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