This study aims to apply the Monte Carlo simulation method to predict daily sales in a small-scale bakery enterprise to support risk-based production planning. The data used consisted of historical daily sales records analyzed to obtain statistical parameters, including mean and standard deviation. The results indicate that daily demand follows a normal distribution with an average of 151.73 units. A Monte Carlo simulation with 10,000 iterations was conducted to estimate the distribution of daily profit and associated risk levels. The findings show an average daily profit of IDR 199,029 with a 95% Value at Risk (VaR) of IDR 99,952. Furthermore, a positive correlation of 0.629 was identified between demand and profit. These results demonstrate that the Monte Carlo method is effective in modeling demand uncertainty and supporting more optimal and efficient production decision-making in micro and small enterprises.
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