<![CDATA[Abstract. Gold is one of the most popular investment instruments because its price fluctuates due to various economic factors. Therefore, a method capable of modeling stochastic price movements is needed. Geometric Brownian Motion (GBM) has been widely used to model financial asset prices because it incorporates both deterministic and stochastic components. This study aims to determine the accuracy of the GBM model in forecasting gold prices based on the Mean Absolute Percentage Error (MAPE) and to forecast gold prices for the next five periods. Daily gold price data from 1 January 2024 to 31 December 2025, obtained from Investing.com, were used in this study. The data were divided into 415 training observations and 104 testing observations. Model parameters were calculated based on return values, and Monte Carlo simulations were performed using 100, 500, and 1000 iterations. Model accuracy was evaluated using MAPE, and the model with the smallest MAPE value was selected for forecasting. The results showed that the Monte Carlo simulation with 500 iterations produced the best model with a MAPE value of 7.8838%. Based on this model, gold prices were projected to increase from 4,321.53 USD/oz in the first period to 4,344.99 USD/oz in the fifth period. These findings indicate that the GBM model provides good forecasting accuracy and is a suitable alternative for short-term gold price forecasting. Abstrak. Emas merupakan salah satu instrumen investasi yang nilainya berfluktuasi akibat berbagai faktor ekonomi, sehingga diperlukan metode yang mampu memodelkan pergerakan harga emas secara stokastik. Penelitian ini bertujuan untuk mengetahui tingkat akurasi model Geometric Brownian Motion (GBM) dalam melakukan peramalan harga emas berdasarkan nilai Mean Absolute Percentage Error (MAPE) serta memperoleh hasil peramalan harga emas untuk lima periode ke depan. Data yang digunakan berupa harga emas harian periode 1 Januari 2024–31 Desember 2025 yang diperoleh dari Investing.com. Data dibagi menjadi 415 data training dan 104 data testing. Parameter model dihitung berdasarkan nilai return, kemudian dilakukan simulasi Monte Carlo sebanyak 100, 500, dan 1000 iterasi. Akurasi model dievaluasi menggunakan MAPE, kemudian model terbaik digunakan untuk melakukan peramalan. Hasil penelitian menunjukkan bahwa simulasi Monte Carlo dengan 500 iterasi menghasilkan model terbaik dengan nilai MAPE sebesar 7,8838%. Berdasarkan model tersebut, harga emas diproyeksikan mengalami tren meningkat selama lima periode ke depan, yaitu dari 4.321,53 USD/oz pada periode pertama menjadi 4.344,99 USD/oz pada periode kelima. Hasil penelitian menunjukkan bahwa model GBM mampu memberikan tingkat akurasi yang baik untuk peramalan harga emas jangka pendek.]]>
