SISTEM PREDIKSI SISWA MELANJUTKAN KE PERGURUAN TINGGI ATAU BEKERJA DENGAN METODE NAIVE BAYES

This research aims to design and develop a web-based prediction system capable of classifying the tendencies of 12th-grade students at SMK Negeri 2 Ponorogo to either continue to higher education or enter the workforce directly. The system employs the Naïve Bayes algorithm as the primary method for classifying student data, taking into account relevant attributes such as gender, major, academic grades, student interests, and parental occupation. The choice of the Naïve Bayes method is based on its ability to process data using a probabilistic approach that is simple yet effective, allowing it to generate accurate predictions that are easy to interpret by non-technical users. The objectives of this system development include the implementation of the Naïve Bayes algorithm to classify students’ post-graduation tendencies, as well as the provision of a data-driven, objective decision-support tool for guidance and counseling teachers (BK) and homeroom teachers in offering career advice. The system is designed with an accessible web interface, with user roles limited to admin and general users, without requiring email-based registration. The findings indicate that the developed system successfully provides reliable predictions and functions as a decision-support tool in student career counseling. The benefits are experienced by schools as a means of optimizing career guidance, by students as a reference in determining their future paths, and by academics as a reference for further research in the field of educational prediction.