An Application Of Double Exponential Method For Forecasting Drug Sales Stock

Abstract

The Drug Stock Forecasting Application using a web-based Double Exponential Smoothing method is designed to optimize drug inventory management, particularly at Romora Drugstore. Modern computing technology plays a crucial role in supporting the operational activities of various business sectors, providing quick, precise, and accurate information. This efficiency is especially important in drugstores, where computers assist employees in managing tasks, such as drug inventory. Romora Drugstore, like many others, faces fluctuating monthly drug demands, making accurate forecasting essential to avoid stockouts or overstock situations. To address this challenge, this research proposes the Double Exponential Smoothing method as a forecasting tool. This method predicts future stock requirements based on historical data, enabling better management of drug supplies. By analysed past sales transactions, the application can forecast future demand, helping the drugstore ensure optimal stock levels, prevent financial losses, and enhance overall operational efficiency.