Analisis Komparatif GARCH Klasik dan Hybrid GARCH–Gaussian Process Regression pada Volatilitas Nilai Tukar USD/IDR 2010–2025
DOI:
https://doi.org/10.33830/saintek.v2i2.14375.2026Keywords:
volatilitas nilai tukar, garch, gaussian process regression, usd/idr, model hybridAbstract
Penelitian ini bertujuan untuk menganalisis akurasi peramalan volatilitas mingguan nilai tukar USD/IDR periode 2010–2025 dengan pendekatan hybrid yang mengintegrasikan model ekonometrika klasik dan machine learning. Tahap awal menggunakan ARIMA(1,0,4) untuk menangkap pola linear pada persamaan rata-rata (mean equation) dan memastikan data bebas dari autokorelasi. Selanjutnya model GARCH(1,1) untuk memodelkan varians bersyarat dari residu ARIMA yang bersifat white noise dan mengandung efek ARCH. Residu dari hasil pemodelan GARCH yang diasumsikan masih mengandung informasi yang belum terjelaskan, kemudian dimodelkan menggunakan Gaussian Process Regression (GPR) dengan fungsi kernel Matern 1,5 untuk menangkap pola hubungan non-linear. Hasil analisis pada data uji menunjukkan bahwa pendekatan hybrid mampu meningkatkan kinerja peramalan secara signifikan dibandingkan model tunggal. Model hybrid berhasil menurunkan nilai Root Mean Squared Error (RMSE) sebesar 8,83%, dari 1,1164 pada model GARCH klasik menjadi 1,0178. Penurunan juga tercatat pada Mean Absolute Error (MAE). Temuan ini menunjukkan bahwa integrasi GPR efektif dalam mengatasi keterbatasan GARCH klasik dalam menangkap dinamika volatilitas kompleks, sekaligus memberikan kontribusi praktis bagi pengelolaan risiko nilai tukar di Indonesia.
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