Dashboard To View Petroleum Import Comparison
Keywords:
petrolium import, dashboard, data visualization, business intellegence, decision making, indonesian, energy products, energy policyAbstract
Petroleum is a strategic commodity with an important role in the economy, widely used in the transportation, industrial, and household sectors. In Indonesia, although there are petroleum reserves, domestic production is often insufficient to meet needs. Therefore, importing petroleum products is the main solution. Petroleum product import data covering the volume and value of various types of products is important for strategic decision making in the energy sector. This study aims to design a dashboard that can visualize import data for each petroleum product in real-time, interactively, and easily understood, thus facilitating analysis and supporting better strategic decisions. This dashboard helps users monitor import trends, compare data, and understand national energy needs. As a result, the dashboard is able to display import trends and comparisons interactively based on volume, value, product type, and specific time periods.
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References
Daniel J. Power, C. H. (2017). Decision Support, Analytics, and Business Intelligence (Third edit). https://www.businessexpertpress.com/books/decision-support-analytics-and- business-intelligence-third-edition/
Miftah Hidayat, N. H. (2019). Dashboard Interaktif untuk Memonitor Data Impor Minyak.
Journal of Energy Analytics, 1(7), 67–76.
Seddon, P. B., Constantinidis, D., Tamm, T., & Dod, H. (2017). How does business analytics contribute to business value? Information Systems Journal, 27(3), 237–269. https://doi.org/10.1111/isj.12101
Setiawas R., & S. S. (2020). Pengembangan Dashboard Business Intelligence untuk Analisis Data Impor Minyak Mentah. Journal of Information System, 2(14), 113–114.
A. S. Budiarto, KPI: Key Performance Indicator. Huta Publisher, 2017.
P. Vassiliadis, M. Simitsis, and S. Skiadopoulos, "Conceptual modeling for ETL processes," in Proc. 5th ACM Int. Workshop on Data Warehousing and OLAP (DOLAP), McLean, VA, USA, 2002, pp. 14–21.
J. Smith, "The Role of Data Warehousing in Business Intelligence," Journal of Data Management, vol. 15, no. 3, pp. 45–56, 2020.
M. Chen et al., "Data Analytics for Smart Cities Using Tableau," IEEE Internet of Things Journal, vol. 7, no. 5, pp. 4181–4192, May 2020, doi: 10.1109/JIOT.2020.2988539.
R. K. Sahu, Business Intelligence for Banking. India: Infosys Finacle, 2012.
C. Vercellis, Business Intelligence: Data Mining and Optimization for Decision Making.
Chichester, UK: John Wiley & Sons, 2009.
D. Edi, S. Betshani, J. Prof, D. Suria, and S. No, "Analisis data dengan menggunakan ERD dan model konseptual data warehouse," Jurnal Informatika, vol. 5, no. 1, pp. 71–85, 2009.
W. H. Inmon, Building the Data Warehouse. Hoboken, NJ, USA: Wiley, 2005.
Hidayat, M. (2019) - Dashboard Interaktif untuk Memonitor Data Impor Minyak. Journal of Energy Analytics, 1(7), 67–76.
Inmon, W. H. (2005) - Building the Data Warehouse. Hoboken, NJ, USA: Wiley.
Watson, H. J., & Wixom, B. H. (2007) - The Current State of Business Intelligence. Computer, 40(9), 96–99. DOI: 10.1109/MC.2007.331
Sharda, R., Delen, D., & Turban, E. (2020) - Business Intelligence, Analytics, and Data Science: A Managerial Perspective (4th Edition). Pearson Education.











