Open AccessSISTEM DETEKSI EMOSI MENGGUNAKAN SINYAL EEG “EMOCLASS”
Author(s) -
Ngarap Imanuel Manik,
Antonius Ivan
Publication year - 2020
Publication title -
jurnal algoritma, logika dan komputasi
Language(s) - English
Resource type - Journals
eISSN - 2621-9840
pISSN - 2620-620X
DOI - 10.30813/j-alu.v3i1.2154
Subject(s) - support vector machine , electroencephalography , artificial intelligence , computer science , emotion detection , psychology , speech recognition , statistical learning , machine learning , pattern recognition (psychology) , emotion recognition , psychiatry
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.