IMPLEMENTASI PENGENALAN WAJAH UNTUK ABSENSI KARYAWAN DENGAN METODE EIGENFACE

Authors

  • Bernad Oktavianus Siahaan Universitas Putera Batam
  • Nia Ekawati

Keywords:

Attendance System, Eigenface, OpenCV

Abstract

Attendance system has been widely used for schools, universities, even in companies. This system can also help HR / Human Resources in calculating data from employees, especially when approaching payday. PT Prima Nusantara Group carries out the employee attendance process by writing his name in the attendance book and signing it every day. No difficulty was found in inputting employee absent data, but the time required was very long so that it interfered with the effectiveness and efficiency of the admin in working. One of the most frequently used biometric technologies in attendance systems except for retinal recognition, finger print and eye scans is facial recognition. Face recognition performed using the eigenface algorithm method when extracted using principle component analysis (PCA) can produce a very high accuracy of face recognition reaching 90.83%. The eigenface method from openCV looks for facial data that is close to the facial data in the database. At this testing stage, the eigenface algorithm has been successfully applied in an employee attendance system with facial recognition to detect faces with the help of openCV. Face recognition process with the eigenface method is known to be sensitive because it depends on light intensity, distance and viewing angle.

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Published

2021-07-26

How to Cite

Siahaan, B. O., & Ekawati, N. (2021). IMPLEMENTASI PENGENALAN WAJAH UNTUK ABSENSI KARYAWAN DENGAN METODE EIGENFACE. Computer and Science Industrial Engineering (COMASIE), 5(5), 19–28. Retrieved from https://ejournal.upbatam.ac.id/index.php/comasiejournal/article/view/4096

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