Comparative Forecasting Demand For Robusta Ground Coffee Product in SME SL Malang Regency Using Holt-Winters Exponential Smoothing and Seasonal ARIMA Method
Small Medium Enterprise SL (SME SL) has a fluctuating volume of demand for ground coffee and to forecast demand for the following month, they only use the owner's intuition, so they cannot ensure the availability of product stocks precisely. Therefore, the use of accurate forecasting methods is...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Brawijaya
2025-07-01
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| Series: | Habitat |
| Subjects: | |
| Online Access: | https://habitat.ub.ac.id/index.php/habitat/article/view/3731 |
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| Summary: | Small Medium Enterprise SL (SME SL) has a fluctuating volume of demand for ground coffee and to forecast demand for the following month, they only use the owner's intuition, so they cannot ensure the availability of product stocks precisely. Therefore, the use of accurate forecasting methods is necessary for forecasting in the future. The purpose of this research is to describe the demand forecasting for robusta ground coffee in SME SL, analyze the demand forecasting for robusta ground coffee products in SME SL and compare the value of forecasting accuracy to get the best forecasting method. Determination of the sample using judgment sampling is the owner of SME SL. The data used is ground coffee demand data for the period January 2015 to August 2022. The forecasting methods used is Holt-Winters Exponential Smoothing and SARIMA. The results showed that SME SL applies executive opinion for forecasting, and the best model for forecasting product demand is the SARIMA model (0,1,1) (0,1,1)12, because it produces an MSE error value of 1.8868 and a MAPE value of 0.20% with the highest demand in January 2023 of 866.32 kg. Suggestions for SME SL to increase demand for their products by applying the SARIMA method, developing appropriate process and capacity planning strategies and making the best use of existing tourism opportunities. |
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| ISSN: | 0853-5167 2338-2007 |