Optimalisasi Artificial Intelligence dalam Pembelajaran Adaptif: Studi Kasus Platform EdTech Berbasis Data di Sekolah Menengah - Citra Anggun Permata; Doni Pratama Nugroho (Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern, 2025)
The rapid development of Artificial Intelligence (AI) has created new opportunities for adaptive learning in secondary education, particularly through data-driven Educational Technology (EdTech) platforms. However, empirical evidence on effective AI optimization in formal secondary schools in Indonesia remains limited. This study aims to examine the optimization of AI-based adaptive learning by identifying best practices, implementation barriers, and key success factors. A mixed-methods case study was conducted across five secondary schools in three Indonesian provinces. Quantitative data were collected from 500 students and analyzed using t-tests, ANOVA, and Pearson correlation, while qualitative insights were obtained from teachers, principals, and EdTech developers through thematic analysis. The findings show a 12.4% increase in average examination scores and an improvement in material completion rates from 74.2% to 88.6% within six months of AI implementation. A strong positive correlation was also found between AI usage intensity and academic achievement (r = 0.62, p < 0.01). This study contributes a practical evaluation framework for assessing the readiness and effectiveness of AI-driven adaptive learning based on real-world school data, offering actionable implications for educators, EdTech developers, and policymakers.