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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University of Brawijaya
2025-07-01
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| Online Access: | https://habitat.ub.ac.id/index.php/habitat/article/view/3731 |
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| author | Annisa Zahara Lutfi Heptari Elita Dewi Djoko Koestiono Ajeng Rizqya Shabrina Aleisha Julia Deme Anak Julin |
| author_facet | Annisa Zahara Lutfi Heptari Elita Dewi Djoko Koestiono Ajeng Rizqya Shabrina Aleisha Julia Deme Anak Julin |
| author_sort | Annisa Zahara Lutfi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-a86909cfa7be48ec8802d7b7a1e9b35f |
| institution | DOAJ |
| issn | 0853-5167 2338-2007 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | University of Brawijaya |
| record_format | Article |
| series | Habitat |
| spelling | doaj-art-a86909cfa7be48ec8802d7b7a1e9b35f2025-08-20T03:01:41ZengUniversity of BrawijayaHabitat0853-51672338-20072025-07-013629410410.21776/ub.habitat.2025.036.2.83528Comparative Forecasting Demand For Robusta Ground Coffee Product in SME SL Malang Regency Using Holt-Winters Exponential Smoothing and Seasonal ARIMA MethodAnnisa Zahara Lutfi0Heptari Elita Dewi1Djoko Koestiono2Ajeng Rizqya Shabrina3Aleisha Julia Deme Anak Julin4Faculty of Agriculture, Universitas Brawijaya, IndonesiaFaculty of Agriculture, Universitas Brawijaya, IndonesiaFaculty of Agriculture, Universitas Brawijaya, IndonesiaRegis Collage, Weston, Massachusetts, USAUniversity of Putra Malaysia, MalaysiaSmall 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.https://habitat.ub.ac.id/index.php/habitat/article/view/3731coffeedemand forecastingholt-winter exponential smoothingsarima |
| spellingShingle | Annisa Zahara Lutfi Heptari Elita Dewi Djoko Koestiono Ajeng Rizqya Shabrina Aleisha Julia Deme Anak Julin Comparative Forecasting Demand For Robusta Ground Coffee Product in SME SL Malang Regency Using Holt-Winters Exponential Smoothing and Seasonal ARIMA Method Habitat coffee demand forecasting holt-winter exponential smoothing sarima |
| title | Comparative Forecasting Demand For Robusta Ground Coffee Product in SME SL Malang Regency Using Holt-Winters Exponential Smoothing and Seasonal ARIMA Method |
| title_full | Comparative Forecasting Demand For Robusta Ground Coffee Product in SME SL Malang Regency Using Holt-Winters Exponential Smoothing and Seasonal ARIMA Method |
| title_fullStr | Comparative Forecasting Demand For Robusta Ground Coffee Product in SME SL Malang Regency Using Holt-Winters Exponential Smoothing and Seasonal ARIMA Method |
| title_full_unstemmed | Comparative Forecasting Demand For Robusta Ground Coffee Product in SME SL Malang Regency Using Holt-Winters Exponential Smoothing and Seasonal ARIMA Method |
| title_short | Comparative Forecasting Demand For Robusta Ground Coffee Product in SME SL Malang Regency Using Holt-Winters Exponential Smoothing and Seasonal ARIMA Method |
| title_sort | comparative forecasting demand for robusta ground coffee product in sme sl malang regency using holt winters exponential smoothing and seasonal arima method |
| topic | coffee demand forecasting holt-winter exponential smoothing sarima |
| url | https://habitat.ub.ac.id/index.php/habitat/article/view/3731 |
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