Prediksi Volume Impor Beras Nasional dengan Metode Multi-Factors High-Order Fuzzy Time Series - Nendiana Putri; Edy Santoso; Sigit Adinugroho (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2017)
A good self-sufficient of rice support is needed to save some foreign exchange reserves that used to import rice. An accurate rice import volume prediction is needed to make a strategic plans for keeping management of rice support stability. Fuzzy time series is one of prediction methods which use past data pattern to projects data in the future. There are some fuzzy time series method's models, one of those models is multi-factors high-order time series model. This method distributes data into several subintervals with different length, depending on centroids that came from clustering process with fuzzy C-Means method. Advantage from using multi-factors high-order time series model is this model uses more than one order and antecedent factor to build a fuzzy logic relationship. Antecedent factors that used in this case are rice productions and consumption factors that affect Indonesia's rice import volume. Minimum value of Normalised Root Mean Squared Error (NRMSE) obtained 0.298 in this study. NRMSE value which is almost zero shows that multi-factors high-order fuzzy time series method is a good method for rice import volume prediction.