Penerapan Firefly Algorithm dalam Menentukan Hyperparameter pada Support Vector Regression untuk Memprediksi Harga Saham dengan Google Trends - Atmaja, Anugerah Surya; Wijayanto, Arie Wahyu (Politeknik Statistika STIS, 2025)
Stock fluctuations as well as the tendency to high volatility raise doubts for investors to invest in a company. Efforts that can be made to minimize investment risk are to conduct predictive analysis. The development of machine learning technology and big data can be a support in prediction, one of which is the use of the Support Vector Regression (SVR) method and google trends index data.This research forms a prediction model for PT. BRI (Persero) Tbk. which involves google trend index data using the SVR method. Referring to the constraints in determining the appropriate hyperparameters for the SVR method, the firefly algorithm is used to obtain hyperparameters that optimize the model. Based on modeling, the SVR-FA model involving the google trend index gave the best results, shown by the RMSE and MAPE were 348,47 and 4,12% respectively. This shows that by adding google trend index variables and utilizing machine learning methods in modeling,it will provide better results.