Determination of Slope Stability Safety Factor based on the Slope Mass Rating (SMR) Method and Linearity Analysis of Discontinuity Conditions and Orientations using Linear Regression Machine Learning: a Case Study of the Breksi Cliff Area, Yogyakarta

Abstract

The Tebing Breksi area is a geotourism of ancient volcanic remains in the Southern Mountains in the Semilir Formation that existed in the Oligocene-Miocene, but not many have discussed the rock mechanic’s side. The observation is conducted in Sambirejo, Prambanan, Sleman Regency, in the Special Region of Yogyakarta. Slope stability study by assessing slope kinematics and rock mass classification using the SMR Method, which assumes that the slope is in a state of failure, and this method evaluates whether the forces and moments acting on each slice are in equilibrium. The data used are slope geometry data, lithology description, and Rock Mass Rating classification data taken along the scanline. Kinematic analysis of the slope is obtained based on the stereographic projection results using Dips and rock slope quality and stability analysis based on RMR and SMR parameters. The RQD value of the slope is 99.94% in the excellent category, and the RMR value obtained is 77 in the good category. The kinematic analysis shows the mass movement that will occur as a toppling avalanche orientated at 46.05%, so the SMR value is 73 in the good category. The heatmap and linear regression analysis between conditions and discontinuity orientations with respect to RMR-SMR values indicate a varied linear relationship, with some variables showing positive correlation and others showing negative correlation. From these results, the existing rock slope has greater than 1 safety factor value, which states that the slope is included in a stable category or rarely has the potential for landslides.