基于CV分解法的阿拉比卡咖啡出口需求预测模型加约咖啡

S. Akmal, M. Sayuti, Muhariani Hasibuan
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引用次数: 1

摘要

咖啡是一种在特定月份有收获季节的植物,而即使不是在咖啡季节,咖啡的出口需求量也总是存在的。以至于公司经常无法满足咖啡出口的需求。本研究旨在了解如何使用分解方法预测阿拉比卡咖啡的出口需求,并找出预测需求所获得的结果。本研究采用定量方法,这是在CV进行的。Oro Kopi Gayo位于加约高地,正好在亚齐中部贝贝森区蒙加尔村。本研究使用的数据为二手数据,即2017年至2021年阿拉比卡咖啡出口需求数据。使用分解法预测2022年咖啡出口需求的结果为1754216公斤,与2021年的需求(153.6万公斤)相比增加了14%。1月份咖啡出口需求为160192公斤,2月份为172445公斤,3月份为146829公斤,4月份为76822公斤,5月份为88583公斤,6月份为106127公斤,7月份为129510公斤,8月份为45472公斤,9月份为45472公斤,269457公斤,10月份为225509公斤,11月份为239090公斤,12月份为94090公斤。阿拉比卡咖啡出口的最高需求出现在9月,达269457公斤,11月为239090公斤,10月为225509公斤。12月份又减少了94090公斤。重复数据模式的增减表明数据具有季节性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting Model Of Arabica Coffee Export Demand With Decomposition Method On CV. Gayo Coffee Oro
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.
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