Penilaian Risiko dan Alokasi Modal pada Investasi Proyek Tambang di Bawah Ketidakpastian: Peran Simulasi Monte Carlo

Abstract

Mining project valuation rests on many interacting uncertain variables, from commodity prices, exchange rates, capital and operating costs, ore grade and recovery, to fiscal terms and the discount rate. Deterministic discounted cash flow analysis is useful as a baseline but offers little information about the probability and severity of loss, which weakens it as a basis for capital allocation decisions. This review positions Monte Carlo simulation as a probabilistic investment appraisal method. The research method is a systematic literature review guided by PRISMA 2020, combining two-stage screening with thematic synthesis of eligible studies. Three search sources were used, namely Publish or Perish, ScienceDirect, and ResearchRabbit, with all records managed in Rayyan. From 6,834 initial records, a two-stage title, abstract, keyword, and metadata screening process followed by full-text verification of potentially eligible studies retained 67 studies, comprising 52 direct mining valuation studies and 15 methodological support studies. The synthesis shows that Monte Carlo simulation moves the basis of decision from a single point value to a distribution of project value together with downside risk metrics such as probability of loss, value-at-risk, and conditional value-at-risk. The review delivers a taxonomy of eight valuation method families mapped to investment decision contexts, a mapping of risk drivers to decision metrics, and a critique of simplified dependency assumptions that may make downside risk estimates too optimistic.