Time Series Analysis to Predicting Demand of Roasted Coffee Production

Agatha Rinta Suhardi, Shendy Amalia, Shinta Oktafien, Siska Ayudia Adiyanti, Siti Komariah and Titto Rohendra

International Journal of Financial Research, 2019, vol. 11, issue 5, 26-31

Abstract: Consumer demand conditions for fluctuating roasted coffee and ineffective production planning often lead to excessive production. Excess production will lead to wasteful costs and maintenance of quality on roasted coffee. Production demand forecasting is the basis for making production demand decisions. The purpose of this study is to predict the number of production requests for the next period and determine the most suitable forecasting method in determining the amount of roasted coffee production demand. The object of the data taken is roasted coffee. Analysis methods use moving averages, weighted moving averages, and exponential smoothing. In determining the most suitable forecasting method based on the Mean Absolute Deviation (MAD) forecasting value and the smallest Mean Squared Error (MSE) of each method used. The results of this study indicate that the most suitable forecasting method is using a Weighted Moving Average with a three-month period and forecasting roasted coffee production for November 2016 of 38.3 kg.

Keywords: moving average; weighted moving average; exponential smoothing; forecasting error (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:jfr:ijfr11:v:10:y:2019:i:5:p:26-31

DOI: 10.5430/ijfr.v10n5p26

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