Sistem Klasifikasi Monitoring dan Evaluasi Kelayakan Penerima Beasiswa UAD Menggunakan Algoritma Naïve Bayes

Abstract

Kartu Indonesia Pintar (KIP) scholarship program at Ahmad Dahlan University includes a monitoring and evaluation internal process conducted at the end of each semester to monitor scholarship recipients. This allows for an assessment of their eligibility to receive the scholarship in the upcoming semester. The current manual MONEVIN process results in a time-consuming and less objective eligibility analysis. This eligibility determination system is needed, utilizing data mining techniques based on previous KIP scholarship recipient data to make predictions. Naïve Bayes algorithm, a data mining technique employing mathematical probability calculations, is utilized. The process begins with preprocessing, followed by data mining, evaluation, system implementation, and testing using System Usability Scale. The research uses a dataset of 270 student records, employing a 9-fold cross-validation process to split the data. Implemented model is integrated into a website-based system accessible to Biro Kemahasiswaan dan Alumni (BIMAWA). Model testing employs the Confusion Matrix technique, resulting in an accuracy score of 0.985, precision of 0.987, recall of 0.985, and an F-score of 0.985, indicating a favorable classification outcome. The system's eligibility assessment is further tested using the SUS, yielding a score of 90. Therefore, it can be concluded that the developed system is suitable for use.

Keywords

• kip scholarship in uad
• data mining
• classification
• naïve bayes
• confusion matrix