Analisa Kompetensi Teknologi Informasi dan Komunikasi (TIK) Siswa SMP Negeri 4 Cibitung Menggunakan Algoritma Naive Bayes - Salsabila Oktavia Jusuf; Arafat Febriandirza (IKRA-ITH Informatika : Jurnal Komputer dan Informatika, 2026)
The rapid development of Information and Communication Technology (ICT) requires students to possess adequate competencies to support learning activities in the digital era. However, students demonstrate varying levels of ICT competence, making an objective classification method necessary. This study aims to classify students' ICT competencies using the Naïve Bayes algorithm. The research data were collected through questionnaires distributed to 101 students of SMP Negeri 4 Cibitung. Before the classification process, the data were labeled using the quartile method, resulting in four competency categories: Not Proficient, Less Proficient, Moderately Proficient, and Proficient. The classification process was carried out using RapidMiner, while the model performance was evaluated using a Confusion Matrix. The results showed that 21 students (20.79%) were categorized as Not Proficient, 20 students (19.80%) as Less Proficient, 33 students (32.67%) as Moderately Proficient, and 27 students (26.73%) as Proficient. The proposed classification model achieved an accuracy of 97.03%, indicating that the Naïve Bayes algorithm performed very well in classifying students' ICT competencies. The findings are expected to support schools in evaluating and improving students' ICT competencies. Keywords : ICT Competency, Naïve Bayes, Data Mining, Classification, RapidMiner.