Application of the Fuzzy Grey Markov Model (2,1) in Forecasting Gold Prices in Indonesia

Abstract

Gold investment is currently considered promising even though gold prices continue to change. This is a challenge for investors in obtaining optimal profits, so an appropriate forecasting method is needed to predict the price of gold in Indonesia. This research introduces a novel approach called the Fuzzy Grey Markov Model (2,1) (FGMM(2,1)), which has never been used before. This combined method utilizes fuzzy logic to handle uncertainty in the data, the Grey model to form a forecasting model, and Markov chains to determine the state transition probability matrix. The FGMM(2,1) approach is interesting to study because it can be considered in forecasting data that shows varying increases and decreases, such as the gold price data used in this research. Furthermore, the method's accuracy level was calculated based on the Mean Absolute Percentage Error (MAPE) value, achieving very accurate forecasting results with a MAPE value of 4.32%.