Peramalan Permintaan Roti Harian dengan Simulasi Monte Carlo di Reza Bakery

Abstract

The fluctuating daily demand at Reza Bakery leads to an imbalance between production capacity and consumer needs. This study aims to forecast the daily demand of the three best-selling bread products using the Monte Carlo simulation method: Small White Bread, Mocha Bread, and French Chocolate Bread. Sales data from April 2025 covering 30 days were used as the simulation basis. The simulation involves calculating the probability distribution of demand, generating random numbers, and mapping them to demand predictions. Results show that daily demand predictions range from 33–40 units for Small White Bread, 16–22 units for Mocha Bread, and 7–12 units for French Chocolate Bread. This method helps in formulating more efficient production strategies, with good accuracy estimates based on the match between simulation results and historical trends. The simulation offers potential to reduce overstock risks and improve operational efficiency.