Journal ID : TRKU-21-03-2020-10566
[This article belongs to Volume - 62, Issue - 03]
Total View : 165

Title : A Comparison of Spatial Interpolation Methods to Estimate Coal Thickness and Quality Based on The Value of Root Mean Square Error (RMSE)

Abstract :

Exploration is one of the activities of the mining process which aims to obtain information about the geological conditions of a deposit that is below the surface of the land. Exploration activities have risks and require a large cost. Therefore, a more accurate estimation method is needed in determining the value of areas that are not sampled in exploration based on the surrounding data. In coal deposits, there are two main output parameters which are coal thickness and quality. In this study, the coal quality parameters used are calorific and sulfur values. In this study, we will compare the Kriging method with Inverse Distance Weighting, in estimating coal thickness and quality. The aim is to find out the most accurate estimation of coal thickness and quality between the Kriging and IDW methods based on the Root Mean Square Error (RMSE) value. The method of testing the estimation results is cross validation. The choice of the variogram model is based on the lowest RMSE value. The research method used is a quantitative method. Coal exploration data in the form of bar data were analyzed with descriptive statistics with Minitab 17 software and continued with geostatistical analysis using GS + software. From the results of the calculation of the two estimation methods, it was found that the kriging method was more accurate than the IDW method based on the lower RMSE Kriging value on the thickness data, calorific value and coal sulfur worth 1,622 m, 71,504 Kcal / Kg, and 0.140% compared to the IDW method RMSE on coal thickness, calorific value, and sulfur data are 1,704 m, 74,731 Kcal / Kg, and 0.142%

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