ANALYSIS OF THE EFFECT OF AMOUNT ROCK PARAMETERS DATA IN DETERMINING PROBABILITY OF FAILURE

• Main Author: Jamil Fawzi, Shabrun
• Format: Final Project
• Language: Indonesia
• Subjects: Pertambangan dan operasi berkaitan
• Online Access: https://digilib.itb.ac.id/gdl/view/51642
• Institution: Institut Teknologi Bandung

The stability of a mine slope is generally expressed by the value of the Safety of Factor (SoF), but SoF has deterministic uncertainty in its calculations. The Probability of Failure (PoF) method is presenting by using all available soil characteristics data to accommodate any variations that may occur. This PoF method requires data on cohesion, friction angle, and unit weight. The purpose of this study was to determine the effect of the amount of rock parameter data and the minimum required data to obtain the optimal PK value. In this study, the data of cohesion, friction angle, and unit weight were used. These were random data from a coal mining company PT XYZ which has rock lithology in the form of mudstone and sandstone. The data was taken randomly 30 times for each group of data intervals with each group having 10, 20, 30, 40, 50, and 60 data. The data were analyzed statistically using @RISK and SPSS software to obtain the type of data distribution, mean, standard deviation, maximum relative value, and minimum relative value. This parameter is used as input for Slide 6.0 software with a single static slope whose slope size has been assumed along with the location of the rock lithology so that the PoF value of the slope is obtained. The 30 PoF data is then made a straight line equation for each group of the amount of data and is statistically processed for each group of the amount of data in order to obtain a straight line equation and descriptive statistics. For descriptive statistics in the form of range, mean, and standard deviation are included in the graph for each data interval from 10 to 60. From the graph, it can be seen that the more data used, the smaller the range and standard deviation, which means the smaller the distribution of PoF data obtained. So, it can be concluded that it is more representative, but it has no effect on the mean of the PoF data obtained. For standard deviation, the power line equation is obtained as a reference in calculating the minimum amount of data to be used in PK calculations. From the graph, it can be seen that when the amount of data is > 40 the standard deviation results have not changed too much and if you enter a standard deviation of 2. 4 9 as the y axis in the equation of the power line y 108.?x-0·966 the x value is obtained as the minimum amount of data is 50 data. So, when calculating PoF using Slide 6.0 as minimum as possible use 40 data or 50 data in order to get good and representative PoF results.