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Model Prediction of Psychoanalysis Trend of Radical Emotional Aggressiveness Using EEG and GLCM-SVM Method

A. Setianingrum,Bagus Sulistio Budhi

Published 2018 in 2018 6th International Conference on Cyber and IT Service Management (CITSM)

ABSTRACT

The prototype model of Aggressiveness Emotion Trends maps issues that trigger emotional aggressiveness such as demonstrations, protests and anger against a condition that is contrary to fate (aqidah) and ideology. The system model approaches psychological behavioral psychoanalytic theory, face recognition, voice recognition, natural language processing, dynamic keystroke, touch screen gesture interaction, EEG brain wave recording., Knowledge representation is used to identify 30, 50, 60 sample respondents with parameters of GBA, GKA, Personality Type and Test of Emotional Aggressiveness in the form of questionnaires. Correlation Methods with result $\alpha \gt 0.557$, $\alpha \gt 0.512$ and $\alpha \gt 0.592 -$ Regression is used to simulate the relationships between variables and obtain the Z score of Score (-4.29-5.52) and T Score (8.07-105.15). Electroenchephalograph (EEG) as a tool that can record electrical activity in the brain through electroda placed on the skin. The characteristics of different brain waves indicate the mental state is divided into several types of Gamma waves (16 - 100 Hz), Beta (12-19 Hz), Alpha (8-12 Hz), Theta (4-7 Hz) and Delta (0.5-4 Hz). The system simulates the prediction and the 2 samples of respondents who have checked their brain waves to produce the Average Frequency (8.421904762 Hz and 6.8857143 Hz) contain the Alpha and Theta categorical waves.

PUBLICATION RECORD

  • Publication year

    2018

  • Venue

    2018 6th International Conference on Cyber and IT Service Management (CITSM)

  • Publication date

    2018-08-01

  • Fields of study

    Psychology

  • Identifiers
    DOI 10.1109/CITSM.2018.8674343
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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