PERAMALAN NILAI TUKAR RUPIAH TERHADAP DOLLAR AMERIKA DENGAN MENGGUNAKAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA)

Gelbi Ardesfira, Hazulil Fitriah Zedha, Iin Fazana, Julia Rahmadhiyanti, Siti Rahima, Samsul Anwar

Abstract


The Rupiah exchange rate was immensely influential in maintaining the stability of the country's economy.  The weakening of the rupiah exchange rate would have an impact on the national economy. Therefore, a forecast was needed to determine the exchange rate of the Rupiah in the future, especially against the US Dollar (USD). This study aimed to predict the rupiah exchange rate against the USD in 2022 and 2023. The data employed were the rupiah exchange rate data against the USD from January 2001 to December 2021. The forecasting method utilized in this study was the Autoregressive Integrated Moving Average (ARIMA) method. The most suitable ARIMA model in forecasting the Rupiah exchange rate against USD was ARIMA (3,1,1).  Forecasting results showed the Rupiah exchange rate weakened more significantly in 2022 and 2023, reaching IDR 14,484.5 and IDR 14,704.7 per USD, respectively, with the highest forecast limit reaching IDR 16,691.6 at the end of 2022 and IDR 17,781.8 at the end of 2023. The government needed preparing special policies in an effort to maintain the stability of the rupiah exchange rate in the future.


Keywords


Arima; Exchange Rate; IDR; USD

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References


Amalutfia, S. Y. and Hafiyusholeh, M. (2020) ‘Analisis Peramalan Nilai Tukar Rupiah Terhadap Dollar dan Yuan Menggunakan FTS-Markov Chain’, Vygotsky: Jurnal Pendidikan Matematika dan Matematika, 2(2), pp. 102–113. doi: 10.30736/VJ.V2I2.258.

Anggraeni, D. P., Rosadi, D. and Rizal, A. A. (2020) ‘Prediksi Harga Emas Dunia di Masa Pandemi Covid-19 Menggunakan Model ARIMA’, Jurnal Aplikasi Statistika & Komputasi Statistik, 12(1), pp. 71–84. doi: 10.34123/JURNALASKS.V12I1.264.

Anwar, S. (2017) ‘Peramalan Suhu Udara Jangka Pendek di Kota Banda Aceh dengan Metode Autoregressive Integrated Moving Average (ARIMA)’, Malikussaleh Journal of Mechanical Science and Technology, 5(1), pp. 6–12.

Assakhiy, R., Anwar, S. and A.R. Fitriana (2019) ‘Peramalan Realisasi Penerimaan Zakat Pada Baitulmal Aceh Dengan Mempertimbangkan Efek Dari Variasi Kalender’, Jurnal Ekonomi dan Pembangunan, 27(2), pp. 27–45. doi: 10.14203/JEP.27.2.2019.27-45.

Cîrnu, M. I. (2012) ‘Newton-Raphson Type Methods’, International Journal of Open Problems in Computer Science and Mathematics, 5(2), pp. 95–104. doi: 10.12816/0006108.

Fitria, V. and Anwar, S. (2020) ‘Penerapan Triple Exponential Smoothing dalam Meramalkan Laju Inflasi Bulanan Provinsi Aceh Tahun 2019 - 2020’, E-Jurnal Ekonomi dan Bisnis Universitas Udayana, 9(1), pp. 23–38. doi: 10.24843/eeb.2020.v09.i01.p02.

Hartati, H. (2017) ‘Penggunaan Metode Arima dalam Meramal Pergerakan Inflasi’, Jurnal Matematika Sains dan Teknologi, 18(1), pp. 1–10. doi: 10.33830/JMST.V18I1.163.2017.

Hidayah, D. Y. and Sugiman, S. (2021) ‘Peramalan Nilai Tukar Rupiah terhadap Dollar Amerika dengan Metode Fuzzy Time Series (FTS) Markov Chain’, Unnes Journal of Mathematics, 10(2), pp. 85-95. doi: 10.15294/UJM.V10I2.53056.

Iswardani, P. R., Sudarma, M. and Jasa, L. (2021) ‘Peramalan Nilai Tukar Rupiah Terhadap Mata Uang Negara Asia Menggunakan Metode Quantum Neural Network’, Majalah Ilmiah Teknologi Elektro, 20(1), pp. 153–160. doi: 10.24843/MITE.2021.V20I01.P18.

Johnson, R. A. and Bhattacharyya, G. K. (2001) Statistics : Principles and Methods. New Jersey: John Wiley & Sons.

Kemendag RI (2021) Nilai Tukar Mata Uang Asing Terhadap Rupiah. Available at: https://satudata.kemendag.go.id/data-informasi/perdagangan-dalam-negeri/nilai-tukar (Accessed: 2 October 2022).

Krispin, R. (2019) Hands-On Time Series Analysis with R : Perform Time Series Analysis and Forecasting Using R. Birmingham: Packt Publishing.

Laily, I. N. (2022) ‘Memahami Devaluasi, Pengertian dan Sejarah Penerapannya di Indonesia’, katadata.co.id, 6 April. Available at: https://katadata.co.id/agung/berita/624d626d1ef80/memahami-devaluasi-pengertian-dan-sejarah-penerapannya-di-indonesia (Accessed: 2 October 2022).

Mubarok, D. N. and Wachidah, L. (2021) ‘Analisis Data Deret Waktu pada Nilai Tukar Rupiah Tahun 2021 Menggunakan Metode Wavelet Thresholding’, in Prosiding Statistika. Bandung: Universitas Islam Bandung, pp. 426–432. doi: 10.29313/.V0I0.28706.

Pamungkas, M. B. and Wibowo, A. (2018) ‘Aplikasi Metode Arima Box-Jenkins Untuk Meramalkan Kasus DBD di Provinsi Jawa Timur’, The Indonesian Journal of Public Health, 13(2), pp. 181–194. doi: 10.20473/ijph.vl13il.2018.181-194.

Rusyida, W. Y. and Pratama, V. Y. (2020) ‘Prediksi Harga Saham Garuda Indonesia di Tengah Pandemi Covid-19 Menggunakan Metode ARIMA’, Square : Journal of Mathematics and Mathematics Education, 2(1), pp. 73-81. doi: 10.21580/square.2020.2.1.5626.

Salwa, N. et al. (2018) ‘Peramalan Harga Bitcoin Menggunakan Metode ARIMA (Autoregressive Integrated Moving Average)’, Journal of Data Analysis, 1(1), pp. 21–31. doi: 10.24815/jda.v1i1.11874.

Shumway, R. H. and Stoffer, D. S. (2011) Time Series Analysis and Its Applications With R Examples. Third edit, Revista do Hospital das Clínicas. Third edit. New York: Springer Science and Business Media LLC.

Susilowati, I. H. and Rosento, R. (2020) ‘Peramalan Nilai Tukar Kurs IDR Terhadap Dollar USD Dengan Metode Moving Average dan Exponential Smoothing’, Perspektif: Jurnal Ekonomi & Manajemen Universitas Bina Sarana Informatika, 18(1), pp. 91–98. doi: 10.31294/jp.v17i2.

Utari, D. T. (2018) ‘Forecasting The Exchange Rate (IDR) of US Dollar (USD) Using Locally Stationary Wavelet’, EKSAKTA: Journal of Sciences and Data Analysis, 18(2), p. 146. doi: 10.20885/EKSAKTA.VOL18.ISS2.ART6.




DOI: https://doi.org/10.34312/jjps.v3i2.15469

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