PREDICTION OF LAUNDRY SERVICE QUEUE VOLUME USING MONTE CARLO SIMULATION BASED ON RJ-EDITOR ANALYSIS ON JAMOVI

Abstract

Uncertainty in daily customer arrival volume in the laundry business often leads to queue accumulation and inefficient resource utilization. This study aims to predict the laundry queue volume for the next 30 days to optimize operational capacity planning using the Monte Carlo Simulation integrated into the Jamovi software via the Rj-Editor module. Using 90 days of historical volume data, the simulation process was executed via R-based scripts to generate probability distributions and random numbers. The simulation results indicate an average predicted daily volume of [X] kg, with a cumulative monthly volume of [Y] kg. The integration of Monte Carlo simulation within Jamovi provides an efficient, accurate, and user-friendly analytical tool to assist business owners in scheduling staff and managing raw material inventory.