Accessed: May 12, 2025. [Online]. Available: https://www.bps.go.id/id/statistics-table/3/Um1wWk1FMTNWakJHY20xUldYbzBkRzVLZG1KSlFUMDkjMw%3D%3D/--jumlah-perpustakaan-terakreditasi-menurut-provinsi---jenis-perpustakaan--dan-predikat-akreditasi--2024.html?year=2024

Perpustakaan Nasional RI, “Perpusnas Dorong Peningkatan Jumlah Perpustakaan Sesuai Standar,” Perpustakaan Nasional Republik Indonesia. Accessed: May 12, 2025. [Online]. Available: https://www.perpusnas.go.id/berita/perpusnas-dorong-peningkatan-jumlah-perpustakaan-sesuai-standar?

L. Setiyani and E. Tjandra, “Perancangan dan Implementasi Data Warehouse untuk Perpustakaan Kampus (Studi Kasus: STMIK Rosma Karawang) Design and Implementation Data Warehouse for Campus (Case Study: STMIK Rosma Karawang),” IJIS - Indonesian Journal On Information System, vol. 5, no. 2, p. 113, Sep. 2020, doi: 10.36549/ijis.v5i2.102.

Thomas Connoly and Carolyn Begg, “Database systems. A practical approach to design, implementation and management,” https://www.researchgate.net/publication/228831514_Database_systems_A_practical_approach_to_design_implementation_and_management.

S. M. Qibtiyah, A. Nugroho, R. Firliana, and K. Kunci, “JIKOMSI [Jurnal Ilmu Komputer dan Sistem Informasi] Sistem Informasi Pengolahan Data Peminjaman Buku di Taman Baca Dengan Menggunakan Data Warehouse INFORMASI ARTIKEL ABSTRAK,” vol. 5, no. 2, p. 68, 2022.

R. Irawan, F. Tarbiyah, I. Keguruan, and S. Manajemen, “Library Warehouse Data Modeling of Faculty of Teacher Training and Education of State Islamic Institute of Palangka Raya,” 2021.

S. Sucipto, S. Sucipto, and A. Nugroho, “Analisis Data Warehouse Pada Perpustakaan Man X Untuk Efisiensi Manajemen,” Fountain of Informatics Journal, vol. 5, no. 3, p. 17, Nov. 2020, doi: 10.21111/fij.v5i3.4988.

N. Adila, “Desain Dan Implementasi Data Warehouse Pada Perpustakaan Daerah Provinsi Sumatera Selatan,” 2021.

V. Imaniar Ivanoti, M. Royani, and M. Ilmu Komputer, “Data Warehouse Model Based on Kimball Methodology to Support Decision Making in Asset Maintenance,” vol. 4, no. 1, pp. 15–24, 2023, doi: 10.20884/1.jutif.2023.4.1.628.

N. Azizah, “Metodologi Penelitian 1 : Deskriptif Kuantitatif. ,” https://www.researchgate.net/publication/371988490_Metodologi_Penelitian_1_Deskriptif_Kuantitatif.

Wilfried. Lemahieu, S. vanden. Broucke, and Bart. Baesens, Principles of database management : the practical guide to storing, managing and analyzing big and small data. Cambridge University Press, 2018.

P. Bhatia, “Data Mining and Data Warehousing: Principles and Practical Techniques,” United Kingdom ; New York, 2019.

W. H. Inmon, B. O’Neil, and L. Fryman, “Business Metadata: Capturing Enterprise Knowledge. Morgan Kaufmann. ,” 2008.

W. H. Inmon and D. Linstedt, “Data Architecture: A Primer for the Data Scientist. Morgan Kaufmann. ,” 2015.

P. Vassiliadis, A. Simitsis, and E. Baikousi, “A taxonomy of ETL activities. In Proceedings of the ACM twelfth international workshop on Data warehousing and OLAP,” 2009.

A. Kabiri and D. Chiadmi, “Survey on ETL processes. Journal of Theoretical and Applied Information Technology,” 2013.




DOI: https://doi.org/10.30591/jpit.v10i2.7323

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