Implementasi Sistem Rekomendasi Hybrid untuk Penentuan Reviewer dan Rekomendasi Anggota Tim Peneliti - Fify Mustika Wondal; Graciella Eunike Bawiling; Anritsu Steven Christian Polii; Robby Tangkudung (Forum Kerjasama Pendidikan Tinggi (FKPT), 2026)
The Center for Research and Community Service (P3M) of Manado State Polytechnic manages a growing volume of research activities. Consequently, a digital transformation in administrative governance is required to ensure temporal efficiency, precise expertise mapping, and compliance with administrative regulations. Beyond objective reviewer assignments, researchers needs a support platform to identify cross-disciplinary collaborators based on publication track records. This study aims to implement a Hybrid Recommender System as an automated solution for reviewer selection and research team formation. The system integrates Content-Based Filtering (TF-IDF and Cosine Similarity algorithms) for text analysis with Constraint-Based Filtering for automated business rule validation. The research methodology follows a Research and Development (R&D) approach using a modified Waterfall model. The processed dataset comprises 516 research titles and profiles of 317 lecturers with SINTA IDs. Black Box testing results confirm the system's effectiveness in validating academic degree qualifications, SINTA score thresholds, and the transparent prevention of conflicts of interest. A comparative evaluation of 44 actual assignment cases demonstrates that the system provides highly relevant recommendations, achieving an accuracy rate of 79.5% compared to manual expert decisions. This research contributes a Microservice-based backend infrastructure that accelerates research coordination while strengthening the transparency and accountability of institutional research management.