Implementasi Algoritma Monte Carlo Untuk Memprediksi Permintaan Aksesoris Mobil

Abstract

Toko ADS Variasi dan AC Mobil is a shop engaged in the sale of car accessories, repairing and replacing car air conditioning spare parts in Kota Palembang, Toko ADS Variasi dan AC Mobil faces challenges in predicting the demand for the right car accessories to sell so that there is no excess or shortage of stock items. So that a method is needed that can be implemented into the inventory system and sales and purchase records. In this research, the author uses the Monte Carlo Algorithm which will generate predictions of demand for car accessories by considering variations in factors that affect demand, taking historical data on car accessories sales from the relevant period, then conducting Monte Carlo simulations using the data as input. The simulation will be repeated as many times as needed and provide results in the form of probability distributions of demand for car accessories that may occur. By taking the average value of the probability distribution, an accurate demand prediction can be generated. The result obtained from this research is a more accurate prediction of demand for car accessories based on the latest historical data  so that stores can determine the right amount of stock and avoid overstocking or understocking. In addition, by considering the factors that affect demand, stores can plan more effective marketing strategies and increase store profits