IMPLEMENTASI DEEP LEARNING UNTUK MENINGKATKAN HASIL PEMBELAJARAN DI SEKOLAH MENENGAH KEJURUAN (SMK) SE-JAKARTA BARAT

Abstract

This research explores the implementation of deep learning technology to enhance learning outcomes in Vocational High Schools (SMK) across West Jakarta. By utilizing deep learning in education, there is significant potential to analyze student data for performance prediction, learning needs identification, and automated assessment. The goal of this study is to develop a deep learning model that can support teachers and educational administrators in tracking students' learning progress, identifying learning difficulties early on, and improving the effectiveness of the learning process. Using deep learning algorithms such as Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN), the model is evaluated in the context of predicting students' academic achievement. The findings indicate that the deep learning model achieves high predictive accuracy in identifying students requiring targeted intervention, which leads to overall improvement in learning outcomes. The implications of these findings are expected to help educators in SMK implement more adaptive and targeted instructional strategies.