The Use of the K-Means Algorithm as a Method for Grouping Major Interests of Class X Students of SMK Satrya Budi 1 Commerce
DOI:
https://doi.org/10.35870/ijmsit.v6i1.6902Keywords:
K-Means Algorithm, Data Mining, Data Clustering, Major Interests, Vocational High School StudentsAbstract
In the modern era like today, education is one of the most important aspects in supporting the development of quality human resources. In addition, through the main discussion carried out in this study aims to be able to apply the K-Means algorithm as a method for grouping the interests of class X students of SMK Satrya Budi 1 Perdagangan systematically and based on data. In addition, to be able to determine the level of compatibility between student interests and available majors based on the results of the grouping using the K-Means algorithm. And in addition, for the Research Method section used in this study, namely a quantitative approach with the support of data analysis techniques using the K-Means Algorithm Method. The selection of this method is based on the need for research to be able to produce objective grouping of class 10 student majors based on numerical data and certain relevant attributes. So based on this, this study shows the results that the application of the k-means clustering algorithm is able to provide a more objective and systematic approach in the process of determining majors. Grouping is done by processing several assessment criteria such as academic grades, aptitude tests, interest tests, entrance exams and basic skills. Based on the final results of the grouping of 30 students, the system divides students into four main major groups, namely Motorcycle Engineering and Business (8 students), Automotive Light Vehicle Engineering (2 students), Heavy Equipment Engineering (11 students) and Industrial Chemistry (10 students).
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