The economic feasibility valuation method is very important in determining the value of a project. The existence of high uncertainty in the mining industry, both from a technical and non-technical perspective, causes the risk of mining projects to be relatively higher compared to other industries. uncertainty is modeled by an unbroken probability series. This distribution is widely used to model uncertainty from non-technical factors such as commodity prices. To describe the uncertainty of the variable input in the simulation, the monte Carlo simulation technique can be used. In addition, to predict the selling price of coal using the bat algorithm. The results show that the prediction of coal prices is one of the parameters that are difficult to predict. To determine the selling price can use a predictive approach with the help of artificial intelligence. The price prediction using the Monte Carlo simulation results in the selling price of coal with calories 5700 kcal/kg is $ 42.2 per tonne. If using the bat algorithm is $ 42.18 per tonne. The feasibility analysis of a mining project using the DCF method shows the result NPV Maximal on stripping ratio 2.5 with a coal volume is 20 million tonnes.
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