Trade-off Akurasi dan Efisiensi Deep Learning versus Machine Learning Tradisional untuk SSVEP: Systematic Review

Gunakan draf abstrak yang sudah ada agar konsisten. Gunakan teks ini: "This dataset and supplementary material support the systematic review titled 'Trade-off Akurasi dan Efisiensi Deep Learning versus Machine Learning Tradisional untuk SSVEP: Systematic Review'. The archive contains: Extracted data from 71 empirical studies (2021-2026) regarding SSVEP classification. Qualitative analysis using the TEMA framework. PRISMA 2020 flow diagram and risk-of-bias assessment using CUSTOM_RUBRIC. This repository aims to provide transparency and reproducibility for the findings concerning the performance trade-offs between deep learning and traditional machine learning methods in SSVEP-BCI applications."