ANALYSIS OF MODIFIED K-MEANS CLUSTERING IN DECISION SUPPORT OF INDUSTRIAL PARTNER GROUPING - Billy Sabella; Veri Julianto; Ahmad Rusadi Arrahimi (KLIK- KUMPULAN JURNAL ILMU KOMPUTER, 2022)
Internship is part of achieving the competencies expected in the educational process. Therefore, the suitability of students to companies that serve as a place for street vendors is something important to pay attention to. Weaknesses in the previous system, there are still many students who are not right in choosing companies/agencies. They are still not paying attention to the competencies expected in this internship process. This study aims to help group industrial partners according to the competency achievements of each department. The method used in this research is Modified K-Means Clustering in the grouping process. While the criteria used are the suitability of the company's field with the department, credibility, company ecosystem, company track record in the field of education, and the facilities provided. In carrying out this work, a system will be developed to process the data resulting from the questionnaire so that groups from each company are obtained. The results of the study were obtained from 86 respondents who were apprentices who had been in 37 companies or agencies. 22 questions that build 7 criteria resulted in 4 stable clusters after 8 iterations.Keywords: internship, decision support system, Modified K-Means Clustering.