The objective of this study is to compare three forecasting methods on three agricultural products consisting of fresh whole chicken (include bone no entrails) red meat pork hip section and Jasmine rice. These methods are Simple Exponential Smoothing method Holt’s method and Winter’s method. Data are colleced for a period of 60 months from January 2007 to December 2011. The most suitable forecasting method are the one that shows no residual autocorrelation and gives the lowest MSE MAPE. The results show that Simple Exponential Smoothing method is the most suitable method on three agricultural products due to this method reveals no residual autocorrelation and displays the lowest MSE MAPE.

The purpose of this research was to construct the appropriate forecasting model for the export values of alcoholic beverages using three-time series analysis methods including Box-Jenkins method damped trend exponential smoothing method and combined forecasting method. Time series data from the website of Office of Agricultural Economics with total 199 months from January 1998 to July 2014 were used and divided into two series. The first 192- month data from January 1998 until December 2013 were used to build the forecasting models and the last 7-month data from January to July 2014 were used to compare the forecasting method accuracy via the criteria of the lowest mean absolute percentage error and root mean squared error. Research findings indicated that for all forecasting methods that had been studied combined forecasting method was the most accurate method and this model was when and represent the single forecasts at time t from Box-Jenkins method and damped trend exponential smoothing method respectively.

The purpose of this research was to construct an appropriate forecasting model for the export quantity of frozen and chilled chicken using three time series analysis methods including Box-Jenkins method Holt’s exponential smoothing method and damped trend exponential smoothing method. Time series data from the website of the Office of Industrial Economics with total 130 months during January 2004 to October 2014 were used and they were divided into two series. Fristly 120 months from January 2004 to December 2013 were used to build the forecasting models and lastly 10 months from January until October 2014 were used to compare the forecasting methods accuracies via the criteria of the lowest mean absolute percentage error and root mean squared error. Research findings indicated that all forecasting methods that had been studied damped trend exponential smoothing method were the most accurate method and showed the forecasting model as where m represented the number of periods to forecast ahead with the starting value was January 2014 (m = 1).

The objective of this research is to construct the appropriate forecasting model for the export quantity of concentrated latex by the three time series analysis methods which are Box-Jenkins method Winters’ multiplicative exponential smoothing method and combined forecasting method. Time series data from the website of Office of Agricultural Economics during January 1998 to February 2014 (194 values) are used and divided into two series. The first 182 values from January 1998 until February 2013 for the models prediction and the last 12 values from March 2013 until February 2014 for comparison the performance of forecasting models via the criterion of the lowest root mean squared error and the criterion of the highest correlation coefficient between existing values and forecasted values. Research findings indicated that for all forecasting methods that have been studied the most powerful method is the combined forecasting and the forecasting model is where and represent the single forecasts at time t from Box-Jenkins method and Winters’ multiplicative exponential smoothing method respectively.

The objective of this research is to design forecasting support models on demand of durian for domestic markets and export markets for durian gardeners durian entrepreneurs of domestic markets and export markets and the Office of Agricultural Economics to plan durian demand conforming with domestic markets and export markets because of Production and marketing main problems (The Agricultural Information Center The office of Agricultural Economics: 2008) such as over - much durian production during production capital increased farmers durian sold price tended to be lower and lower inefficient domestic market management and more export but cheaper price therefore after that to design forecasting for the purpose in order that durian would not be over demand which is containing factors of the demand of durian fresh durian frozen durian paste and durian chips for domestic markets and export markets exported to Asia America Australia and Africa. The research involves historical collection data in the period of 2002 to 2008. The basic of forecast models are the designed and improved models using an intelligent knowledge-based approach beginning Moving average Deseasonalized Exponential smoothing Double exponential smoothing and Artificial neural network (ANNs) program within the model of new value Creation and comparative accuracy models. The evaluation result of forecasting durian demand showed that lowest MAPE of Deseasonlized models at 3 month was durian fresh durian frozen and durian paste but durian chips showed that lowest MAPE of ANNs at 4 input 10 hidden layers and 1 output was high accurate forecasting and optimal models. The analysis recommendations and error forecast of durian demand are also presented.