PERAMALAN TINGKAT INFLASI INDONESIA MENGGUNAKAN NEURAL NETWORK BACKPROPAGATION BERBASIS METODE TIME SERIES
AbstractIn this study will be used back propagation neural network method to predict the monthly inflation rate in Indonesia. In the results of the data analysis is concluded that the performance of back propagation neural network that formed by the training data and validated by testing data generates prediction accuracy rate is very good with a mean square error (MSE) is 0.0171. By using a moving average to forecast the independent variables obtained the rate of inflation in the month of July 2014 is 0.514, by using exponential smoothing to forecast the independent variables obtained by the rate of inflation in the month of July 2014 is 0.45, and by using seasonal method to forecast the independent variables obtained by the rate of inflation in the month of July 2014 is 0.93.
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