Efektivitas Deep Learning dalam Pembelajaran Informatika Kelas X.A di SMA Negeri 1 Ciledug

Abstract

The development of learning in the digital era demands the implementation of strategies that are not only oriented towards mastery of material, but also capable of developing students' critical thinking and problem-solving skills. However, the Informatics learning process in schools is still often dominated by material delivery, so that active student engagement and higher-order thinking skills have not developed optimally. This condition encourages the need for the implementation of a deep learning approach that emphasizes in-depth conceptual understanding, meaningful learning, and active student participation. This study aims to describe the implementation of a deep learning approach and improve student learning outcomes in Informatics subjects. The study used the Classroom Action Research (CAR) method implemented in two cycles, each including the planning, implementation, observation, and reflection stages. The research subjects were class X.A students of SMA Negeri 1 Ciledug in the 2025/2026 academic year. Data were collected through observation and learning outcome tests, then analyzed descriptively quantitatively to compare the results between cycles. The results showed an increase in the quality of learning implementation, student participation, and learning outcomes from Cycle I to Cycle II. These findings indicate that the implementation of deep learning has the potential to support more active and meaningful Informatics learning, although this study was not designed to test its effectiveness inferentially.