<![CDATA[Our research is focused on developing an effective attendance system that matches the conditions of pandemic or other specific pandemic situations. We have built a legacy system using Randomized QR-Code and MAC-Address as the authentication method. Based on the analysis, it is known that users need around 25.8877 seconds to authenticate their presence in the system. Therefore, we are trying to improve the authentication time and robustness of the system by using user facial biometrics. Facial biometrics was chosen because it is the most appropriate way to authenticate one's identity during pandemic, where physical contact is unnecessary or even expected to be avoided. According to several test scenarios, it is known that our new system takes time simultaneously to recognize the user and record their presence data once they show their face to the recognition camera. This new system can also run more powerfully with a percentage of 1.26% processor time, 16.9059% faster than the previous system, because it is deployed in a web browser using the latest web app framework technology, which can run on various devices. Based on these findings, our new approach successfully improves its predecessor systems. To produce a robust attendance system, we must implement a Biometric Authentication method, which is enhanced with other secure authentication methods such as Random QR-Code scanning. With a combination of these methods, an attendance system will run safely and efficiently.]]>
