<![CDATA[Automation of the attendance process has become a necessity nowadays to facilitate the process of recording and recapitulating precise attendance data compared to conservative (manual) attendance. This process is carried out through the recognition of biometric information, namely faces, using the Naive Bayes method with Gaussian distribution and pre-trained VGG16 feature extraction. In this study, the model developed based on this method uses the public CASIA WebFace dataset which has high variation and a private dataset which has low variation. The results show that the proposed method is able to work well on datasets with low variation, with accuracy results reaching 97% supported by feature dimension reduction using the PCA method.]]>
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