Implementasi Model Gabungan Analisis Komponen Independen Dan Jaringan Saraf Tiruan Untuk Memperkirakan Variasi Nilai Tukar Mata Uang

Budhi, Wildan Ghiffarie (2021) Implementasi Model Gabungan Analisis Komponen Independen Dan Jaringan Saraf Tiruan Untuk Memperkirakan Variasi Nilai Tukar Mata Uang. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pasar mata uang merupakan salah satu pasar yang sangat efisien dan cepat, sehingga sangat susah untuk memperkirakan harganya di masa depan. Mata uang merupakan salah satu instrumen dalam dunia finansial yang digunakan sebagai instrumen investasi. Sehingga sangatlah penting bagi investor mata uang untuk mengetahui nilai tukar masa depan suatu mata uang. Dalam kegiatan ekspor dan impor diperlukan mata uang suatu negara di mana pemilik atau pembeli barang berlokasi, membuat pelaku ekspor dan impor perlu membeli mata uang tersebut sebelum melakukan transaksi. Sehingga sangatlah penting untuk mengetahui nilai tukar masa depan suatu mata uang sebagai landasan waktu membeli atau menjual mata uang tersebut agar tidak rugi.
Dalam tugas akhir ini, penerapan model gabungan digunakan untuk memperkirakan Variasi Nilai Tukar suatu Mata Uang (Exchange Rate Variation). Model gabungan menggunakan Analisis Komponen Independen (Independent Component Analysis) untuk mendekonstruksi variasi nilai tukar suatu mata uang menjadi komponen independen dan menggunakan Jaringan Saraf Tiruan (Artificial Neural Network) untuk memperkirakan setiap komponen independen.
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The currency market is one of the most efficient and volatile markets, making it very difficult to forecast future prices. Currency is one of the instruments in the financial world that used as an investment instrument. So it is very important for currency investor to know the future currency exchange rates.Export and import activities require the currency of a country where the owner or the buyer of the goods is located, which make exporters and importers need to buy the currency before a transaction can be made. Thus, it is very important to know the future currency exchange rates as a basis for buying or selling the currency to prevent the loss.
In this thesis, the implementation of a joint model has been used to forecast the variation of currency exchange rates. This model uses the independent component analysis to deconstruct the variation of currency exchange rates into independent components and uses artificial neural networks to forecast each independent component.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	artificial neural network, currency exchange rate, export and import, forecasting, independent component anlysis, investment
Subjects:	H Social Sciences > HA Statistics > HA30.3 Time-series analysis Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry) Q Science > QA Mathematics > QA336 Artificial Intelligence Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science)
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Computer Engineering > 90243-(S1) Undergraduate Thesis
Depositing User:	Wildan Ghiffarie Budhi
Date Deposited:	04 Aug 2021 22:22
Last Modified:	04 Aug 2021 22:22
URI:	http://repository.its.ac.id/id/eprint/84838

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