DEVELOPMENT OF SLOPE STABILITY GRAPH OF COAL MINING IN INDONESIA USING BINARY LOGISTIC REGRESSION METHOD

• Main Author: Yosef Sianipar, Agustinus
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/72847
• Institution: Institut Teknologi Bandung

Many coal mining companies in Indonesia have unstable pit slope condition even though in the initial analysis the slope condition were stable. This can be caused by factors of uncertainty, which can be in the form of spatial variability, error measurement and model uncertainties used. Several additional alternatives in the form of stability graphs have been widely used before, but have several limitations in their use, one of which has not been considered the probability to accommodate the uncertainty factor. So that currently it is still necessary to develop slope stability graphs specifically for coal mines to increase the level of confidence from the geotechnical analysis carried out. This research studies the development of slope stability graphs using the Binary Logistic Regression method with secondary data on coal mines. The method will consider the probabilistic factor which is the ratio between the probability of an event occurring and the probability of an event not occurring. From the verification results using 20 other slope stability data and performing 1 (one) slope stability return analysis on the method, a prediction accuracy of 75% was obtained. This research has produced an effective and efficient alternative tools to increase the level of confidence from geotechnical analysis and to determine slope stability quickly, by using the Slope Stability Graph to predict probability values and to predict orientation of slope stability from the analysis results in a stable or unstable potential.