Optimizing Coal Production Estimates: Balancing Topographic Surveys Method and Truck Counts Method at Pit Kress, PT. Bordun Indie, South Kalimantan, Indonesia

Abstract

Accurate coal production estimation is essential to support efficient decision-making and operational success in the mining industry. Discrepancies between estimation methods, such as truck counts and topographic surveys, often lead to inefficiencies and failure to achieve production targets. This research aims to identify the root causes of such discrepancies at PT Bordun Indie and propose effective solutions to improve the accuracy of production estimation. Using the DMAIC (Define, Measure, Analyze, Improve, Control) methodology, this research analyzes critical factors such as human error, absence of standard operating procedures (SOPs), and reliance on manual data entry. Descriptive statistical approach and linear regression analysis were used to measure the variation and relationship between the two estimation methods. The results showed that the implementation of process standardization, digital technology integration, and continuous monitoring significantly reduced data variability, thereby improving the accuracy of production estimation. The implications of this research are not only relevant for PT Bordun Indie, but can also be widely applied in the mining industry to optimize production planning, improve decision-making, and support better achievement of production targets. This research confirms the importance of systematic improvement to drive operational efficiency and sustainability in the mining sector.