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All Journal Mobile and Forensics
Robin, Qori Aulia
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Library & Information Science Neuroscience

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K-Means for Majoring Informatics Students' Interests Based on Brainwave Signals Robin, Qori Aulia; Azhari, Ahmad
Mobile and Forensics Vol. 5 No. 1 (2023)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v5i1.6629

Abstract

This study investigates the potential of utilizing EEG (electroencephalogram) as a determinant for the specialization choices of Informatics students. EEG, measuring brain activity patterns, is employed to discern majors of interest among students. A questionnaire revealed that some students opt for specializations due to class availability and peer influence, leading to potential mismatches between their abilities and interests, consequently affecting their final project or thesis. EEG data from 30 respondents, recorded using NeuroSky Mindwave and MyndPlayer Pro software, were subjected to K-Means Clustering after feature extraction through PCA. However, the evaluation using Silhouette indicated a low score of 0.453, possibly due to significant distance between cluster data and centroids, minimal dataset size, and random respondent selection without considering their specific areas of interest. This suggests limitations in using EEG alone for determining specialization choices, necessitating further refinement and integration with additional factors for more accurate predictions.
Co-Authors Ahmad Azhari