Analisis Tingkat Kepuasan Mahasiswa dalam Kegiatan UKM di Stikom CKI Menggunakan Algoritma Naive Bayes

The main problem in increasing the level of student satisfaction in UKM activities at STIKOM CKI is caused by various factors, including the rare frequency of meetings and the multiplication of material without significant development. This dissatisfaction can reduce students' interest in actively participating in UKM activities, which should be a source of positive experiences and skills development. Well-managed SME activities can be an important means of developing soft skills such as leadership, team collaboration and communication skills. However, when these activities are not managed well, the results can be counterproductive, causing frustration and dissatisfaction among students. Based on these problems, an application of the Naive Bayes algorithm will be carried out to determine the satisfaction level of STIKOM CKI students with 80 training data and 6 test data. After calculating, an accuracy rate of 83.33%, recall of 33.33%, and precision are obtained. 100%. Therefore, it is important to manage student satisfaction levels to avoid being counterproductive. One of the appropriate data mining algorithms to solve the case above is to use the Naive Bayes algorithm.