RANCANG BANGUN SISTEM INFORMASI ALUMNI DENGAN REKOMENDASI LOWONGAN KERJA BERBASIS WEBSITE MENGGUNAKAN METODE CONTENT-BASED FILTERING (Studi Kasus: STMIK AMIKOM Surakarta)

Alumni services at STMIK AMIKOM Surakarta still rely on documents, Microsoft Excel, and WhatsApp, so alumni data updates and post-graduation information delivery are not centralized. An initial survey of 49 alumni showed that job vacancy information was the most needed service (67.9%). This study aims to design and develop a web-based Alumni Service Information System equipped with job vacancy recommendations using the Content-Based Filtering method. A mixed-method approach was used, with data collected through observation, interviews, literature review, and questionnaires, and the existing services analyzed using PIECES. The system was developed using Rapid Application Development with Next.js and Supabase, while job vacancy data were collected through web scraping. Recommendations are generated by constructing alumni profile and job vacancy documents, text preprocessing, TF-IDF weighting, Cosine Similarity calculation, and ranking. Black-box testing of 58 scenarios produced 58 valid results (100%), and System Usability Scale testing yielded scores of 82.50 for administrators and 81.30 for alumni, indicating good usability. The system supports integrated alumni services and ranks job vacancies according to their similarity to alumni profiles.
Keywords: Alumni Information System, Job Vacancy Recommendation, Content-Based Filtering, TF-IDF, Cosine Similarity