Application of the Monte Carlo Method in Predicting Customer Frequency in Micro-Scale Laundry Business

Qisti Azraladiba Batubara; Lutfi Nur Yasin; Alfin Budiman Sihotang; Fauhan Alfarizi Saragih; Salsabilla Lubis; Shofwan Sasri Azhari

doi:10.59934/jaiea.v5i2.2032

Authors

Qisti Azraladiba Batubara Universitas Islam Negeri Sumatera Utara
Lutfi Nur Yasin Universitas Islam Negeri Sumatera Utara
Alfin Budiman Sihotang Universitas Islam Negeri Sumatera Utara
Fauhan Alfarizi Saragih Universitas Islam Negeri Sumatera Utara
Salsabilla Lubis Politeknik Negeri Medan
Shofwan Sasri Azhari Universitas Negeri Medan

DOI:

https://doi.org/10.59934/jaiea.v5i2.2032

Keywords:

Monte Carlo, Simulation, Probabilistic model, Customer frecuency prediction, micro-scale

Abstract

The main challenge for micro-scale laundry businesses is the variability and uncertainty in daily customer frequency, which directly impacts operational efficiency and resource planning. This study aims to model and predict the average customer frequency using the Monte Carlo Simulation. One hundred days of historical data were processed to determine the customer arrival probability distribution. The simulation was run for 5,000 iterations, resulting in a predicted average daily customer frequency of 20.57 customers/day. This value is proven valid and slightly above the historical expectation. The conclusion indicates that the Monte Carlo Method is an effective tool for modeling systems with high uncertainty. This quantitative prediction provides a strong basis for the business owner to effectively optimize employee scheduling and inventory management of raw materials.

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