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CREATION
Title : Oversampling approach using Radius-SMOTE for imbalance electroencephalography datasets
Author :

Prof. Drs. Retantyo Wardoyo, M.Sc., Ph.D. (1) I MADE AGUS WIRAWAN (2) GEDE ANGGA PRADIPTA (3)
Date : 0 2022
Keyword : Electroencephalogram; ,Radius- SMOTE; ,Emotion Recognition; ,Oversampling; Imbalance Data Electroencephalogram; ,Radius- SMOTE; ,Emotion Recognition; ,Oversampling; Imbalance Data
Abstract : Several studies related to emotion recognition based on Electroencephalogram signals have been carried out in feature extraction, feature representation, and classification. However, emotion recognition is strongly influenced by the distribution or balance of Electroencephalogram data. On the other hand, the limited data obtained significantly affects the imbalance condition of the resulting Electroencephalogram signal data. It has an impact on the low accuracy of emotion recognition. Therefore, based on these problems, the contribution of this research is to propose the Radius SMOTE method to overcome the imbalance of the DEAP dataset in the emotion recognition process. In addition to the EEG data oversampling process, there are several vital processes in emotion recognition based on EEG signals, including the feature extraction process and the emotion classification process. This study uses the Differential Entropy (DE) method in the EEG feature extraction process. The classification process in this study compares two classification methods, namely the Decision Tree method and the Convolutional Neural Network method. Based on the classification process using the Decision Tree method, the application of oversampling with the Radius SMOTE method resulted in the accuracy of recognizing arousal and valence emotions of 78.78% and 75.14%, respectively. Meanwhile, the Convolutional Neural Network method can accurately identify arousal and valence emotions of 82.10% and 78.99%, respectively.
Group of Knowledge : Ilmu Komputer
Original Language : English
Level : Internasional
Status :
Published
Document
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1 Paper ESJ.pdf
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2 Similaritas Paper_ESJ.pdf
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3 Bukti Korespondensi ESJ RW-compressed.pdf
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4 Ver4 Surat Pernyataan Publikasi syarat utama RW-final.pdf
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5 BK Retantyo Oversampling Approach Using Radius.pdf
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