<![CDATA[This study aims to analyze the performance of a queueing system in a small-scale coffee shop operation using the Monte Carlo simulation method based on historical data from 2022–2026. Coffee shop operations exhibit stochastic characteristics influenced by fluctuations in customer arrivals and service time variability. Data on daily visitors, revenue, cost, and profit were processed using Microsoft Excel to construct empirical probability distributions. The simulation was executed through thousands of iterations to ensure statistical stability. The results indicate that the model effectively captures operational uncertainty, with convergent average daily profit and measurable downside risk assessed through percentile analysis and Value at Risk (VaR). The findings provide an analytical foundation for managerial decision-making regarding service capacity and cost control strategies. Monte Carlo simulation proves to be an effective tool for performance evaluation and risk management in small-scale service businesses.]]>
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