Neural network revisited: perception on modified Poincare map of financial time-series data

Artificial Neural Network Model for prediction of time-series data is revisited on analysis of the Indonesian stock-exchange data. We introduce the use of Multi-Layer Perceptron to percept the modified Poincare map of the given financial time-series data. The modified Poincare map is believed to become the pattern of the data that transforms the data in time-t versus the data in time-t+1 graphically. We built the Multi-Layer Perceptron to percept and demonstrate predicting of the data for specific stock-exchange in Indonesia.