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Classification Of Brainwave Using Data Mining In Producing An Emotional Model

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dc.contributor.authorKhairul Anuaren_US
dc.contributor.authorNurshuhada Mahfuzen_US
dc.contributor.authorWaidah Ismailen_US
dc.contributor.authorZalisham Jalien_US
dc.contributor.authorMd Jan Nordinen_US
dc.date.accessioned2024-05-28T04:44:44Z
dc.date.available2024-05-28T04:44:44Z
dc.date.issued2015
dc.descriptionJournal of Theoretical and Applied Information Technology 20th May 2015 -- Vol. 75. No. 2 -- 2015en_US
dc.description.abstractIn this paper, classification of brainwave using real world data from Parkinson’s patients is presented. Emotional model is produced from the classification of brainwave. Electroencephalograph (EEG) signal is recorded on eleven Parkinson’s patients. This paper aim to find the “best” classification for the emotional model in brainwave patterns for the Parkinson’s disease. The work performed based on the two method phases which are using the raw data and pre-processing data. In each of the method, we performed for steps in the sum of the hertz and divided by total hertz. In the pre-processing data we are using statistic mean and standard deviation. We used WEKA Application for the classification with 11 fold validation. As a results, implecart from the classification tree performed the “best” classification for the emotional model for Parkinson Patients. The Simplecart classification result is 84.42% accuracy.en_US
dc.identifier.epage136
dc.identifier.issn1992-8645
dc.identifier.issue2
dc.identifier.spage128
dc.identifier.urihttp://www.jatit.org/volumes/seventyfive2.php
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/6123
dc.identifier.volume75
dc.language.isoen_USen_US
dc.publisherLittle Lion Scientificen_US
dc.relation.ispartofJournal of Theoretical and Applied Information Technologyen_US
dc.subjectClassification,en_US
dc.subjectBrainwave,en_US
dc.subjectEmotional Model,en_US
dc.subjectParkinson Patientsen_US
dc.titleClassification Of Brainwave Using Data Mining In Producing An Emotional Modelen_US
dc.typeArticleen_US
dspace.entity.typePublication

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