πŸ“… 08 July 2024
DOI: 10.26877/asset.v6i3.672

The AirNav Semarang Employee Presence System Using Face Recognition Based on Haar Cascade

Advance Sustainable Science, Engineering and Technology
Universitas Persatuan Guru Republik Indonesia Semarang

πŸ“„ Abstract

The presence of employees is a key factor in supporting the needs of the workplace. At present, the employee presence system at PT. AirNav Indonesia Semarang Branch still uses fingerprint and RFID-based employee ID cards for authentication. This RFID-based system can increase employee fraud by allowing employees to misuse each other's ID cards. To avoid such fraud, a system needs to be built and it will be using face recognition technology as the primary authentication method, with the Haar Cascade Algorithm. This algorithm has the advantage of being computationally fast, as it only relies on the number of pixels within a rectangle, not every pixel of an image. In addition to fast computation, this algorithm also has the advantage of identifying objects that are relatively far away. With the implementation of the Haar Cascade algorithm, the results indicate the capability of face recognition in detecting the faces of registered employees within the system based on facial angles with an accuracy rate of 60%, expressions with an accuracy rate of 100%, as well as obstructive parameters such as glasses and masks with an accuracy rate of 33.33%. The ability to detect objects from various camera angles, recognize faces with different expressions, and identify objects obstructed by parameters can serve as reasons why this algorithm needs to be implemented

πŸ”– Keywords

#Attendance System; Authentication; Face recognition; Haar Cascade Classifier

ℹ️ Informasi Publikasi

Tanggal Publikasi
08 July 2024
Volume / Nomor / Tahun
Volume 6, Nomor 3, Tahun 2024

πŸ“ HOW TO CITE

Azzahra, Fidela; Sari, Christy Atika; Rachmawanto, Eko Hari, "The AirNav Semarang Employee Presence System Using Face Recognition Based on Haar Cascade," Advance Sustainable Science, Engineering and Technology, vol. 6, no. 3, Jul. 2024.

ACM
ACS
APA
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver

πŸ“š References & Citations

Artikel ini telah dikutip oleh 1 publikasi lainnya.

πŸ”— Artikel Terkait dari Jurnal yang Sama

πŸ“Š Statistik Sitasi Jurnal