<![CDATA[Online learning is one of the implementations of distance education that continues to develop, particularly with the utilization of video conferencing applications such as Zoom Meeting. This study aims to analyze the effectiveness of using Zoom Meeting in online learning by focusing on detecting students' attention levels based on blink analysis. In this research, an eye detection module was developed using the Dlib Model and Facelandmark, with the Histogram of Oriented Gradients (HOG) method as a feature extraction technique. Blink analysis was conducted to determine the blink ratio, which serves as an indicator of an individual's attention level. Generally, attention levels can be identified through blinking patterns, where fatigue or lack of focus is reflected in higher blink frequency. The study results show that the developed system can identify an individual's focus level with a highest accuracy of 95.56% in tests with three subjects, while the lowest accuracy was 72.24% in tests with 16 subjects. Based on the analysis of blink frequency during learning sessions using Zoom Meeting, it can be concluded that the average student focus level remains within the normal range.]]>
Copyrights © 2023
