Pembuatan Aplikasi Perdagangan Valas Dengan Metode Elman Neural Network

Sabil Yudifera Daeng Pattah(1*), Leo Willyanto Santoso(2), Murtiyanto Santoso(3),


(1) Program Studi Teknik Informatika
(2) Program Studi Teknik Informatika
(3) Program Studi Teknik Elektro
(*) Corresponding Author

Abstract


Neural Network technology is a system that functions like the
human brain. This technology is able to solve intractable
problem with mathematical calculations. In this thesis Elman
neural network is used to predict the value of foreign
currencies in order for helping the traders or investors in
making decisions.
Based on the above problems, the application is made by
utilizing some forex indicators that are often used by traders
to put on the input node in the neural network and the output
node in the form of predictions buy or sell.
From the test results it can be concluded that the selection of
appropriate training time and the greater number of the best
indicators in used can improve the success rate for predicting
currency prices.

Keywords


Prediction, Price Currency, Artificial Neural Networks, multilayer, feedforward, Elman Neural Network.

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