Abstract
One of the keys to success in learning is determining student learning styles. Learning styles are grouped into 3, grouping learning styles based on the characteristics of students. Sample data was used for 3 classes in the artificial intelligence course with total data of 83 students who answered 36 questions. To be able to carry out student mapping using the k modes method for clustering. The K modes method is used because the data used is categorical. K modes can be used for multi-dimensional clustering and shorter computing times. With the clustering application for grouping student learning styles with a sample of 83 students by answering 36 questions to be divided into 3 groups, the results were 37 students for the visual group, 31 students for the auditory group, and 15 students for kinesthetics. At the testing stage, black box testing is used. By knowing learning style groups, students can easily learn and absorb information.
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