Real-Time Information System Integration In Coal Production And Distribution Management
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Abstract
Coal production faces challenges in data management and operational coordination efficiency. This study examines the integration of an information system using AI and real-time capabilities to improve the efficiency and effectiveness of coal production. With a system development approach using the SDLC Waterfall method and dummy data simulation, the system successfully accelerates production monitoring, increases data accuracy, and supports rapid decision-making. These findings provide a strong foundation for developing adaptive and effective mining information systems in the digital era. The applied method delivers optimal results in measuring pressure and temperature as well as detecting coal sensor values using an AI-based IoT system. Evaluation results show a reduction in reporting response time by up to 40%, an increase in stored data accuracy up to 95%, and positive feedback from simulation users regarding ease of access and production monitoring.
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Yulistiawan, B. S. ., Krisnanik, E. ., Puspita Dewi, C. N. ., & Pinastika, I. W. R. . (2025). Real-Time Information System Integration In Coal Production And Distribution Management. Journal of Intelligent Decision Support System (IDSS), 8(3), 162-172. Retrieved from https://www.idss.iocspublisher.org/index.php/jidss/article/view/303
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Vergara, D., Rubio, M. P., & Lorenzo, M. (2017). On the design of virtual reality learning environments in engineering. Multimodal Technologies and Interaction, 1(2). https://doi.org/10.3390/mti1020011
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