Forecasting Model Of Arabica Coffee Export Demand With Decomposition Method On CV. Gayo Coffee Oro

Syarifah Akmal, M Sayuti, Muhariani Hasibuan

Abstract


Coffee is one type of plant that has a harvest season in certain months, while the amount of coffee export demand is always there even though it is not in the coffee season. So that the company is often unable to meet the demand for coffee exports. This study aims to find out how the use of the decomposition method in forecasting the demand for Arabica coffee exports and also to find out the results of forecasting the demand obtained. This study uses a quantitative approach, which was conducted at CV. Oro Kopi Gayo is located in the Gayo highlands, precisely in the Mongal Village, Bebesen District, Central Aceh Regency. The data used in this study is secondary data, namely data on Arabica coffee export demand from 2017 to 2021. The results of forecasting coffee export demand using the decomposition method in 2022, which is 1754216 kg, have increased when compared to demand in 2021, which is equal to 1536000 kg with a percentage increase of 14%. Demand for coffee exports in January was 160192 kg, February was 172445 kg, March was 146829 kg, April was 76822 kg, May was 88583 kg, June was 106127 kg, July was 129510 kg, August was 45472 kg, September was 45472 kg 269457 kg, October 225509 kg, November 239090 kg, and December 94090 kg. The highest demand for Arabica coffee exports occurred in September, amounting to 269457 kg, in November at 239090 kg, and in October at 225509 kg. Then it decreased again in December, which was 94090 kg. The increase and decrease in the repetitive data pattern indicate that the data has a seasonal pattern.


Keywords


Decomposition, Arabica, Forecasting, Export

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DOI: https://doi.org/10.52088/ijesty.v2i3.282

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