Business Intelligence Implementation for Groceries Commodity Price Data Analytics
DOI:
https://doi.org/10.31598/sintechjournal.v7i2.1676Keywords:
business intelligence, decision making, data analysis, data visualization, apache supersetAbstract
As a startup company specializing in agricultural technology, currently PT XYZ does not have any effective and integrated tools to analyze groceries commodity for purchase and sale data-driven decision making. This research will integrating multiple data sources for accurate analysis, tailoring the business intelligence (BI) system to PT XYZ’s specific needs, and developing a robust solution that supports comprehensive decision-making. BI implementation solution will be developed using Pentaho Data Integration & Apache Superset. Applied research used as its method, that contains processes to gather user requirements to gather user needs from each information, design the solution, and dashboard development. The study focused on analyzing data from both internal sources, such as purchase and sales transactions, and external sources, including market price data, using these BI tools to provide comprehensive insights. The developed dashboard contains several sections that allow users to see price recommendation price and get the insight for the last seven days trend, monitor the market position, see team performance, and find the summary about estimated and actual margin comparison. Pentaho successfully handled ETL and data modeling, while Apache Superset enabled straightforward dashboard setup, though chart customization is limited.
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[2] N. Elgendy, A. Elragal, and T. Päivärinta, “DECAS: a modern data-driven decision theory for big data and analytics,” J Decis Syst, vol. 31, no. 4, pp. 337–373, 2022, doi: 10.1080/12460125.2021.1894674.
[3] R. Akshaya, V. Ravi, S. R. Lakshmi, and R. Aparna, “Big Data to Big Impact: Effect of Big Data in Modern Decision Making,” 2023, pp. 363–373. doi: 10.2991/978-94-6463-162-3_32.
[4] A. A. Nurdin, G. N. Salmi, K. Sentosa, A. R. Wijayanti, and A. Prasetya, “Utilization of Business Intelligence in Sales Information Systems,” Journal of Information System Exploration and Research, vol. 1, no. 1, pp. 39–48, 2022, doi: 10.52465/joiser.v1i1.101.
[5] B. van Gils, Data in Context. Cham: Springer Nature Switzerland, 2023. doi: 10.1007/978-3-031-35539-4.
[6] T. Maaitah, “The Role of Business Intelligence Tools in the Decision Making Process and Performance,” 2023.
[7] K. Nisa, D. Sugiarto, and T. Siswanto, “Perancangan Data Warehouse Harga Pangan Di Wilayah Perumda Pasar Jaya,” Explore:Jurnal Sistem informasi dan telematika, vol. 12, no. 1, p. 47, 2021, doi: 10.36448/jsit.v12i1.1744.
[8] A Sumarudin, Adi Suheryadi, Bahrainsyah Oksareinaldi, and Lia Nurfadilah, “Aplikasi Monitoring dan Prediksi Harga Komoditas Pasar Daerah Indramayu Berbasis Fuzzy Time Series,” JITSI : Jurnal Ilmiah Teknologi Sistem Informasi, vol. 1, no. 1, pp. 15–24, 2020, doi: 10.30630/jitsi.1.1.4.
[9] R. Bahtiar and F. D. Raswatie, “Analisis Fluktuasi Harga Pangan di Kota Bogor,” Indonesian Journal of Agriculture Resource and Environmental Economics, vol. 1, no. 2, pp. 70–81, 2023, doi: 10.29244/ijaree.v1i2.42020.
[10] M. K. Hidayat and D. Putri, “Business Intelligence Untuk Memantau Perkembangan Harga Pangan Provinsi DKI Jakarta,” Jurnal Infortech, vol. 6, no. 1, pp. 30–36, 2024, doi: 10.31294/infortech.v6i1.21832.
[11] Z. Hamidu, P. B. Oppong, E. Asafo-Adjei, and A. M. Adam, “On the Agricultural Commodities Supply Chain Resilience to Disruption: Insights from Financial Analysis,” Math Probl Eng, vol. 2022, 2022, doi: 10.1155/2022/9897765.
[12] I. Marina, D. Sukmawati, E. Juliana, and Z. N. Safa, “Dinamika Pasar Komoditas Pangan Strategis: Analisis Fluktuasi Harga Dan Produksi,” Paspalum: Jurnal Ilmiah Pertanian, vol. 12, no. 1, p. 160, 2024, doi: 10.35138/paspalum.v12i1.700.
