Principal Component Analysis and Regional Coordinates on Face Recognition in Mobile-Based Attendance Systems

Authors

  • Indah Puspasari Handayani Universitas Budi Luhur
  • Rizky Pradana Universitas Budi Luhur

DOI:

https://doi.org/10.32493/informatika.v9i1.33362

Keywords:

Presence, Face Recognition, Mobile, Principal Component Analysis, Regional Coordinates

Abstract

The pattern of attendance in the world of work after the Covid-19 outbreak that hit the world, has apparently brought quite big changes, due to the taboo on gathering and using shared media which is considered a medium for the spread of bacteria/viruses. The way out of this is to use facial recognition and collaborate with location coordinates using a mobile application that can be used on each smartphone to authenticate workers in changing the characteristics of presence data, so that the presence process cannot be represented. The method used for face recognition in this research is Principal Component Analysis (PCA) by linearly transforming eigenvalues ​​and eigenvectors from extraction and reduction of faces captured from the mobile presence application. Based on the trials carried out, the success rate reached 78,667% for testing the functionality and strength of facial recognition.

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Published

2024-08-08

Issue

Vol. 9 No. 1 (2024): JURNAL INFORMATIKA UNIVERSITAS PAMULANG

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Article

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