Perancangan Data Warehouse untuk Analisis Penjualan Ritel Elektronik Berbasis Business Intelligence

Authors

  • Reno Naufal Maulidyan Universitas Pembangunan Nasional Veteran Jawa Timur
  • M. Muharrom Al Haromainy Universitas Pembangunan Nasional Veteran Jawa Timur

DOI:

https://doi.org/10.61722/jipm.v4i3.2604

Keywords:

business intelligence, data warehouse, electronic retail, star schema, Tableau

Abstract

This study proposes a data warehouse design based on a star schema to support electronic retail sales analysis using PostgreSQL, Pentaho Data Integration, and Tableau. The objective is to transform heterogeneous transactional data into a structured analytical environment that can improve business intelligence capability. The research method includes data ingestion into a relational database, staging area construction, ETL-based cleansing and standardization, dimensional modeling, datamart development, and interactive dashboard visualization. The resulting architecture enables multidimensional analysis across time, product, region, sales channel, payment method, and customer type. The findings indicate that the proposed system improves data consistency, analytical efficiency, and decision-support capability, making it suitable as a foundation for retail performance monitoring and strategic planning.

References

Adesyahputra, M. K., & Rachmawati, E. P. (2025). Analysis of corn production in Indonesia using business intelligence technology based on Power BI How to Cite: “Analysis of corn production in Indonesia using business intelligence technology based on Power BI.” Matrix : Jurnal Manajemen Teknologi Dan Informatika, 15(1), 21–31.

Astriyani, W., Nisrina, N. N., Naila, N., Azahra, N., Aprillianah, D., & Noviany, D. (2026). Pengaruh Integrasi Big Data , Penerapan Artificial Intelligence , dan Optimalisasi Kompetensi Auditor terhadap Efektivitas Audit dalam Mendeteksi Financial Fraud. 4(4), 11448–11464.

Aulia Rachman, A., & Susyanti, J. (2024). Tinjauan Literatur : Penerapan Business Intelligence untuk Meningkatkan Kinerja Bisnis Ekspedisi. Jurnal Ekonomi Manajemen Dan Bisnis, 1(6), 384–391. https://doi.org/10.62017/jemb

Darmawan, R., & Swalaganata, G. (2025). Analisa Komparatif Power Bi Dan Tableau Dalam Implementasi Business Intelligence Pada Brazilian E-Commerce Public Dataset By Olist. JATI (Jurnal Mahasiswa Teknik Informatika), 9(5), 8936–8944. https://doi.org/10.36040/jati.v9i5.15178

Fauzi, A., Nugroho, A., Monte, A., Ignesia, A., Makruf, M., Andreas, R., & Hasanah, S. (2023). Pemanfaatan Business Intelligence Dalam Pembuatan Strategi dan Pengambilan Keputusan Bisnis. Jurnal Manajemen Dan Bisnis, 2(3), 212–218.

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.

Hartanto, R., Candra Kirana, J., & Indra, I. (2026). Perancangan Data Warehouse Menggunakan Metode Star Schema dan ETL Untuk Menghasilkan Laporan Efektifitas Proses Rekrutmen Kandidat di Enigma Camp. Jurnal Pendidikan Dan Teknologi Indonesia, 5(12), 3658–3672. https://doi.org/10.52436/1.jpti.1229

Khotimah, K., & Sriyanto. (2016). Perancangan Dan Implementasi Data Warehouse. Jurnal TIM Darmajaya, 2(1), 97. https://media.neliti.com/media/publications/141617-ID-perancangan-dan-implementasi-data-wareho.pdf

Muhamad Wisnu Alfiansyah, I Nyoman Switrayana, L. M. (2024). Peran Business Intelligence dalam Meningkatkan Kinerja UMKM. Economist:Jurnal Ekonomi Dan Bisnis, 2024, 13–19.

Murtiwiyati, Agathon, H., & Safitri, L. (2024). Implementasi Data Warehouse dan Business Intelligence Menggunakan Pentaho dan Metabase untuk Membuat Dahboard Visualisasi Kinerja Penjualan E-Commerce Wish. Jurnal Penelitian Teknologi Informasi Dan Sains, 2(2), 101–109.

Print, I. (2026). InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan PERBAIKAN PADA PT TELKOM WITEL BENGKULU. 02.

Putri Susanto, A. N. A., & Kurniawan, G. I. (2023). Analisis Terbatasnya Peminatan Profesi Data Analyst Di Indonesia Berdasarkan Pendekatan Analytical Hierarchy Process (AHP). Journal of Information System, Applied, Management, Accounting and Research, 7(1), 217. https://doi.org/10.52362/jisamar.v7i1.1042

Rismaninda Putri Dwi Prasetya, Azizah, R. N., Halwa, J. B. W., Nugroho, R. H., & Kusumasari, I. R. (2024). Implementasi Penggunaan Data Analytics untuk Mengoptimalkan Pengambilan Keputusan Bisnis di Era Digital. Jurnal Bisnis Dan Komunikasi Digital, 2(2), 12. https://doi.org/10.47134/jbkd.v2i2.3459

Suwandhi, A., Johan, J., Jimmy, J., & Benny, B. (2025). Meningkatkan Minat pada Profesi Data Analyst di Indonesia: Pendekatan Analytical Hierarchy Process. Jurnal Minfo Polgan, 13(2), 2375–2378. https://doi.org/10.33395/jmp.v13i2.14492

Yulianto, A., & Firmansyah. (2024). Optimalisasi Performa Data Warehouse dengan Data Mart. Remik: Riset Dan E-Jurnal Manajemen Informatika Komputer, 8(4), 1081–1089. http://doi.org/10.33395/remik.v8i4.14152

Downloads

Published

2026-06-19

How to Cite

Reno Naufal Maulidyan, & M. Muharrom Al Haromainy. (2026). Perancangan Data Warehouse untuk Analisis Penjualan Ritel Elektronik Berbasis Business Intelligence. JURNAL ILMIAH PENELITIAN MAHASISWA, 4(3), 980–989. https://doi.org/10.61722/jipm.v4i3.2604

Issue

Vol. 4 No. 3 (2026): JUNI

Section

##section.default.title##

License

Copyright (c) 2026 JURNAL ILMIAH PENELITIAN MAHASISWA

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.