This study was conducted at Ibnu Sina Regional Hospital in Gresik Regency with the aim of improving the accuracy of drug demand forecasting. The main issue in the hospital's drug inventory management is the inaccuracy in estimating demand, which leads to the risk of stock shortages or surpluses and disrupts healthcare services. The study seeks to compare the effectiveness of the currently used consumption-based method with the Single Exponential Smoothing method as a more adaptive alternative to changes in demand. A descriptive approach was used, utilizing historical order and usage data of ten selected generic drugs from July to December 2023. Forecasting accuracy was evaluated using the Mean Absolute Percentage Error (MAPE) indicator. The results indicate that the Single Exponential Smoothing method provides higher accuracy compared to the consumption method, with MAPE values below 10% for most of the drug data. Therefore, this method is more effective in minimizing forecasting errors and supports more efficient and timely drug procurement decisions. The study concludes that implementing the Single Exponential Smoothing method can enhance drug inventory management and is worth considering as the basis for a hospital drug demand forecasting system.
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