This study aims to develop the Mentorku application as a learning support tool for students through a mentor recommendation system based on expertise. The recommendation system uses a Content-Based Filtering (CBF) approach with TF-IDF and Cosine Similarity algorithms to match user needs with mentor profiles. The application development process follows the agile method using the Scrum framework, which includes the stages of Product Backlog, Sprint Planning, Sprint Execution, Sprint Review, and Sprint Retrospective. This application provides key features such as mentor search, live mentoring sessions, private discussions, chat, and one-on-one mentoring. Beta testing results show that 79% of respondents stated that the application is usable and capable of providing relevant recommendations according to learning needs. These findings indicate that the Mentorku application is effective in helping to overcome unstructured learning problems through direct interaction with mentors.
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