The Role of EEG Signals: SVM Classification of Cognitive Load as a Support for UX Evaluation

Ennu Intan Iksan(1), Murein Miksa Mardhia(2*)


(1) Universitas Ahmad Dahlan
(2) Universitas Ahmad Dahlan
(*) Corresponding Author

Abstract


Cognitive load is the mental effort that needs to be applied to working memory to process information received over a period of time. Cognitive load can be viewed as the level of mental energy required to process a given amount of information. In user experience design, cognitive load is considered as the mental processing power required to use a product. If the amount of information processed exceeds the user's ability to process it, the overall performance will be disrupted. An EEG device is needed that is used to record electrical activity that occurs in the brain by channeling brain electrical waves to cables and modulators that are sensitive to electrical waves. The object of this research is the EEG Beta signal with the attention wave type from UX testing activities on students aged 21-24 years with a frequency level of 13-30 Hz. The EEG tool records the activity of the respondent's wave signal by collecting data on the activity of working on a questionnaire about evaluating the WhatsApp application using the Google Form application. The classification of cognitive load studied is unencumbered and burdened. Unencumbered represents the ease that is felt when interacting with the application, while burdened represents the difficulty or confusion that is felt when interacting with the application. Testing is done with the Confusion matrix. The best accuracy results among the kernel types in the SVM method are linear kernel types with an accuracy result of 89% consisting of 1 data that is categorized as an unencumbered label and 8 data labels that are loaded

Keywords


Cognitive Load; UX; Electroencephalogram; Support Vector Machine (SVM);

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References


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DOI: https://doi.org/10.26714/jichi.v4i1.11198

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Journal of Intelligent Computing and Health Informatics (JICHI)
ISSN 2715-6923 (print) | 2721-9186 (online)
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Department of Informatics
Faculty of Engineering
Universitas Muhammadiyah Semarang

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