Perbandingan Metode Prediksi untuk Nilai Jual USD: Holt-Winters, Holt's, dan Single Exponential Smoothing

Yesy Diah Rosita; Lady Silk Moonlight

doi:10.35746/jtim.v5i4.473

Yesy Diah Rosita Institut Teknologi Telkom Purwokerto
Lady Silk Moonlight Politeknik Penerbangan Surabaya

DOI: https://doi.org/10.35746/jtim.v5i4.473

Keywords: data, evaluation, splitting, prediction, comparison

Abstract

In the ever-changing landscape of the global economy, the role of the United States Dollar (USD) as the backbone of the international financial system significantly influences market stability and dynamics. The close correlation between fluctuations in the USD exchange rate and internal and external factors demands effective prediction methods to understand and manage associated risks. This study aims to compare the performance of three main prediction methods: Single Exponential Smoothing (SES), Holt's Method, and Holt-Winters Method, in forecasting USD exchange rates. Utilizing historical data from the Central Statistics Agency (BPS) and testing under three training data distribution scenarios (45%, 55%, and 75%), this research provides in-depth findings on the strengths and weaknesses of each prediction method. Performance evaluations include the time required, Mean Absolute Error (MAE), Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), R-Squared, and correlation for the implementation of each method. If averaged, the results are as follows for SES, Holt’s, and Holt’s Winter, respectively: SES (1.58; 284.20; 68,768.26; 440.07; 0.03; -2.12; Nan), Holt’s (1.39; 890.23; 426,377.44; 1,043.28; 0.06; -24.28; -0.66), and Holt’s Winter (1.20; 997.45; 513,657.58; 1,168.00; 0.07; -30.62; -1.55). Overall, this indicates that the Holt-Winters Method stands out with significant performance, especially in scenarios with larger training data distributions, with a low R-Squared value (-4.618) and satisfactory correlation (0.417). Holt's Method also shows improved accuracy, while Single Exponential Smoothing (SES) offers time efficiency, albeit with limitations in explaining data variations. In conclusion, this research provides valuable guidance for business stakeholders, investors, and policymakers in selecting prediction methods suitable for their data characteristics and analysis goals, with the potential for a positive impact on business strategies, competitiveness, and risk management amid the uncertainty of USD exchange rate fluctuations.

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References

W. Khamidah and R. Sugiharti, “Faktor yang Mempengaruhi Nilai Tukar Rupiah terhadap Dollar Amerika, Euro dan Poundsterling,” Ecoplan, vol. 5, no. 1, 2022, doi: 10.20527/ecoplan.v5i1.425

D. Efriyenty, “Pengaruh Inflasi dan Kurs terhadap Harga Saham di Industri Dasar dan Kimia,” Going Concern : Jurnal Riset Akuntansi, vol. 15, no. 4, pp. 570–576, 2020, doi: 10.32400/gc.15.4.31601.2020

A. A. Istri, S. Larasati, M. Kembar, and S. Budhi, “Pengaruh Inflasi dan Kurs Dollars AS terhadap Nilai Ekspor Alas Kaki Indonesia ke China,” E-Jurnal EP Unud, vol. 7, no. 11, pp. 2430–2460, 2017.

R. P. Nugraheni, E. Rimawati, and R. T. Vulandari, “Penerapan Metode Exponential Smoothing Winters Pada Prediksi Harga Beras,” Jurnal Ilmiah SINUS, vol. 20, no. 2, p. 45, Jul. 2022, doi: 10.30646/sinus.v20i2.608.

O. D. Rahayu, W. Ramdhan, and S. Sumatri, “Implementasi Metode Single Exponential Smoothing Dalam Memprediksi Kebutuhan Pupuk Bagi Petani,” Building of Informatics, Technology and Science (BITS), vol. 4, no. 2, Sep. 2022, doi: 10.47065/bits.v4i2.2080.

