Penerapan Model Least Square Untuk Prediksi Nilai Dalam Sistem Pengabdian Berbasis Website
DOI:
https://doi.org/10.47065/bulletincsr.v5i5.715Keywords:
Information System; Internship; Online Attendance; Daily Report; Artificial Intelligence; Least Square RegressionAbstract
This study aims to develop a web-based internship information system (PKL) at SMK At-Taqwa Muhammadiyah Miri to replace the manual process of recording student attendance and daily activity reports. The main problem addressed in this research is the inefficiency of PKL administrative processes, which are still carried out manually, leading to a high risk of data loss, delayed reporting, and low accuracy in student performance evaluation. In addition, monitoring student activities by supervisors and teachers is less than optimal due to the absence of a real-time integrated reporting system. The system was built using the Waterfall method with the Laravel framework and MySQL database, and it integrates a Least Square regression model to predict students’ final scores based on their attendance and daily activities. The system testing results showed 100% functional success across 16 test scenarios using the Black Box method. This system is expected to improve efficiency, transparency, and objectivity in monitoring and evaluating internship activities.
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