Pembuatan Aplikasi Perdagangan Valas Dengan Metode Elman Neural Network

Sabil Yudifera Daeng Pattah, Leo Willyanto Santoso, Murtiyanto Santoso

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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References


Seputarforex. 2010. Apa Itu Metatrader. Diakses

tanggal 20 Agustus 2016, dari http://www.seputar

forex.com/belajar/metatrader.

Indrayana, C. H. 2016. Pengenalan Dokumen Jawa

Menggunakan Jaringan Syaraf Tiruan Feedforward

Elam Type Algorithm. Diakses tanggal 18 Desember

, dari http://studentjournal.petra.ac.id/index.php/

teknik-informatika/article/view/4072/3727.

MQL4 Reference. Trade Functions. Diakses tanggal 20

Agustus 2016, dari http://docs.mql4.com/trading.

MQL4 Reference. Technical Indicator Functions.

Diakses tanggal 20 Agustus 2016, dari

http://docs.mql4.com/indicators.

MQL4 Reference. The predefined Variables. Diakses

tanggal 20 Agustus 2016, dari http://docs.mql4.com/

predefined.

Harianto, R. 2010. Perancangan dan pembuatan

aplikasi untuk mengenali tanda tangan dengan metode

backpropagation. Diakses tanggal 20 Agustus 2016,

dari http://dewey.petra.ac.id/catalog/ft_detail.php?

knokat=19444.

Antara, P. A. 2013. Model Jaringan Syaraf Tiruan

Backpropagation Dengan Input Berdasarkan Model

Regresi Terbaik. Diakses tanggal 20 Agustus 2016, dari

http://statistik.studentjournal.ub.ac.id/index.php/statisti

k/article/view/3.

Purnamasidhi, W. 2013. Pemodelan jaringan syaraf

tiruan dengan peubah input model arch pada data

return saham untu peramalan volatilitas. Diakses

tanggal 20 Agustus 2016, dari http://statistik.

studentjournal.ub.ac.id/index.php/statistik/article/view/

Harsono, T. I. 2011. Analisis dan implementasi elman

recurrent neural network dan tabu search pada

prediksi harga perak. Diakses tanggal 18 Desember

, dari https://openlibrary.telkomuniversity.ac.id/

pustaka/files/95344/resume/analisis-dan-implementasielman-

recurrent-neural-network-dan-tabu-search-padaprediksi-

harga-perak.pdf.

Hilal, M. Pengertian Drawdown. Diakses tanggal 26

Agustus 2016, dari http://www.forexpoin.com/2014/04/

pengertian-drawdown.html.


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