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All Journal Perfecting a Video Game with Game Metrics ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Jurnal Ilmiah Mahasiswa Pendidikan Kimia Informatika Mulawarman Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Nasional Teknik Elektro dan Teknologi Informasi J-Innovation Chimica Didactica Acta : Journal of Chemistry and Chemistry Education Jurnal Rekayasa elektrika Jurnal INFOTEL
Syahrial, Syahrial
Universitas Syiah Kuala
Chemistry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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Journal : Jurnal INFOTEL

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Decision tree method to classify the electroencephalography-based emotion data Teuku Muhammad Mirza Keumala; Melinda Melinda; Syahrial Syahrial
JURNAL INFOTEL Vol 14 No 1 (2022): February 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v14i1.750

Abstract

Electroencephalography (EEG) data contains recordings of brain signal activity divided into several channels with different impulse responses that can be used to detect human emotions. In classifying emotions, EEG data needs to be parsed or signal processed into values ​​that can help recognize emotions. Research related to electroencephalography has been carried out previously and has experienced success using the Fuzzy C-Means, Multiple Discriminant Analysis, and Deep Neural Network methods. This study was conducted to classify human emotions from electroencephalography data on 10 participants. Each participant carried out 40 trials of testing using the Power Spectral Density (PSD) and Discrete Wavelet Transform (DWT) methods at the initial stage of classification and the Decision Tree method as the final method that can improve the accuracy of the two methods at the initial stage of classification. The results of this study were the finding of 2 participants (3 trials) who were unmatched from a total of 10 participants (400 trials), which were analyzed using the decision tree method. The decision tree method can correct this error and increase the classification result to 100%. The DWT method is used as a reference in the classification of emotions, considering that the DWT method has an output of arousal and valance values ​​. In contrast, the PSD method only has a combined output.
Co-Authors . Roslidar Afdhal Al Bahri Ary Firnanda Daifi Afrila Riefi DESI KURNIA NURILAHI Ernita Dewi Meutia Melinda Melinda Mukhroji Mukhroji Nurrisma Nurrisma Putri Ramadhani Rizal Munadi Rizal Munadi Safwan Sri Winarni Teuku Muhammad Mirza Keumala Teuku Yuliar Arif Zuhar Musliyana