TY - GEN
T1 - Android application for presence recognition based on face and geofencing
AU - Shahab, Alvin Syarifudin
AU - Sarno, Riyanarto
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/19
Y1 - 2020/9/19
N2 - The Attendance system, especially in companies is needed to help assess the attendance and discipline of employees. Some attendance systems that have been made based on the detection of biometrics, barcodes, and QR Codes have not been able to simplify the attendance process where employees still have to queue in front of the attendance machine. This paper aims to design an attendance system that flexible which can simplify and speed up the process by using a mobile application based on geofencing and face recognition so the company does not need to expend the extra cost to buy dedicated machine. The system is using a mobile application as a device to presence. Each of the employees has their own geofencing area which worked as a location virtual boundary. The employee face images are sent to the server from mobile application for the attendance process which includes a recognition process using k-Nearest Neighbours (k-NN) and Principal Component Analysis (PCA). The results obtained are using face recognition k-NN and PCA obtained a 90% accuracy rate with a processing time of 1.5 seconds. The fastest time to do a complete presence is 3.4s which include a geofencing authentication and face recognition process.
AB - The Attendance system, especially in companies is needed to help assess the attendance and discipline of employees. Some attendance systems that have been made based on the detection of biometrics, barcodes, and QR Codes have not been able to simplify the attendance process where employees still have to queue in front of the attendance machine. This paper aims to design an attendance system that flexible which can simplify and speed up the process by using a mobile application based on geofencing and face recognition so the company does not need to expend the extra cost to buy dedicated machine. The system is using a mobile application as a device to presence. Each of the employees has their own geofencing area which worked as a location virtual boundary. The employee face images are sent to the server from mobile application for the attendance process which includes a recognition process using k-Nearest Neighbours (k-NN) and Principal Component Analysis (PCA). The results obtained are using face recognition k-NN and PCA obtained a 90% accuracy rate with a processing time of 1.5 seconds. The fastest time to do a complete presence is 3.4s which include a geofencing authentication and face recognition process.
KW - face recognition
KW - geofencing
KW - k-Nearest Neighbours
KW - mobile-based presences system
KW - principal component analysis
UR - http://www.scopus.com/inward/record.url?scp=85096850830&partnerID=8YFLogxK
U2 - 10.1109/iSemantic50169.2020.9234253
DO - 10.1109/iSemantic50169.2020.9234253
M3 - Conference contribution
AN - SCOPUS:85096850830
T3 - Proceedings - 2020 International Seminar on Application for Technology of Information and Communication: IT Challenges for Sustainability, Scalability, and Security in the Age of Digital Disruption, iSemantic 2020
SP - 208
EP - 213
BT - Proceedings - 2020 International Seminar on Application for Technology of Information and Communication
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Seminar on Application for Technology of Information and Communication, iSemantic 2020
Y2 - 19 September 2020 through 20 September 2020
ER -