Analysis of medication demand forecasting using single exponential smoothing method based on consumption patterns at Bali Mandara Hospital, Indonesia

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Authors: Ni Putu Vyra Ginanti Putri, Chairun Wiedyaningsih, Endang Yuniarti
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Abstract

Drug planning requires accurate forecasting to determine the right type and amount of drugs. The Single Exponential Smoothing (SES) method is used in this study due to its ability to produce more accurate forecasts than other methods. Drugs are classified based on consumption patterns into Smooth, Intermittent, Erratic, and Lumpy to evaluate the accuracy of the SES method on each pattern. This descriptive and non-experimental study uses retrospective data from 469 drugs at Bali Mandara Hospital from January 2023 to December 2023. Data were classified based on consumption patterns with CV2 and ADI parameters, and forecasting was performed using the Eviews-12 application and evaluated with the MAPE accuracy indicator using Microsoft Excel. The clustering results showed 335 drugs with smooth consumption patterns, three with intermittent consumption patterns, 50 with lumpy consumption patterns, and 81 with erratic consumption patterns. SES gives the best results in a smooth pattern, with 71.43% of forecasts falling into the accurate, good, or reasonable category. The smooth pattern also shows highly accurate (MAPE

Fields of Study & Subjects

Forecasting Techniques and Applications Supply Chain and Inventory Management Data Mining and Machine Learning Applications

Publication details

Journal / source
Journal of Public Health and Development
Volume
24
Issue
1
Pages
107–118
Publication date
29 January 2026
Language
EN