This study aims to analyze students’ learning difficulties in solving linear programming problems based on their thinking styles. Learning difficulties often arise from differences in the way students think and process information. This research employed a descriptive qualitative approach involving eight eleventh-grade students at SMK Negeri 2 Tanjungpinang, selected purposively according to four thinking-style categories: sequential concrete, sequential abstract, random concrete, and random abstract. Data were collected through written tests and semi-structured interviews, then analyzed using Miles and Huberman’s model, which includes data reduction, data display, and conclusion drawing. The results indicate that students with sequential concrete and sequential abstract thinking styles tend to perform better in solving problems systematically, although they still struggle with algorithmic procedures and inequality notation. Meanwhile, students with random concrete and random abstract thinking styles experienced greater difficulties in understanding problem information, translating it into mathematical models, and identifying extreme points on graphs. These findings suggest that thinking style differences significantly affect students’ mathematical learning difficulties, highlighting the need for teachers to apply adaptive learning strategies that align with students’ cognitive characteristics to improve their understanding of linear programming concepts.
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