Prediksi Tren Kurs Dollar Dari Berita Finansial Amerika Serikat Berbahasa Indonesia Menggunakan Support Vector Machine - Ade Kurniawan; Putra Pandu Adikara; Yuita Arum Sari (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
United States Dollar (USD) is the most used currency for international transaction, its daily circulation is bigger than the other currency in the world. America's financial data not only give an impact in America itself but also directly effecting the other country. The main focus of this research is to predict USD's trend from America's Financial News in Bahasa Indonesia Using Support Vector Machine Algorithm. Kernel that used in this research is polynomial degree d, the best data ratio is 80% for training data and 20% for testing data. The output generated into 2 class to weaken USD price (Down) and on the other hand to strengthen USD price (Up) to rival's currency. The best parameter combination that give best average accuracy are using under DF threshold = 15%, upper DF threshold = 85%, Î»=0.1, CLR=0.01, C=1, epsilon=0.00001, maximum iteration=100 and generated average accuracy=76.66%, sensitivity=80% and specificity=73.33%.