Prediction of stock price using artificial neural network: a case of Indonesia

By: Yohanes Budiman and Togar Alam Napitupulu

ABSTRACT: Artificial Neural Network (ANN) has been widely used
in many application because of its ability to solve non-parametric
problems. ANN is also recognized as a good and widely used tool
in forecasting stock prices. Traditionally stock forecasting in
Indonesia usually used time series analysis. This paper compared
the stock forecasting result of ANTM (PT Aneka Tambang)
using ANN and that of Autoregressive Integrated Moving
Average (ARIMA). The results of the study showed that
forecasting using ANN method has smaller error than ARIMA