Forecasting Palm Oil Production Using Fuzzy Time Forecasting Two-Factor Cross Associations with Frequency Density Partitions

Abstract

Economic decisions have many determining factors based on estimates of macroeconomic variables. The accuracy of decision estimates can have an important impact. Forecasting is a method to reducing uncertainty about the future, because of economic decisions have multi-factor problems, the high order fuzzy time series forecast method is more suitable than the first order fuzzy time series forecast. Predictions are made for main factors by taking influence from both factors. FLR reflects the relationship between the premise and consequence. In this paper will be discussed fuzzy time series forecasting multi-factor one order cross association based on frequency density partition as a forecasting method to forecast palm oil production with influenced by large of the area. The results of the estimates show that the proposed method has a high forecast performance, with AFER value is according to the AFER criteria table 10%, it can be concluded that the forecast has very good criteria