<![CDATA[This study examines the emotional dynamics of the main character in Dwi Nur Rahmawati's Leiden and analyzes how these emotions can inform literature teaching within the Merdeka Curriculum. Employing a descriptive mixed-methods design, the research integrates qualitative literary psychology analysis with quantitative frequency mapping. Data were collected through systematic reading, identification of emotional expressions, structured recording, and coding of 76 emotional quotations from the novel. Analysis followed Miles, Huberman, and Saldaña's interactive model to classify emotion types, examine narrative contexts, identify patterns, and interpret pedagogical relevance. The findings revealed three significant patterns. First, sadness emerged as the dominant emotion (18.4%), followed by love and fear (14.5% each) and guilt (11.8%), indicating the protagonist's psychological vulnerability characteristic of adolescent development. Second, nonverbal behavior (39.5%) and author narration (35.5%) appeared more frequently than dialogue (25%), demonstrating a "show, don't tell" characterization strategy requiring inferential reading. Third, complex emotions appeared in 10.5% of instances, exclusively through author narration, reflecting psychological nuance demanding higher-order interpretation. These emotional patterns are pedagogically relevant because they mirror adolescents' socioemotional experiences and provide opportunities for developing empathy, emotional literacy, and analytical reading skills. The findings demonstrate that emotional analysis can serve as a foundation for designing character-oriented literature activities aligned with Phase F learning outcomes in the Merdeka Curriculum. The study contributes empirical support for integrating literary psychology into Indonesian literature classrooms through structured emotional mapping and offers practical guidance for teachers seeking to enhance students' character formation and critical comprehension within curriculum frameworks emphasizing competency-based, analytical, and reflective learning.]]>
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