[13] Blessing Otohan Irabor, Adekunle Abiola Abdul, Bankole Ibrahim Ashiwaju, and Gbolahan Olaoluwa Oladayo, “a Comprehensive Review of the Role of Data Analytics in Shaping Food Pricing Strategies in the United States: Historical Perspectives, Current Trends, and Future Projections,” Computer Science & IT Research Journal, vol. 4, no. 1, pp. 36–53, 2023, doi: 10.51594/csitrj.v4i1.603.
[14] A. Yudhistira, I. S. Sitanggang, and H. A. Adrianto, “Development ETL (Extract, Transform and Load) Module in Indonesian Agricultural Commodities OLAP System,” ILKOM Jurnal Ilmiah, vol. 15, no. 2, pp. 335–343, 2023, [Online]. Available: https://jurnal.fikom.umi.ac.id/index.php/ILKOM/article/view/1758
[15] A. Aljuwaiber, “Data Warehousing as Knowledge Pool : A Vital Component of Business Intelligence,” International Journal of Computer Science, Engineering and Information Technology, vol. 12, no. 4, pp. 21–26, Aug. 2022, doi: 10.5121/ijcseit.2022.12402.
[16] Dr. L. C. Manikandan and Dr. R. K. Selvakumar, “A Review on Data Warehousing Concepts, Challenges and Applications,” International Journal of Scientific Research in Computer Science, Engineering and Information Technology, pp. 25–31, Jan. 2023, doi: 10.32628/cseit239015.
[17] M. Paliwal and P. Saraswat, “APPROACHES OF DATA WAREHOUSING AND THEIR APPLICATIONS: A REVIEW,” International Journal of Innovative Research in Computer Science & Technology, pp. 117–121, Jan. 2022, doi: 10.55524/ijircst.2022.10.1.21.
[18] J. Sreemathy, R. Brindha, M. Selva Nagalakshmi, N. Suvekha, N. Karthick Ragul, and M. Praveennandha, “Overview of ETL Tools and Talend-Data Integration,” in 2021 7th International Conference on Advanced Computing and Communication Systems, ICACCS 2021, Institute of Electrical and Electronics Engineers Inc., Mar. 2021, pp. 1650–1654. doi: 10.1109/ICACCS51430.2021.9441984.
[19] D. Orlovskyi and A. Kopp, “A Business Intelligence Dashboard Design Approach to Improve Data Analytics and Decision Making,” 2020.
[20] I. Putu, A. Eka Pratama, N. P. Nirmala, and D. Widhiasih, “PERANCANGAN DATA WAREHOUSE UNTUK PREDIKSI PENJUALAN PRODUK PADA ORBA EXPRESS MENGGUNAKAN PENTAHO,” 2020.
[21] M. OZDEMİR, E. E. ÜLKÜ, and K. YILDIZ, “Analysis and Comparison of Business Intelligence Tools Most Preferred by Companies in Turkey,” Balkan Journal of Electrical and Computer Engineering, vol. 11, no. 2, pp. 144–155, Jun. 2023, doi: 10.17694/bajece.1123171.
[22] K. A. Khedikar, “Data Analytics for Business Using Tableau,” SSRN Electronic Journal, 2021, doi: 10.2139/ssrn.3835030.
[23] F. Anwar, I. Wahyuddin, and D. Hidayatullah, “Data Visualization Application ‘JIRA’ at PT. Jati Piranti Solusindo Using the Metabase,” Jurnal Mantik, vol. 4, no. 1, pp. 289–293, 2020.
[24] A. Halundi, M. Moharir, and A. Professor, “CREATING DASHBOARD USING SUPERSET BY API CALL TO DIFFERENT SOURCE,” 2021. [Online]. Available: www.jetir.org
[25] Firdaus, Zulfadilla, and F. Caniago, “RESEARCH METHODOLOGY : TYPES IN THE NEW PERSPECTIVE,” Jurnal Manajemen dan Ilmu Pendidkan, vol. 3, no. 1, pp. 1–16, 2021, [Online]. Available: https://ejournal.stitpn.ac.id/index.php/manazhim.
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2024-08-31
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