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Prediction Of Drug Sales Using Methods Forecasting Double Exponential Smoothing (Case Study : Hospital Pharmacy of Condong Catur)
Abstract
Purpose: Knowing the best alpha value from the data for each type of drug with various alpha parameters in the Double Exponential Smoothing Method and knowing the prediction results on each type of drug data at the Condong Catur Hospital pharmacy.
Design/methodology/approach: Applying the Double Exponential Smoothing method with alpha parameters 0.1; 0.2; 0.3; 0.4; 0.5; 0.6; 0.7; 0.8; 0.9
Findings/result: The test results on a system built using test data show that the double exponential smoothing method provides accuracy below 20% by producing a different Alpha (α) for each type of drug because the trend patterns in each drug sale are different at the Pharmacy at the Condong Catur Hospital. .
Originality/value/state of the art: Based on previous research, this study has similar characteristics such as themes, parameters and methods used. Previous researchers used smoothing methods such as Double Exponential Smoothing in predicting stock / sales of goods
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DOI: https://doi.org/10.31315/telematika.v18i1.4586
DOI (PDF): https://doi.org/10.31315/telematika.v18i1.4586.g3349
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