Facial Recognition Implementation using K–NN and PCA Feature Extraction in Attendance System

Authors

  • Juliansyah Putra Tanjung Universitas Prima Indonesia, Indonesia
  • Bayu Angga Wijaya Universitas Prima Indonesia, Indonesia

DOI:

10.33395/sinkron.v5i1.10612

Keywords:

Face; K-Nearest Neighbor (K – NN); Principal Component Analysis (PCA); Attendance; School;

Abstract

Attendance is the fact that someone is present at an event or goes regularly to an institution, or attendance at an event is the number of people present at that time. The Saifiatul Amaliyah school itself is one of the many schools in Indonesia where the attendance of students or attendance is still done manually. This can cause problems, namely allowing fraud when filling in attendance and errors in data recapitulation. Therefore, in this study a computerized face attendance was created, which was formed using the K-Nearest Neighbor (K-NN) method and combined with the extraction of the Principal Component Analysis (PCA) feature where the attendance process can be done with a person's face. The face attendance system using the K-NN and PCA methods has an accuracy of 82%.

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Publication History:

Submitted Sep 4, 2020
Published Oct 1, 2020
Last Modified Oct 6, 2020

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How to Cite

Tanjung, J. P., & Wijaya, B. A. (2020). Facial Recognition Implementation using K–NN and PCA Feature Extraction in Attendance System. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 5(1), 43-50. https://doi.org/10.33395/sinkron.v5i1.10612