Forecasting on the crude palm oil production in Malaysia using SARIMA model

Abstract

Today, accurate prediction on the seasonal trend of the crude palm oil production is critical for the government and agriculturist management to aid in decision-making. The study aims to forecast the Malaysia crude palm oil production by using the Seasonal Autoregressive Integrated Moving Average model. The monthly data of Malaysia crude palm oil production were obtained from Malaysian Palm Oil Board, from January 2014 until September 2019. The Seasonal Autoregressive Integrated Moving Average model was applied to the data by using the Box-Jenkins approach. Based on the adequacy checking and accuracy testing, SARIMA(1,0,0)(0,1,1)12 is the best fitted model for the Malaysia crude palm oil production. As a result of the findings, the SARIMA(1,0,0)(0,1,1)12 model appears to be the best choice for decision makers to make reliable and accurate long-term forecasts on Malaysia crude palm oil production.