Jurnal Algoritma, Logika dan Komputasi

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.

Emotion detection, EEG, Support vector machine

. Fabian Gieseke, Antti Airola, Tapio Pahikkala, and Oliver Kramer(2015) “Sparse Quasi-Newton Optimization for Semi-Supervised Support Vector Machines”. In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods. pp 45-54.

. Fausett, L R. E. (2018). An Introduction to Artificial Intelligence: Can Computers Think?, Boyd & Fraser Publishing Company, San Francisco.

. Karl Pearson (2015) "Notes on regression and inheritance in the case of two parents, " Proceedings of the Royal Society of London, 58 : 240–242. Denmark

. M. Soleymani, J. Lichtenauer, T. Pun and M. Pantic (2011), "A Multi¬Modal Affective Database for Affect Recognition and Implicit Tagging", IEEE Transactions on Affective Computing, Special Issue: Naturalistic Affect Resources,

. R. Adolphs, D. Tranel, and A.R. Damasio,(2013) “Dissociable Neural Systems for Recognizing Emotions,” Brain and Cognition, vol. 52,no. 1, pp. 61-69

. Royce, Winston W. (2016) "Managing the development of large software systems." proceedings of IEEE WESCON. Vol. 26. No. 8.

. S. Koelstra, C. Muhl, M. Soleymani, Jong-Seok, A. Yazdani, T. Ebrahimi, T. Pun, A. Nijholt and I. Patras (2014), "DEAP: A Database for Emotion Analysis using Physiological Signals," John wiley, USA