A MODEL SELECTION FOR PRICE FORCASTING OF CRUDE PALM OIL AND FRESH FRUIT BUNCH PRICE FORECASTING

Abstract

This study was aimed to determining a fitted forecasting method for the forecasting of crude palm oil prices at international and domestic market as well as fresh fruit bunch prices at collecting merchant and farmer level in Bengkulu Province market by considering three models, namely, double exponential smoothing, autoregressive integrated moving average, and classical decomposition.  The data used were monthly data of crude palm oil prices at domestic and world markets from January 2012 – October 2016 and January 2012 – April 2017, while the fresh fruit bunch data at collecting merchant and farmers in Bengkulu Province were also monthly data from 2007 – 2014.  The result showedthat the most accurate method was ARIMA for all prices at all market levels.  This decision was based on all criteria used to determine the best model including MAPE, MAD, and MSD.