Jaringan Syaraf Tiruan dalam Memprediksi Penjualan Air Minum dalam Kemasan dengan Metode Backpropogation

Abstract

This study predicts the sale of bottled water by applying Artificial Neural Networks. The application uses the Backpropogation Algorithm where the data entered is the number of sales, then Artificial Neural Networks are formed by determining the number of each layer. After the network is formed training is carried out from the data that has been grouped. Experiments are carried out with a network architecture consisting of input units, hidden units, output units and network architecture. Testing is done with Matlab software. Predictions with the best accuracy use 3-10-1 architecture with an accuracy rate of 75% and the lowest level of accuracy using architecture 3-40-1 with an accuracy rate of 33%.