Penerapan Algoritma Naive Bayes untuk Klasifikasi Penurunan Semangat Belajar Mahasiswa Program Studi Sistem Informasi Angkatan 2023 Universitas Nahdlatul Ulama Lampung

Abstract

Learning motivation plays an important role in supporting students’ academic performance as well as their involvement in learning activities. A decrease in motivation can arise from both personal and environmental influences, such as self-drive, social media exposure, time management ability, peer influence, and daily study behavior patterns. This study focuses on analyzing the factors related to the decline in learning motivation among students of the Information Systems Study Program, Class of 2023, Universitas Nahdlatul Ulama Lampung, while applying the Naive Bayes method for data classification. A quantitative approach was adopted, where data were collected through questionnaires distributed to 28 respondents. The collected data were processed using the Naive Bayes algorithm with the assistance of R Studio. The research process included data collection, preprocessing, model building, testing, and performance evaluation. The results show that the Naive Bayes model achieved a classification accuracy of 60%. These findings indicate that the method can help identify patterns related to declining student motivation. Therefore, the study is expected to support students, lecturers, and institutions in developing strategies to improve learning motivation.