Implementasi Algoritma Random Forest untuk Prediksi Perkembangan Anak Terintegrasi dengan Sistem Informasi Administrasi (Studi Kasus: TK Kramat Jati) - Nur diasih (Universitas Lampung, 2026)
Early childhood development is a crucial phase that requires continuous monitoring to ensure optimal growth. However, TK Kramat Jati still faces obstacles in managing administrative data and child development assessments that are conducted manually and not yet integrated. This research aims to develop a web-based administrative information system integrated with the Random Forest algorithm to predict child development. The research method uses a system development approach with data collection techniques through observation, interviews, and literature studies. The system was built using PHP Native, MySQL, and XAMPP with the implementation of the Random Forest algorithm for classifying child development based on cognitive, motoric, linguistic, and social-emotional aspects. Black box testing results show that all system functions run according to the design. Based on the implementation of the Random Forest algorithm with 100 decision trees and a maximum depth of 10, the model achieved 100% accuracy on the test data. User Acceptance Test (UAT) obtained an acceptance rate of 85% with a Very Good category. This research concludes that the administrative information system integrated with the Random Forest algorithm effectively assists in data management and child development prediction at TK Kramat Jati.