No abstract

In education, it is crucial to make the students enjoy during the class. Many platforms have been introduced for online classes, especially since the COVID-19 pandemic; thus, it is significant to assess the student's perception of the usability of those platforms. This research aims to evaluate the usability of the selected platforms, Google Classroom, Microsoft Teams, and Padlet. The System Usability Scale is used to measure the usability of each Learning Management System platform. A survey consisting of ten questions is distributed to a group of students. The result indicates that Google Classroom got the highest usability score, suggesting that it provides students with a more user-friendly and intuitive experience. Although Microsoft Teams received the lowest usability score, ironically, most students prefer to use it compared to the other LMSs. These findings emphasise that it is important to consider factors beyond usability alone when assessing students' platform preferences. Understanding these factors can assist educators in making informed decisions about selecting and implementing LMS platforms.

No abstract

<p>COVID-19 is a pandemic crisis that has introduced new norm to the world where we are not encouraged to be in 3C areas, namely crowded place, confined space, and close conservation. We must also ensure that we are at least one meter apart from one another at all time even while queuing. The queuing process can be seen at any organization that offer services. Adhering to the new norm can be a challenge for organization such as banks, hospitals, and government offices when the number of clients waiting in queue increases while in confined space.  On the client’s side, they must go through the queue process of obtaining a queue number ticket and then wait to be served in confined and sometimes crowded space every time they require a service.  Thequeue process will be repeated at different premise. This study proposes real-time multi-organizationsC19-SmartQ system which use predictive modelling to generate single or consecutive queue number tickets for any client requiring services from two different organizations located within the same building.  C19-SmartQsystemmanages queues thus administer social distancing and streamline queues to reduce waiting periods and improve service efficiency. To ensure operability of C19-SmartQ system, itwas tested on the functionality and web server speed performance. The web server speed performance results show that data transfer and web loading were stable since there was only an increase of 0.2 seconds or 0.08% as the number of users per session increases. In the future, the system can be designed to accommodate queuing for more organizations located within the same building.  Machine learning can also be integrated in the system to improve the predictive modelling based on current environment at each organization.</p>

No abstract