Suriyanti, Satriani, A. A. Sabnur, and F. Hasrianti, “Hubungan Inflasi, Suku Bunga dan Nilai Tukar dalam Penentuan Nilai tukar Valuta Asing,” Jurnal Mirai Management, vol. 8, no. 3, pp. 245–253, 2023, doi: 10.37531/mirai.v8i3.5933

R. Utami and S. Atmojo, “Perbandingan Metode Holt Eksponential Smoothing dan Winter Eksponential Smoothing Untuk Peramalan Penjualan Souvenir,” Jurnal Ilmiah Teknologi Informasi Asia, vol. 11, no. 2, p. 123, Aug. 2017, doi: 10.32815/jitika.v11i2.191.

A. Desduana Selasakmida, T. Wuryandari, D. Statistika, and F. Sains dan Matematika, “Perbandingan Metode Double Exponential Smoothing Holt Dan Fuzzy Time Series Chen Untuk Peramalan Harga Paladium,” Jurnal Gaussian, vol. 10, no. 3, pp. 325–336, 2021, [Online]. Available: https://ejournal3.undip.ac.id/index.php/gaussian/

S. J. Amalia, N. Oktaviani, G. I. Prameswara, Y. D. Prasetyo, and M. Y. Fathoni, “Perbandingan Metode Moving Average dan Exponential Smoothing pada Peramalan Nilai Tukar Rupiah terhadap Dollar AS,” JURIKOM (Jurnal Riset Komputer), vol. 9, no. 4, p. 974, Aug. 2022, doi: 10.30865/jurikom.v9i4.4493.

A. Aryati, I. Purnamasari, and Y. N. Nasution, “Peramalan dengan Menggunakan Metode Holt-Winters Exponential Smoothing (Studi Kasus: Jumlah Wisatawan Mancanegara yang Berkunjung Ke Indonesia) Forecasting using the Method of Holt-Winters Exponential Smoothing (Case Study: Number of Foreign Tourists Visiting Indonesia),” Jurnal Eksponensial, vol. 11, no. 1, 2020.

K. Komariah, E. Kurniawan, and M. Handayani, “Penerapan Metode Single Exponential Smoothing Untuk Prediksi Penjualan Bahan Bangunan,” Building of Informatics, Technology and Science (BITS), vol. 4, no. 2, Sep. 2022, doi: 10.47065/bits.v4i2.2140.

P. Anzhelmus Boli and R. Putranda Kristianto, “Penerapan Algoritma Single Exponential Smoothing untuk Prediksi Jumlah Calon Mahasiswa Baru,” Nasional Teknologi Informasi dan Komputer), vol. 6, no. 1, 2022, doi: 10.30865/komik.v6i1.5686.

R. Rachman, S. Nusa, and M. Jakarta, “Penerapan Metode Moving Average dan Exponential Smoothing pada Peramalan Produksi Industri Garment,” Jurnal Informatika, vol. 5, no. 1, 2018, doi: 10.31294/ji.v5i2.3309

I. Hidayat Susilowati, “Peramalan Nilai Tukar Kurs IDR Terhadap Dollar USD Dengan Metode Moving Average dan Exponential Smoothing,” Perspektif: Jurnal Ekonomi & Manajemen Universitas Bina Sarana Informatika , vol. 18, no. 1, 2020, doi: 10.31294/jp.v17i2.

I. H. Susilowati and Rosento, “Peramalan Nilai Tukar Kurs IDR Terhadap Dollar USD Dengan Metode Moving Average dan Exponential Smoothing,” Perspektif: Jurnal Ekonomi & Manajemen Universitas Bina Sarana Informatika, vol. 18, no. 1, 2020.

N. H. A. S. Al Ihsan, H. H. Dzakiyah, and F. Liantoni, “Perbandingan Metode Single Exponential Smoothing dan Metode Holt untuk Prediksi Kasus COVID-19 di Indonesia,” Ultimatics : Jurnal Teknik Informatika, vol. 12, no. 2, pp. 89–94, Dec. 2020, doi: 10.31937/ti.v12i2.1689.

A. Fahlevi, F. A. Bachtiar, and B. D. Setiawan, “Perbandingan Holt’s dan Winter’s Exponential Smoothing untuk Peramalan Indeks Harga Konsumen Kelompok Transportasi, Komunikasi dan Jasa Keuangan,” 2018. [Online]. Available: http://j-ptiik.ub.ac.id