Industry Recommendation for Undergraduate Internship using Decision Tree

The process of matching student profiles to industry profiles is critical to ensuring that students are placed in industries that are a good fit for their program. Therefore, to solve this problem, a system is presented that will give suggestions on suitable industrial types and internship placement from companies in the suggested industry for undergraduate students. This project maps student profiles from seven computer science programs and seven industrial types. There are 284 sample profiles collected from undergraduate students of Universiti Teknologi MARA. The profiles are gathered from previous records of placement for internship training. A decision tree model is constructed based on the sample profiles. The student’s Cumulative Grade Point Average (CGPA) and registered program are used as the main feature of industry recommendation. As a result, a web-based system for mapping students’ profiles to industries’ profiles has been developed. The application stores students’ and industries’ profiles and recommends suitable industries for each student’s profile.