Rizky Arbi Dwialfawan

UJI BAIK SUAI UNTUK PARAMETER MASUKAN EVALUASI KESTABILAN LERENG PADA AREA TAMBANG AIR LAYA BARAT PT BUKIT ASAM Tbk

Introduction

Uji baik suai untuk parameter masukan evaluasi kestabilan lereng pada area tambang air laya barat pt bukit asam tbk. Analisis kestabilan lereng tambang terbuka PT Bukit Asam Tbk. Uji baik suai Chi-kuadrat pada parameter masukan menemukan distribusi probabilitas (normal, lognormal, gamma) guna mencegah longsor.

Abstract

Abstrak Pada tambang terbuka, melakukan analisa kestabilan lereng adalah hal yang wajib dilakukan. Hal tersebut dilakukan agar operasi penambangan pada tambang tersebut berjalan dengan baik dan mencegah terjadinya kecelakaan kerja akibat longsor pada lereng tambang. Untuk menganalisa kestabilan lereng tambang dapat digunakan dengan pendekatan probabilistik, dimana probabilistik adalah suatu cara untuk menentukan nilai FK dengan cara mempeerlakukan nilai parameter masukan sebagai variabel acak. Pada artikel ini parameter masukan tersebut akan dilakukan uji baik suai dengan metode Chi-kuadrat untuk mengetahui distribusi masing-masing yang sesuai dengan data yang ada dan juga mendapatkan nilai statistik deskriptif seperti rata-rata, varans dan standar deviasi. Untuk distribusi yang digunakan ada empat yaitu normal, lognormal. Gamma dan eksponensial. Dimana hasil dari uji baik suai tersebut mendapatkan bahwa bobot isi natural dan sudut gesek menunjukan fungsi distribusi yang sesuai adalah normal, sedangkan hasil uji baik suai untuk kohesi menunjukan bahwa distribusi yang sesuai adalah normal, lognormal dan gamma. Kata kunci: probabilistik, uji baik suai, distribusi AbstractIn open pit mining, analyzing slope stability is a must thing to do. This is done so that mining operations at the mine run well and prevent work accidents due to landslides on the slopes of the mine. To analyze the stability of the mine slope can be used with a probabilistic approach, where probabilistic is a way to determine the FK value by treating the value of the input parameter as a random variable. In this article, the input parameters will be tested according to the Chi-square method to determine the each of distribution according to the existing data and also get the value of descriptive statistics such as average, variance and standard deviation. For the distribution used there are four, namely normal, lognormal, Gamma and exponential. Where the results of the fitting-test found that the weight of the natural contents and the friction angle showed that the corresponding distribution function was normal, while the results of the fitting-test for cohesion showed that the appropriate distribution was normal, lognormal and gamma.Keywords: probabilistic, fitting-test, distribution

Review

This paper addresses a critical aspect of open-pit mining operations: the probabilistic assessment of slope stability, specifically focusing on the characterization of input parameters. The authors highlight the necessity of robust slope stability analysis to ensure operational safety and prevent accidents from landslides. The study proposes using a probabilistic approach, where key input parameters are treated as random variables. The primary objective is to apply goodness-of-fit tests to these parameters for the PT Bukit Asam Tbk Air Laya Barat Mine Area, thereby identifying their appropriate statistical distributions and calculating essential descriptive statistics, which forms a fundamental basis for more advanced stability evaluations. Methodologically, the study employs the Chi-square goodness-of-fit test to evaluate four commonly used statistical distributions: normal, lognormal, Gamma, and exponential. The input parameters subjected to this rigorous analysis include natural content weight, friction angle, and cohesion. The findings provide specific insights into the statistical behavior of these parameters. Specifically, the goodness-of-fit test results indicated that both natural content weight and friction angle are best represented by a normal distribution. For cohesion, the analysis revealed that normal, lognormal, and Gamma distributions all demonstrated a suitable fit to the observed data. Overall, this article presents a valuable and methodologically sound preliminary study that contributes significantly to understanding the stochastic nature of geotechnical parameters in a specific mining context. The application of the Chi-square test to identify suitable distributions for input parameters is a crucial step towards implementing more realistic and reliable probabilistic slope stability analyses. While the abstract effectively outlines the process and key findings, a more detailed discussion in the full paper on the implications of multiple fitting distributions for cohesion, and how this ambiguity might be handled in subsequent stability calculations, would further enhance its value. This research provides a solid foundation for future probabilistic slope stability assessments at the Air Laya Barat mine.

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