EFFECTIVENESS OF USING META AI IN IMPROVING UNDERSTANDING OF ALGEBRA CONCEPTS BY GRADE VII STUDENTS AHMAD YANI JUNIOR HIGH SCHOOL

This study aims to analyze the effectiveness of using Meta AI in improving the understanding of algebra concepts of seventh-grade students at Ahmad Yani Pagelaran Junior High School. The background of the problem shows that students have difficulty understanding basic algebra concepts, including the introduction of variables, coefficients, constants, and simplification of algebraic equations due to the use of conventional learning methods that are less interactive. The study used a quasi-experimental design with 42 students divided into an experimental group (using Meta AI) and a control group (conventional method). Data were collected through pretests, posttests, and learning observations, then analyzed using descriptive and inferential statistics with t-tests and N-Gain analysis. The results showed a significant difference between the two groups (p < 0.05). The experimental group achieved an average posttest of 83 with an N-Gain of 73.4% (high category), while the control group only achieved 35 with an N-Gain of 17% (low category). The classical completeness of the experimental group reached 100%, exceeding the minimum standard of 85%. Meta AI has been shown to increase student engagement by up to 90%, reduce procedural errors by 70%, and improve the accuracy of identifying algebraic components by up to 85%. The study concluded that Meta AI is highly effective in improving understanding of algebraic concepts through adaptive, personalized, and interactive learning tailored to individual students' needs.