Jurnal SINTA 2
Prediksi Nilai Tukar Rupiah Terhadap US Dollar Menggunakan Metode Genetic Programming
Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 3 No. 4 (2016) · pp. 285–291
- ISSN
- 2528-6579, 2355-7699
- Published
- 2016-12-26
- Publisher
- Fakultas Ilmu Komputer, Universitas Brawijaya
- Language
- en
Abstract
AbstrakNilai tukar mata uang mempunyai pengaruh yang sangat luas dalam perekonomian suatu negara, baik dalam negeri ataupun internasional. Pentingnya mengetahui pola nilai tukar IDR terhadap USD bisa membantu pertumbuhan ekonomi dikarenakan perdagangan luar negeri menggunakan mata uang negara yang berbeda. Maka dari itu, diperlukan suatu aplikasi yang dapat memprediksi nilai tukar Rupiah terhadap US Dollar di masa yang akan datang. Pada penelitian ini penulis menggunakan metode genetic programming(GP), yang dapat menghasilkan solusi (chromosome) optimum, yang didapat dari evaluasi nilai tukar yang lalu, sehingga solusi ini digunakan sebagai pendekatan atau prediksi terhadap kurs nilai tukar mata uang Rupiah di masa yang akan datang. Solusi ini dibentuk dari kombinasi dari himpunan terminal (set of terminals) dan himpunan fungsi (set of function) yang dibangkitkan secara random. Setelah dilakukan pengujian dengan jumlah popsize dan iterasi yang berbeda, didapatkan bahwa Algoritma GP dapat melakukan prediksi nilai tukar Rupiah terhadap mata uang US Dollar dengan sangat baik, dilihat dari nilai Mean Absolute Percentage Error (MAPE) yang dihasilkan sebesar 0,08%. Penelitian ini bisa dikembangkan lebih baik dengan menambahkan parameter terminal dan parameter operasi sehingga bisa menambah variasi hasil perhitungannya.Kata kunci: prediksi, nilai tukar mata uang, genetic programming, MAPE. AbstractExchange currency rate has a wide influence in the economy of a country, both domestically or internationally. The importance of knowing the pattern of exchange rate against the IDR to USD could help the economic growth due to foreign trade involves the use of currencies of different countries. Therefore, we need an application that can predict the value of IDR against the USD in the future. In this research, the authors use genetic programming (GP) method which produces solutions (chromosome) that obtained from the evaluation of exchange rate and then this solution used as an approximation or prediction of currency exchange rate in the future. These solutions formed from the combination of the set terminal and the set of function that generated randomly. After testing by the number popsize and different iterations, it was found that the GP algorithm can predict the value of the rupiah against the US Dollar with a very good, judging from the value of Mean Absolute Percentage Error (MAPE) generated by 0.08%. This research can be developed even better by adding terminal parameters and operating parameters so they can add variation calculation results.Keywords: prediction, exchange currency rate, genetic programming, MAPE.
Collaboration network of the authors
40 authors · 115 co-authorship links · 3 across different organisations · showing the 40 most connected
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- University of Brawijaya
- Universitas Amikom Purwokerto
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Dhimas Anjar Prabowo | University of Brawijaya | 5 |
| Muhammad Fhadli | University of Brawijaya | 4 |
| Arief Andy Soebroto | University of Brawijaya | 3 |
| Aryeswara Sunaryo | University of Brawijaya | 3 |
| Sutrisno . | Affiliation unknown | 2 |
| Nurul Hidayat | University of Brawijaya | 2 |
| Canny Amerilyse Caesar | University of Brawijaya | 2 |
| Latifah Hanum | University of Brawijaya | 2 |
| Listiya Surtiningsih | University of Brawijaya | 2 |
| Fitra Abdurrachman Bachtiar | University of Brawijaya | 2 |
| Candra Dewi | University of Brawijaya | 2 |
| Lailil Muflikhah | University of Brawijaya | 2 |
| Muhammad Syafiq | University of Brawijaya | 2 |
| Achmad Jafar Al Kadafi | University of Brawijaya | 2 |
| Rizka Husnun Zakiyyah | University of Brawijaya | 2 |
| Wanda Athira Luqyana | University of Brawijaya | 2 |
| Ahmad Afif Supianto | University of Brawijaya | 1 |
| Randy Cahya Wihandika | University of Brawijaya | 1 |
| Maria Tenika Frestantiya | University of Brawijaya | 1 |
| Ziya El Arief | University of Brawijaya | 1 |
| Rina Christanti | University of Brawijaya | 1 |
| Alfian Himawan | University of Brawijaya | 1 |
| Budi Darma Setiawan | University of Brawijaya | 1 |
| Rekyan Regasari Mardi Putri | University of Brawijaya | 1 |
| Uswatun Hasanah | Universitas Amikom Purwokerto | 1 |
| Lintang Resita Mayangsari | University of Brawijaya | 1 |
| Andhica Pratama | University of Brawijaya | 1 |
| Mochammad Ainun Najib | University of Brawijaya | 1 |
| Handika Agus Fauzi | University of Brawijaya | 1 |
| Sutrisno Sutrisno | University of Brawijaya | 1 |
| Maryamah . | University of Brawijaya | 1 |
| Moh. Fadel Asikin | University of Brawijaya | 1 |
| Daisy Kurniawaty | University of Brawijaya | 1 |
| Selly Kurnia Sari | University of Brawijaya | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.