Stock Price Prediction: Comparison of Arima and Artificial Neural Network Methods - An Indonesia Stock's Case

摘要

Neural Network is a network that resembles a human brain tissue, which may infer a result based on the facts or experience that happened. Many applications have implemented neural network. In this thesis, we compared the stock forecasting result of ANTM (PT Aneka Tam bang) using Artificial Neural Network and ARIMA. ARIMA is a technique of time-series forecasting, which means forecast based on the existing pattern. The results of the study showed that forecasting using Artificial Neural Network method has higher accuracy value than the results with ARIMA method.