<![CDATA[This study aims to determine the effect of implementing Artificial Intelligence (AI)-based Virtual Tutoring technology on students’ learning interest in Computer Systems material. The research employed a quasi-experimental method with a Pretest–Posttest Nonequivalent Control Group Design. The research subjects consisted of two classes: an experimental class that received treatment using AI Virtual Tutoring and a control class that received conventional learning. The results showed that the students’ initial learning interest was relatively balanced, with the average pretest score of the control class at 38.33 and the experimental class at 36.42. After the treatment was administered, the average posttest score of the experimental class increased significantly to 85.64, while the control class only reached 70.72. The normality test using Shapiro–Wilk indicated that all data were normally distributed (significance value > 0.05), while the homogeneity test using Levene’s Test showed that both groups were homogeneous (sig. 0.211 > 0.05). The independent t-test results revealed a significant effect on the improvement of students’ learning interest in the experimental class. The increase of 49.22 points, or more than 135% from the initial pretest condition, indicates that AI features such as automated explanations, interactive visual simulations, real-time quizzes, and instant feedback were able to enhance students’ engagement, motivation, and attention during the learning process. Therefore, the implementation of AI Virtual Tutoring is proven to be effective and significant in improving students’ learning interest in Computer Systems material and is suitable to be applied as a modern technology-based learning innovation at SMA Negeri 7 Kupang.]]>
