Integrasi Teknologi Deep Learning Dalam Analisis Teks Dan Pembelajaran Bahasa Indonesia Di Sekolah Menengah

Abstract

This study aims to analyze the integration of deep learning technology in text analysis and Indonesian language learning in secondary schools. The method used is a qualitative descriptive approach with a library research approach. Data were obtained from various secondary sources, including books, national and international journal articles, and relevant educational policy documents from 2023 to 2025. Data collection techniques were carried out through documentation and literature reviews, while data analysis used content analysis techniques. The results show that deep learning technology plays a significant role in improving the quality of text analysis, including identifying linguistic structures, understanding contextual meaning, and automatically detecting language errors. Furthermore, this technology can also improve students' writing skills, learning motivation, and critical thinking skills through adaptive and personalized learning. The integration of deep learning is also in line with the implementation of the Merdeka Curriculum, which emphasizes digital literacy and project-based learning. However, several challenges in its implementation exist, such as the digital divide, limited teacher competency, and ethical issues regarding the use of artificial intelligence in education. Therefore, an appropriate strategy is needed to optimize the use of this technology to support the sustainable improvement of the quality of Indonesian language learning in the digital era.