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All Journal Jurnal Riset Informatika
Winda Wulandari
STMIK Royal Kisaran
Computer Science & IT

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FORECASTING OYSTER MUSHROOM SALES USING THE DOUBLE EXPONENTIAL SMOOTHING METHOD AT KUB RUMAH MUSHROOM BERSAMA Winda Wulandari; Havid Syafwan; Muhammad Ihsan
Jurnal Riset Informatika Vol 4 No 4 (2022): Period of September 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (989.569 KB) | DOI: 10.34288/jri.v4i3.417

Abstract

The amount of oyster mushroom production is often not by consumer orders due to a lack of attention to the mushroom stock in the Mushroom House KUB. The purpose of this study is to apply double exponential smoothing (DES) to predict future sales of oyster mushrooms so that consumer needs are met. This research method uses quantitative methods. The data source comes from data on sales of oyster mushrooms from June 2021-May to 2022. The data is analyzed using double exponential smoothing based on alpha and MAPE values. The results showed that an alpha of 0.6 with a MAPE value of 6.23% was the alpha with the smallest MAPE. This study concluded that the double exponential smoothing method could accurately predict future oyster mushroom sales.
FORECASTING OYSTER MUSHROOM SALES USING THE DOUBLE EXPONENTIAL SMOOTHING METHOD AT KUB RUMAH MUSHROOM BERSAMA Winda Wulandari; Havid Syafwan; Muhammad Ihsan
Jurnal Riset Informatika Vol. 4 No. 4 (2022): September 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (912.963 KB) | DOI: 10.34288/jri.v4i4.191

Abstract

The amount of oyster mushroom production is often not by consumer orders due to a lack of attention to the mushroom stock in the Mushroom House KUB. The purpose of this study is to apply double exponential smoothing (DES) to predict future sales of oyster mushrooms so that consumer needs are met. This research method uses quantitative methods. The data source comes from data on sales of oyster mushrooms from June 2021-May to 2022. The data is analyzed using double exponential smoothing based on alpha and MAPE values. The results showed that an alpha of 0.6 with a MAPE value of 6.23% was the alpha with the smallest MAPE. This study concluded that the double exponential smoothing method could accurately predict future oyster mushroom sales.
Co-Authors Havid Syafwan Muhammad Ihsan