SISTEM DETEKSI EMOSI MENGGUNAKAN SINYAL EEG “EMOCLASS”

Manik, Ngarap Imanuel (Mathematics Departement SoCS Binus University)
Ivan, Antonius (Mathematics Departement SoCS Binus University)

Jurnal Algoritma, Logika dan Komputasi
Vol 3, No 1 (2020): Jurnal ALU, Maret 2020

An emotional detection system has been developed using EEG signals with the help of a computer program. The results of this development are an important step in progress in learning the classification of emotional detection because it can be obtained more quickly. This study uses a support vector machine approach with a statistical analysis model that can be used to classify emotions into the Russell Emotion Model. Emotions included are Amused, Fear, Calm, Sad, and Neutral. With some assumptions, this system can provide benefits to the multimedia sector by producing applications that automatically detect human emotional experiences.