Bank Indonesia Interest Rate Prediction and Forecast With Backpropagation Neural Network
Rini Sovia, Musli Yanto, Rima Liana Gema, Rizki Fernando · 2018
The BI Rate is a policy interest rate that plays a role in directing the movement of the national economy. The problem that arises in the study is to determine a forecast for the movement of the BI Rate. Predictions of bank interest rates can be done with various techniques and methods, one of which uses backpropagation artificial neural networks. This method is a branch of artificial intelligence that has the same process carried out by human brain tissue. The method of working method starts from analyzing the data to be used. The process starts from determining the variables namely: Dollar Exchange Rate, Amount of Money Supply, Inflation, and JCI. The process of backpropagation artificial neural network calculation is continued until the final stage of the process is to find the network output which is used as a forecasting number. The author uses Matlab Software that can determine the weight and bias values. The network architecture used is 4 input layers, 2 hidden layers, and 1 output layer and the desired target is the interest rate number.