Inaccurate drug inventory planning can lead to stock shortages or excess inventory, which negatively affects the efficiency of hospital services. One drug with highly fluctuating demand is Omeprazole injection 40 mg at XYZ Hospital. This study aims to forecast the demand for Omeprazole injection 40 mg using time series forecasting methods, namely Single Moving Average, 2-month Moving Average, and 3-month Moving Average. This research employed a descriptive quantitative approach using historical demand data from January to September as the basis for forecasting demand for the period of October to December. Forecast accuracy was evaluated using Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE). The results indicate that the Single Moving Average method produced the lowest MAD value of 91.33 and MSE value of 9,948.67, making it the most effective method in minimizing absolute and squared forecasting errors. The 2-month Moving Average method resulted in the lowest MAPE value of 57.91% but showed the highest MAD and MSE values, while the 3-month Moving Average method demonstrated more moderate and stable performance with error values between the other two methods. The high MAPE values across all methods indicate substantial demand variability; therefore, MAD and MSE are considered more relevant indicators for selecting the appropriate forecasting method. The findings of this study are expected to support more effective and efficient decision-making in planning the procurement of Omeprazole injection 40 mg at XYZ Hospital.
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