This paper discusses the automatic matching of students applying for the Internship and Independent Study (MSIB) program with partner companies. Many companies offer MSIB programs. This makes it difficult for students to register according to their competence. For this reason, a system is needed that will help students recommend vacancies according to their competence. This research will build a MSIB recruitment recommendation system. The research will begin by building a database of activity details for apprentice and independent study program partners. Details of partner activities contain program descriptions, Developed Competencies and Participant Criteria. This data will be used to build a MSIB vacancy recommendation system. Matching is done by comparing the Company's needs with the portfolio. At the beginning of the research, notes will be made based on students who are accepted into the MSIB program. Next, build a matching system between the MSIB vacancies offered and the work portfolios made by students. This system is expected to help students to be accepted into the MSIB program. The model used is content-based recommendation system. A content-based recommendation system will provide a list of vacancies that best match the student portfolio. The content-based recommendation system will use the cosine similarity algorithm and K-Nearest Neighbor (K-NN).The output of this study is a recommendation model for recruiting apprenticeship programs and independent studies. It is hoped that this system will help students determine internship programs and independent studies that suit their portfolios
Copyrights © 2023