Adi, Hafizh Zaki Prasetyo (2021) Peramalan Nilai Tukar Dollar Terhadap Rupiah dan Utang Luar Negeri Menggunakan Hybrid Autoregressive Intergrated Moving Average dan Radial Basis Function Neural Network. Undergraduate thesis, Institut Teknologi Sepuluh Nopember Surabaya.
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Abstract
Meramal valuta asing merupakan strategi yang sangat penting bagi suksesnya pemerintahan karena hampir sebagian besar perdagangan antara negara dipengaruhi oleh perubahan-perubahan nilai tukar. Salah satu kebijakan pemerintah di bidang ekonomi yang dipengaruhi oleh kurs dollar terhadap rupiah adalah Utang Luar Negeri. Kebijakan pengambilan ULN bertujuan untuk menutup defisit anggaran pendapatan dan belanja negara. Kurs dan ULN mempunyai 3 periode tren pada jangka waktu November 2010 sampai Januari 2021. Kurs dan ULN mempunyai pola data non linear sehingga dapat dimodelkan menggunakan model RBFNN dan hybrid ARIMA-RBFNN. Model terbaik untuk meramalkan data testing kurs dollar terhadap rupiah adalah model RBFNN dengan node 47. Model terbaik untuk meramalkan data testing utang luar negeri dalam bentuk rupiah adalah model hybrid ARIMA([46],1,0) dan RBFNN dengan node 14 Kurs dollar terhadap rupiah diprediksi turun dari 14.765 pada Bulan Agustus 2020 hingga 14.123 pada Bulan Januari 2021. Pola dan tren berbeda dimiliki oleh utang luar negeri dalam bentuk rupiah dimana utang luar negeri diprediksi naik dari 5.981.161.372 pada Bulan Agustus 2020 hingga 6.114.065.838 pada Bulan November 2020. Namun, setelah Bulan November utang luar negeri dalam bentuk rupiah diprediksi turun di angka 5.873.995.184 pada Bulan Januari 2021.
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Forecasting foreign exchange is a very important strategy for a
successful government because most of the trade between countries
is affected by changes in exchange rates. One of the government's
policies in the economic sector which is influenced by the dollar
exchange rate against the rupiah is foreign debt. The policy of
taking external debt is aimed at covering the budget deficit of state
revenues and expenditures. The exchange rate and external debt
have 3 trend periods in the period November 2010 to January
2021. The exchange rate and external debt have non-linear data
patterns so that they can be modeled using the RBFNN and
ARIMA-RBFNN hybrid models. The best model for predicting
testing data on the dollar exchange rate against the rupiah is the
RBFNN model with node 47. The best model for forecasting foreign
debt testing data in the form of rupiah is the ARIMA hybrid model
([46],1,0) and RBFNN with node 14. The rupiah is predicted to
decline from 14,765 in August 2020 to 14,123 in January 2021.
Foreign debts in the form of rupiah have different patterns and
trends where foreign debt is predicted to increase from
5,981,161,372 in August 2020 to 6,114,065,838 in November 2020
However, after November, foreign debt in the form of rupiah is
predicted to decline to 5,873,995,184 in January 2021.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | ARIMA, Dollar, RBFNN, Time Series, dan Utang Luar Negeri |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA30.3 Time-series analysis H Social Sciences > HG Finance > HG3881 Foreign exchange. Q Science |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Hafizh Zaki Prasetyo Adi |
| Date Deposited: | 13 Sep 2021 05:12 |
| Last Modified: | 13 Sep 2021 05:12 |
| URI: | http://repository.its.ac.id/id/eprint/91980 |
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