Article’s

Selecting a compatible roommate is a critical factor in enhancing students’ accommodation experience and overall well-being. However, most existing roommate-finding platforms primarily emphasize accommodation availability, rental cost, and location while providing limited support for evaluating lifestyle compatibility. This paper presents VIBE ROOMMATE, a compatibility-based roommate matching platform designed for college students. The proposed system employs a weighted score-based compatibility algorithm that evaluates users across ten lifestyle attributes, including sleep schedule, cleanliness, study habits, social behaviour, food preference, and budget, to generate transparent and explainable roommate recommendations. The platform is developed using the MERN technology stack and integrates JWT-based authentication, bcrypt password encryption, MongoDB Atlas, Cloudinary, and Socket.IO to provide secure profile management, accommodation listing, cloud-based storage, and real-time communication within a unified web application. A functional prototype involving ten test users successfully validated the integration of the proposed modules and demonstrated the technical feasibility of the platform. The proposed solution provides a secure, scalable, and user-centric foundation for compatibility-driven roommate matching and supports future integration of AI-based recommendation techniques.