Penerapan Teknik Clustering Data Mining untuk Memprediksi Kesesuaian Jurusan Siswa (Studi Kasus SMA PGRI 1 Subang) - Tubagus Riko Rivanthio; Mardhiya Ramdhani; Ahmad Sahi (LPPM, 2020)
SMA PGRI 1 Subang is a private school that has several missions, one of which is the establishment of academic and non-academic achievements. In an effort to achieve the mission must supervise student achievement. The effort he did was to provide understanding in the selection of majors in accordance with the interests and talents of students. But in the activity of providing understanding, the school does not yet have a model that can evaluate the interests and talents of students to choose majors. The model can be obtained using student data processing. Data processing can be done using data mining, namely data mining clustering techniques. The technique will produce a model in the selection of majors. This clustering process is the process of grouping similar data based on the similarity of data held by students. The research method used is the CRISP-DM method which has 6 stages consisting of: Business Understanding, Data Understanding, Data Processing, Modeling, Evaluation, and Dissemination. The data that is processed is 620 data consisting of class of students in 2014, 2015, 2016. The results of processing using clustering obtained 6 clusters that have different models for each cluster. The results of this study can be used by schools in recommending courses chosen by students according to students' interests and talents, so students can learn optimally.Key words: clustering, dataMining, suitability, majors, students