Reseach Article
Artificial Neural Networks for Stock Price Prediction
| Journal of Advanced Artificial Intelligence |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 3 |
| Year of Publication: 2024 |
| Authors: Akbar Maulana, Enny Itje Sela |
10.5120/jaai202413
|
Akbar Maulana, Enny Itje Sela . Artificial Neural Networks for Stock Price Prediction. Journal of Advanced Artificial Intelligence. 1, 3 ( Dec 2024), 7-13. DOI=10.5120/jaai202413
Abstract
This research is based on a problem that is difficult to predict stock prices, especially for beginners. Stock prices are difficult to predict because stock prices are volatile. By using artificial neural networks, users will find it easier to predict stock prices. The artificial neural network method used is Multilayer Perceptron. Multilayer Perceptron (MLP) is a variant of an artificial neural network and is a development of perceptron. The selection of the Multilayer Perceptron method is based on the ability of MLP to solve various problems both classification and regression. The research conducted by the author is a regression problem because MLP is asked to predict the close price or closing price of shares after seven days. The results of the model built are able to predict stock prices and produce good accuracy because the resulting RMSE value is 0.042649862994352014 and the RMSE value is close to 0.
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