Unisda Journal of Mathematics and Computer Science (UJMC)
Vol 1 No 01 (2015): Unisda Journal of Mathematics and Computer Science

PREDIKSI HARGA SAHAM MENGGUNAKAN JARINGAN SYARAF TIRUAN BACKPROPAGATION

Siti Amiroch (Universitas Islam Darul 'Ulum Lamongan)



Article Info

Publish Date
01 Jun 2015

Abstract

In the stock market, stock price prediction is an important issue for the perpetrators of capital transactions to help making the right decision. Most traders have their own application software to predict the stock price so that it can be decided would buy the shares or sell them. By using a neural networks, prediction of stock prices can be done by using the backpropagation algorithm. Artificial neural networks can be used either to predict the level or price of the stock index, stock movement (trend), and the return earned on stocks. This study discusses the use of techniques Backpropagation Neural Network to predict the stock price closing (Close) in AKR Tbk (AKRA Corporindo) engaged in the petroleum, chemical,logistics, manufacturing and coal are simulated in Matlab. Of some testing done, the prediction results obtained are very close to the price actually with very small MSE value.

Copyrights © 2015






Journal Info

Abbrev

ujmc

Publisher

Subject

Computer Science & IT Education Mathematics

Description

Unisda Journal of Mathematics and Computational Science (UJMC) is a research journal published by Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan with the scope of pure mathematics, applied science, education, ...