Sugar Price Prediction in East Java Using the Geometric Brownian Motion Model

Amaliyatul Hasanah

Abstract


Sugar is a national strategic commodity that plays a vital role in Indonesia's economic stability and food security. East Java, as a major sugar producer, faces fluctuating price dynamics due to various factors, including sugarcane production, supply distribution, refined sugar imports, weather conditions, and the needs of the food and beverage industry. To understand the random price movement patterns, the Geometric Brownian Motion (GBM) model is used because it is able to represent price dynamics through log-normal drift and volatility components. This study aims to predict sugar prices in East Java using the Geometric Brownian Motion (GBM) model to provide insight into price uncertainty and volatility. The study population consists of daily sugar price data in East Java in August-November 2025, with August-October 2025 data as training data and November 2025 data as testing data. Sugar price prediction uses a stochastic modeling approach, implementing GBM through multi-path simulations to capture the shift and volatility parameters of sugar price movements. Sugar price prediction using the GBM model is carried out with 50, 500, and 1000 iterations (paths). The results obtained from the GBM model effectively capture the inherent volatility of sugar prices, producing a Mean Absolute Percentage Error (MAPE) value of 0.0846% for 50 trajectories, 0.0659% for 500 trajectories, and 0.0522% for 1,000 trajectories. These results indicate that the GBM can model sugar price fluctuations in East Java and provide accurate probabilistic estimates.


Keywords


Geometric Brownian Motion; MAPE; Sugar Price

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References


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DOI: https://doi.org/10.31764/justek.v9i1.37063

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