Utilization of Software for Employee Working Time Efficiency and Accuracy of Coal Reserve Calculation

Authors

  • Denny Boy Sitanggang Universitas Dirgantara Marsekal Suryadarma
  • I Dewa Ketut Kerta Widana Universitas Dirgantara Marsekal Suryadarma
  • Dewi Puspaningtyas Faeni Universitas Dirgantara Marsekal Suryadarma

DOI:

https://doi.org/10.59784/glosains.v7i3.785

Keywords:

Calculation Accuracy, Coal Reserves, Work Efficiency, Minescape, Mining Software

Abstract

Background: Digital transformation in the mining sector has increasingly encouraged the adoption of specialized software to improve operational performance, particularly workforce time efficiency and the precision of technical calculations.

Objective: This study aimed to evaluate the effect of mining software utilization on employee working time efficiency and the accuracy of coal reserve calculations, addressing a research gap in systematically examining these relationships within open-pit mining operations.

Methods: This study employed an integrated quantitative–qualitative approach using a comparative method between manual work processes and software-based processes. The analysis used geological data, topographic data, and mining technical parameters from open-pit mining operations. Data processing was conducted using MineScape to simulate mine planning and reserve estimation, and the results were compared with those obtained through previously used conventional methods.

Results: The results indicated that software utilization significantly reduced job completion time and improved the consistency and accuracy of reserve calculation results. In addition, more systematic data integration through software helped minimize potential calculation errors and accelerate the decision-making process.

Conclusion: This study concluded that the utilization of mining software had a positive impact on improving work efficiency and the accuracy of coal reserve calculations. Therefore, the implementation of software-based technology is considered a relevant strategy for supporting performance optimization and competitiveness in the mining industry in the digital era.

References

Arifin, R. N., Sianipar, G. W. W., & Komariah, A. (2019). Computer based management information system towards employee performance in Indonesian National Police Educational Headquarters Bandung. 2nd International Conference on Research of Educational Administration and Management (ICREAM 2018), 37–41.

Barnewold, L., & Lottermoser, B. G. (2020). Identification of digital technologies and digitalisation trends in the mining industry. International Journal of Mining Science and Technology, 30(6), 747–757.

Bhattacharyya, S. S., & Shah, Y. (2022). Emerging technologies in Indian mining industry: an exploratory empirical investigation regarding the adoption challenges. Journal of Science and Technology Policy Management, 13(2), 358–381. https://doi.org/10.1108/JSTPM-03-2021-0048

Darling, P. (2011). SME mining engineering handbook (Vol. 1). SME.

Ediriweera, A., & Wiewiora, A. (2021). Barriers and enablers of technology adoption in the mining industry. Resources Policy, 73, 102188.

Flores-Castañeda, R. O., Olaya-Cotera, S., López-Porras, M., Tarmeño-Juscamaita, E., & Iparraguirre-Villanueva, O. (2025). Technological advances and trends in the mining industry: a systematic review. Mineral Economics, 38(2), 221–236. https://doi.org/10.1007/s13563-024-00455-w

Gackowiec, P., Podobińska-Staniec, M., Brzychczy, E., Kühlbach, C., & Özver, T. (2020). Review of key performance indicators for process monitoring in the mining industry. Energies, 13(19), 5169.

Krisna, O. S., & Faturohman, T. (2021). Economic analysis of coal mining project using real option valuation method. Review of Integrative Business and Economics Research, 10, 450–470.

Laudon, K. C., & Laudon, J. P. (1996). Management information systems (Vol. 8). Prentice Hall Englewood Cliffs, New Jersey.

Litvinenko, V. S. (2020). Digital economy as a factor in the technological development of the mineral sector. Natural Resources Research, 29(3), 1521–1541. https://doi.org/10.1007/s11053-019-09568-4

Lööw, J. (2022). Understanding technology in mining and its effect on the work environment. Mineral Economics, 35(1), 143–154. https://doi.org/10.1007/s13563-021-00279-y

Majeed, H., & Iftikhar, T. (2026). Automation and Sustainability in Industrial Revolution 6.0 Coal Mining. In Intelligent Manufacturing in Industry 6.0: A Climate Resilience Approach (pp. 581–607). Springer. https://doi.org/10.1007/978-3-032-07278-8_15

Mamba, N. B., Matshediso, B. B., & Verma, R. (2023). Application of geological data analysis and assessment techniques for coal resource evaluation.

Nagovitsyn, O. V, & Lukichev, S. V. (2025). Engineering Geological Block Model as an Informational Framework for Digital Management in Mining. Journal of Mining Science, 61(6), 1056–1065. https://doi.org/10.1134/S1062739125060201

Quansah, E. A., & Yakin, Z. (2025). Probabilistic and Stochastic Mine Planning: A Review of Methods for Managing Mine Project Uncertainties. Journal Of Engineering And Computer Sciences, 4(12), 39–46.

Saługa, P. W., Szczepańska-Woszczyna, K., Miśkiewicz, R., & Chłąd, M. (2020). Cost of equity of coal-fired power generation projects in Poland: Its importance for the management of decision-making process. Energies, 13(18), 4833. https://doi.org/10.3390/en13184833

Sharma, A. S., Prakash, A., Mandal, S. K., Prasanth, K., Kumbhakar, D., & Jaiswal, P. (2023). Reserve Estimation Through Conventional Method and Computer-Aided Software: A Comparative Case Study. Asian Mining Congress, 32–44. https://doi.org/10.1007/978-3-031-46966-4_3

Sishi, M., & Telukdarie, A. (2020). Implementation of Industry 4.0 technologies in the mining industry-a case study. International Journal of Mining and Mineral Engineering, 11(1), 1–22.

Suparno, F., Paithankar, A., & Chatterjee, S. (2025). Minable coal reserve estimation by incorporating tonnage and calorific value uncertainties by successive multiple-point and two-point geostatistical simulation algorithms. Journal of the Southern African Institute of Mining and Metallurgy, 125(9), 555–570. https://doi.org/10.17159/2411-9717/3448/2025

Wang, G., Ren, H., Zhao, G., Zhang, D., Wen, Z., Meng, L., & Gong, S. (2022). Research and practice of intelligent coal mine technology systems in China. International Journal of Coal Science & Technology, 9(1), 1. https://doi.org/10.1007/s40789-022-00491-3

Zhou, W., Wang, T., Zhu, J., Tao, Y., & Liu, Q. (2024). Perceived working conditions and employee performance in the coal mining sector of China: a job demands-resources perspective. Chinese Management Studies, 18(6), 1656–1677. https://doi.org/10.1108/CMS-06-2023-0292

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Published

2026-06-26