Implementation of Profile Matching Analysis Method for Decision-Making in Online Learning for Homeschooling Student - Jikti Khairina; Nurdin Nurdin; Muhammad Nasir (Journal of Artificial Intelligence and Software Engineering, 2024)
In a homeschooling learning system, adjustment between learning methods and student characteristics is very important to achieve optimal learning outcomes. Online learning provides flexibility for homeschooled students, but determining the most appropriate learning method according to the student's profile is still a challenge. In the context of homeschooling, where an individual approach is needed, the application of the Profile Matching method in decision-making for an online learning system allows for the personalization of education according to student characteristics, where this method provides recommendations for the most appropriate learning methods based on student profiles, including learning styles, cognitive abilities, and learning preferences. By comparing the profile of students' competencies and learning styles against predetermined criteria, the system can provide recommendations for appropriate learning methods. The results of this study indicate that the Profile Matching Analysis method can improve learning effectiveness and facilitate personalization of the learning process.