Analisis Tingkat Akurasi Algoritma Backpropagation Dalam Prediksi Produksi Ubi Kayu Di Provinsi Indonesia - Nuraysah Zamil Purba; Deviana Sitompul (STIKOM Tunas Bangsa Pematangsiantar, 2018)
Cassava is one type of food that is widely consumed by the people of Indonesia. In addition to the typical taste, cassava is often processed by the community into a cake or snacks that diverse. According to the statistical report of cassava agriculture in Indonesia from 2005-2015 experience up and down. In order to improve the cassava in Indonesia, it is necessary to make a prediction for the coming year so that the government will have a reference to immediately make the right policy to increase the production of cassava in Indonesia to prevent the increase of cassava import quantity. This study aims to determine the development of cassava production in Indonesia, in the hope that it can be used as a reference to increase the production and productivity of cassava. Data used in this research is data of cassava production in province of Indonesia year 2005-2015, algorithm used is Artificial Neural Network Backpropagation. Data analysis was done using Matlab 2011b. This research uses 5 architecture that is 5-8-1, 5-10-1, 5-15-1, 5-18-1, 5-20-1 but the best architecture is 5-18-1 with percentage accuracy 94% and MSE value of 0.007227812. This model is well used to predict cassava in the province of Indonesia.