Optimisasi Ramalan Penjualan ATK: Simulasi Monte Carlo untuk Gandria Store - Zeki Alex Sandra, Zeki; Rizki lubis, Alya; Nabila, Putri; Anggraini, Sari; Efriyanti, Liza (JOVISHE : Journal of Visionary Sharia Economy, 2024)
In the face of uncertainty and complexity in business, forecasting sales is a major challenge, especially in the Office Stationery (ATK) category. Gandaria Store at UIN Sjech M. Djamil Djambek Bukittinggi seeks to improve sales forecasting accuracy to optimise stock and marketing strategies. This article proposes the use of the Monte Carlo Method as an innovative approach to forecasting stationery sales at Gandaria Store. The Monte Carlo method is a statistical simulation technique that generates a large number of scenarios based on the probability distribution of the variables that affect sales. By integrating historical data, seasonal factors, economic conditions, and promotional strategies, this method provides a more accurate forecast of future demand. This study uses a quantitative method with a Monte Carlo simulation approach for the period 1 June 2024 to 21 June 2024. The data used are stationery sales transactions during 2021 to 2023. The simulation was conducted with a mathematical model based on historical data to produce an optimal sales forecast. The results show that the use of the Monte Carlo method can improve prediction accuracy compared to traditional methods. This approach helps to optimise inventory, reduce the risk of shortages or overstocks, and support more effective marketing strategies, thus potentially improving the sales performance of stationery at Gandaria Store. The contribution of this research is global, as the use of the Monte Carlo method can be applied to various business sectors around the world that face similar challenges in forecasting demand. This approach can also provide deeper insights into more efficient stock management and marketing strategy planning in the global market, particularly in the retail sector.