Qistan, Muhammad Hafits
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Rock Mass Classification Using RMR and GSI for Slope Stability at PT Bukit Asam, Tanjung Enim Sabila, Dona; Harnani, Harnani; Qistan, Muhammad Hafits; Sidiq, Muhammad
Jambura Geoscience Review Vol 7, No 2 (2025): Jambura Geoscience Review (JGEOSREV)
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jgeosrev.v7i2.32492

Abstract

Evaluating slope stability in tropical open-pit mining environments remains a technical challenge due to the complex geological formations and the influence of dynamic climatic conditions, particularly intense rainfall and high humidity. This study aims to assess the effectiveness of integrating the Rock Mass Rating (RMR) system and the Geological Strength Index (GSI) for classifying rock mass quality and predicting slope stability in such settings. Field data were collected from interbedded claystone and sandstone formations through systematic mapping of RMR parameters, including Rock Quality Designation (RQD), spacing and condition of discontinuities, groundwater presence, and uniaxial compressive strength. Complementary evaluations using GSI focused on block structure, joint surface conditions, and weathering characteristics. The RMR analysis classified the rock mass as Class III (Fair Rock), indicating moderate stability. However, the system’s static framework and limited responsiveness to rapid hydrogeological changes posed constraints in capturing the actual slope behavior. In contrast, GSI, with values ranging between 40 and 50, offered enhanced interpretive depth by incorporating qualitative assessments of lithological heterogeneity and structural anisotropy. The adaptability of GSI proved critical in environments where visual and textural indicators of degradation fluctuate spatially and temporally. The combined application of RMR and GSI enabled a more accurate, context-sensitive geotechnical evaluation, bridging the gap between empirical rigidity and field-based complexity. This integrated methodology supports more reliable engineering decisions and enhances the predictive capacity for slope failures in tropical geological settings, emphasizing the necessity for multidimensional classification tools in geotechnical practice.