APPLICATION OF ARTIFICIAL NEURAL NETWORKS FOR STOCK PRICE PREDICTION

MAULANA, AKBAR (2024) APPLICATION OF ARTIFICIAL NEURAL NETWORKS FOR STOCK PRICE PREDICTION. Tugas Akhir thesis, Informatics.

[img] Text
5200411304_Akbar Maulana_Abstrak.pdf

Download (139kB)

Abstract

ABSTRACT This research is based on a problem, namely that it is difficult to predict stock prices, especially for beginners. Share prices are difficult to predict because share prices fluctuate. By using artificial neural networks, it will be easier for users to predict stock prices. The artificial neural network method used is Multilayer Perceptron. Multilayer Perceptron (MLP) is a variant of artificial neural networks and is a development of the perceptron. The choice of the Multilayer Perceptron method is based on MLP's ability to solve various problems, both classification and regression. The research carried out by the author is a regression problem because MLPs are 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 0.043 and the RMSE value is close to 0 Keywords: Machine Learning, Stock Price Prediction, Artificial Neural Network, Multilayer Perceptron, MLP.

Item Type: Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir)
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User: Kaprodi S1 Informatika UTY
Date Deposited: 09 Aug 2024 08:45
Last Modified: 09 Aug 2024 08:45
URI: http://eprints.uty.ac.id/id/eprint/15969

Actions (login required)

View Item View Item