Business Intelligence for Decision Support System for Replenishment Policy in Mining Industry - Seto, Franklin Chandra Pragnyono; Daryanto, Yosef; Diar Astanti, Ririn (Universitas Atma Jaya Yogyakarta, 2023)
The mining industry has unique characteristics in the sense that usually, the plant is located in a remote area while the headquarters are located in an urban area. These conditions pose challenges for the industry related to coordination within companies. This coordination is very important, especially in relation to the decision-making that must be carried out by the company. One of the important managerial decisions is related to the replenishment policy. To make replenishment decisions, companies need past data, such as biodiesel consumption rate, and current data, such as current stock and storage capacity, where the source of those data is in the plant. Often, decisions must be taken quickly because they have impacts on the continuousness of production operations at the plant. However, the remote location and shipping routes across rivers have created new challenges in the flow of goods and services supply because the shipment depends on the tides of the river. This research proposes a business intelligence system that collects, sorts, and visualizes data, then analyzes the replenishment decision to support decision-making in the mining industry. The system uses Microsoft Power BI software which is integrated with the company’s ERP system. To illustrate the applicability of the proposed system, it is applied to a coal mining company, especially in relation to the replenishment policy of biofuel. The result of this study indicates that the proposed system can work. In addition, it can reduce decision-making time by 220.65%.