Kurniawan, Vincentius and Wicaksana, Arya and Prasetiyowati, Maria Irmina (2017) The implementation of eigenface algorithm for face recognition in attendance system. 2017 4th International Conference on New Media Studies (CONMEDIA).
Full text not available from this repository.Abstract
Technology advancement has brought in mobility and flexibility into the workplaces in contrast to the old days. Workers are demanded to perform their job at places other than their office. The well-known long-established attendance systems that are widely used in workplaces are heavily depending on technologies such as the Radio Frequency Identification (RFID) and fingerprint. Both technologies have limitation especially when it comes to flexibility and mobility. Thus, this research proposes an attendance system that addresses the mentioned condition. The attendance system is built using Android and web technologies with geolocation extraction feature and biometric technology: the face recognition. The Eigenface algorithm is chosen for face recognition process in the system. In addition to that, Euclidean distance is used for calculate the distance between input image and the training image. There are variables in this research that may disturb the recognition process: lighting, distance between the face and the camera, and hardware specifications, which are not taken into consideration. Based on the implementation and testing process, the overall accuracy of the system is 86.67%.
| Item Type: | Article |
|---|---|
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 006 Special Computer Methods 600 Technology (Applied Sciences) > 650 Management and Public Relations > 651 Office Services |
| Divisions: | Faculty of Engineering & Informatics > Informatics |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 07 Oct 2021 03:53 |
| Last Modified: | 07 Oct 2021 03:53 |
| URI: | https://kc.umn.ac.id/id/eprint/18562 |
Actions (login required)
 |
View Item |
