Pemanfaatan Deep Learning dalam Analisis Faktor-Faktor Disiplin Diri Siswa dengan Pendekatan Kearifan Lokal
DOI:
https://doi.org/10.29407/yhdhkk16Keywords:
Self-Discipline, Deep Learning, Local Wisdom, Character Education, Educational TechnologyAbstract
Self-discipline is a crucial aspect in shaping students' character, directly affecting their academic success and social behavior. However, the level of student discipline remains a challenge across educational levels. This article explores the utilization of deep learning technology to analyze factors influencing students' self-discipline by integrating local wisdom as the underlying cultural values shaping their behavior. Deep learning is capable of processing large and heterogeneous data, including quantitative and qualitative data related to student behavior and local cultural values. This approach is expected to contribute to designing contextual character education strategies rooted in national culture and supported by technological advances. The study indicates that integrating deep learning with local wisdom can improve the accuracy of predicting student discipline and strengthen the preservation of cultural values in modern education.
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