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

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 of reducing uncertainty about thefuture because economic decisions have multi-factor problems, the high order fuzzy time series forecast method is more suitable to overcome these problems. Predictions are made for main factors by taking influence from both factors. Fuzzy Logic Relationships (FLR) reflect the relationship between the premise and consequence. 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 influenced by large the area. The results of the estimates show that the proposed method has a high forecast performance, with an AFER value is 1.128%according to the AFER criteria table 1.128%<10%, it can be concluded that the forecast has very good criteria.