<![CDATA[This study aims to explore the application of Deep Learning technology in improving the quality of formative and summative assessments at the junior high school level in Banjarmasin City. The research findings indicate that the application of Deep Learning has significant potential in enhancing the effectiveness of assessments by providing faster, more targeted, and personalized feedback to students. The Deep Learning model is capable of analyzing student performance data in real-time, identifying patterns of difficulties faced by students, and offering more focused corrective recommendations, which were previously hard to achieve with conventional assessment methods. This study also identifies challenges in integrating this technology, such as the diversity of student characteristics, limited resources, and a curriculum that needs adjustments to fully accommodate this technology. However, the application of Deep Learning increases the objectivity of assessments, reduces human bias, and improves time efficiency for teachers by automating many aspects of the assessment process. Overall, the use of Deep Learning technology can have a positive impact on improving the quality of evaluation in Banjarmasin City's junior high schools, though greater attention to teacher training, curriculum adjustments, and the improvement of technological infrastructure is needed to ensure long-term success.]]>
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