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Perbandingan Metode Prediksi untuk Nilai Jual USD: Holt-Winters, Holt's, dan Single Exponential Smoothing Yesy Diah Rosita; Lady Silk Moonlight
Jurnal Teknologi Informasi dan Multimedia Vol. 5 No. 4 (2024): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i4.473

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.
Co-Authors Achmad Setiyo Prabowo Ade Akbar Mukhlisin Ahmad Musadek Aizatul Mufidah Aldy Wahyu Saputra Annisarahma Parameswari Anwar Kholil Ariyono Setiawan Arnaz Olieve Arnaz Olieve Aura Putri Ahmadiyah Bambang Bagus Harianto Bambang Riyanto Trilaksono Bambang Wasito Bambang Wasito Bayu Dwi Cahyo Cindy Berliana Damar Istri Pratiwi Deny Pratama Dewi Ratna Sari Didi Hariyanto Dido Dirgantara Dewangga Diky Chandra Hermawan Dimas Bagus Christian Dinda Sri Wahyuni Dio Fadli Arwan Dwiko Nugroho Sadewo Dwiky Rizqi Firmansyah Fariz Ahmad Nurudin Fatmawati Fiqqih Faizah Fiqqih Faizah Haris Ihsanul Fadhlurrohman Haryo Penang Setyo Boma Henslok Mateus Arcanjo Nalvamaris Ilham Rizky Aries Djianto Irfansyah, Ade iswahyudi, Prasetyo Ivan Zulkifly Laurenta Pradana Kusno Kusno Kusno Kustori Lusiana Dewi Kusumayati Matius Wahyu Susanta Maulana Anifa Silvia Mimbar Maulana Ishaq Moch Muharrom Ricky Maulana1 Moch. Noval Ardiansyah Mubarak Mubarak Mubarak Muh. Firsya Ali Akbar Najwa Artania Istiqomah Sutikno Naufal Yusuf Prasaja Nyaris Pambudiyatno Panji Dwi Saputro Pawitra Enhar Sahisnu Ramining Puspitaningsih Retno Purwanig Tiyas Revayanto Eka Primadi Rinda Festyana Putri Riyanta, Wawan Rochmawati, Laila Shandy Bayu Erlangga Shendy Artileriawan Sintya Safitri Slamet Hariyadi Sugiarto, Sugiarto Suhanto Suhanto Sunardi Sunardi Sunaryo Suwito Teguh Arifianto Teguh Imam Suharto Tiziano Jose Paulo Dos Santos Pinto Vicky Rendra Purwanto Widyarini, Resty Wiwid Suryono Yessica Kristina Damayanti Yesy Diah Rosita Yuyun Suprapto