Optimizing Artificial Intelligence for the Use of Learning Management Systems at STMIK Mardira Indonesia - Fadli Emsa Zamani (Social Impact Journal, 2026)
This comprehensive research investigation aims to systematically explore and analyze the implementation of Artificial Intelligence (AI) technologies to optimize and enhance the usage of Learning Management System (LMS) at STMIK Mardira in Indonesia. The study employs a rigorous mixed-method approach combining qualitative and quantitative data collection techniques to provide triangulated findings. A total of 150 undergraduate students and 25 full-time faculty members participated in this research through structured questionnaires, semi-structured in-depth interviews, direct classroom observation, and focus group discussions. The comprehensive findings indicate that integrating AI-powered technological features such as personalized learning paths, automated intelligent feedback systems, and adaptive intelligent tutoring significantly improves overall student engagement by 45%, substantially reduces learning time requirements by 38%, and dramatically enhances overall academic performance achievements by 32%. Additionally, faculty workload burden decreases substantially by 40% through comprehensive automation of grading systems and administrative tasks, liberating valuable faculty time for meaningful pedagogical activities. The study strongly recommends establishing comprehensive training programs for educators and implementing phased systematic implementation of AI features to ensure sustainable long-term adoption and institutional success. This significant research contributes substantially to the growing body of knowledge regarding how AI and machine learning technologies can effectively optimize educational technology platforms in higher education institutions, particularly within the Indonesian context.