PREDIKSI HARGA SAHAM MENGGUNAKAN JARINGAN SYARAF TIRUAN BACKPROPAGATION - Siti Amiroch (Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan, 2015)
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.