IMPLEMENTASI LARAVEL UNTUK PREDIKSI PELUANG KERJA LULUSAN SMK MENGGUNAKAN DECISION TREE - Yesi Tri Maita; Fido Rizki; Deni Nurdiansyah (JUTIM (Jurnal Teknik Informatika Musirawas), 2026)
SMK Negeri Tugumulyo possesses comprehensive data on students' productive subject scores and industrial internship portfolios; however, these data have not been optimally utilized to predict graduates' employment opportunities. The evaluation of graduates' job readiness is still conducted manually, resulting in a lack of objective information for the school. This study aims to develop a web-based system for predicting graduates' employment opportunities using the Decision Tree method. The research employed the Research and Development (R&D) approach with the CRISP-DM framework, which consists of the business understanding, data understanding, data preparation, modeling, evaluation, and deployment phases. The dataset comprised 1,018 student records collected from three graduating cohorts. The system was developed using the Laravel framework and generates three prediction categories: Accepted, Considered, and Rejected. The evaluation results showed that the proposed model achieved an accuracy of 67.65% based on the confusion matrix, while Black Box Testing confirmed that all system functions operated as expected. Therefore, the developed system can assist schools in evaluating graduates' employment opportunities more objectively and based on data