Analisis Perbandingan Model Algoritma Data Mining dalam Memprediksi Harga Emas terhadap Mata Uang US Dollar (XAU/USD) di Pasar Forex

Patah Herwanto; Fanji Arief Suwandy; Yudhi Widya Arthana Rustam; Rosida

doi:10.37424/informasi.v16i1.292

Patah Herwanto STMIK IM
Fanji Arief Suwandy
Yudhi Widya Arthana Rustam STMIK IM
Rosida STMIK IM

DOI: https://doi.org/10.37424/informasi.v16i1.292

Keywords: Jaringan Saraf Tiruan, Support Vector Machine, Regresi Linier, Gaussian Process, Regresi Polinomial, Validasi Silang K-Fold, Akar Mean Square Error

Abstract

Studi ini menganalisis pergerakan harga XAU/USD di pasar forex untuk memfasilitasi prediksi tren yang akurat bagi para trader. Berbagai model algoritma data mining, termasuk Jaringan Saraf Tiruan (Neural Network), Mesin Vector Pendukung (Support Vector Machine), Gaussian Process, Regresi Linier, dan Regresi Polinomial, dibandingkan untuk akurasi. RapidMiner memproses data, dan Validasi Silang K-Fold digunakan untuk menentukan akurasi model. Akar Mean Square Error (RMSE) digunakan untuk evaluasi, dengan Jaringan Saraf Tiruan menunjukkan kesalahan terendah (7,059). Pengujian mengkonfirmasi identifikasi tren yang akurat dan prediksi harga penutupan oleh Jaringan Saraf Tiruan, membantu para trader dalam transaksi yang terinformasi.

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