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PREDIKSI HARGA SAHAM MENGGUNAKAN JARINGAN SYARAF TIRUAN BACKPROPAGATION

Unisda Journal of Mathematics and Computer Science (UJMC)

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Field Value
 
ISSN 2579-907X
2460-3333
 
Authentication Code dc
 
Title Statement PREDIKSI HARGA SAHAM MENGGUNAKAN JARINGAN SYARAF TIRUAN BACKPROPAGATION
 
Personal Name Amiroch, Siti
Universitas Islam Darul 'Ulum Lamongan
 
Summary, etc. 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.
 
Publication, Distribution, Etc. Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan
 
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http://e-jurnal.unisda.ac.id/index.php/ujmc/article/view/439
 
Data Source Entry Unisda Journal of Mathematics and Computer Science (UJMC); Vol 1 No 01 (2015): Unisda Journal of Mathematics and Computer Science
 
Language Note eng
 
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