PREDICTION OF STOCK PRICE USING ARTIFICIAL NEURAL NETWORK: A CASE OF INDONESIA

By: 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 method.
been developed for different hybrid power system configurations for tuning the proportional-integral
controller for SVC. Transient responses of different autonomous configurations show that SVC controller
with its gained tuned by the ANNs provide optimum system performance for a variety of loads