Monte Carlo Simulation in Predicting Trends in Demand for Coconut Milk at PT. Flash Food

Abstract

Coconut milk is one of the perishable food ingredients. PT. Flash Food receives daily orders for coconut milk from hospitals in the city of Padang. Every day, PT. Flash Food must provide coconut milk in the required quantity and at the right time. Therefore, a method is needed to predict the coconut milk demand for the next day. The Monte Carlo simulation method is used to predict the demand for several days ahead based on the existing data. The data used is from October and November. This data will be simulated to generate predictions for the next 7 days. To test the accuracy of the Monte Carlo simulation, the simulated data is compared with the actual data. The comparison results show an average accuracy of 90.6%. The Monte Carlo simulation is then translated into a programming language so that PT. Flash Food can easily use the simulation.