01 / Context
Rental search was scattered and difficult to trust.
People looking for rentals in Butuan City often had to browse fragmented social posts, work with incomplete details, and judge listings without a consistent way to compare them.
NestSeeker began as a thesis project focused on making that process more structured, transparent, and useful for both renters and property owners.
02 / Approach
Translate a decision model into a usable product.
I led the product implementation, connecting the interface, backend services, authentication, and property data into a working MVP.
The core challenge was balancing the theory behind FBWM and TOPSIS ranking with an experience that still felt familiar to someone simply looking for a place to live.
- 01Verified property information and structured listing data
- 02Filtering around price, proximity, and preferred amenities
- 03Preference-based ranking to support—not replace—human decisions
03 / Outcome
A defended thesis and a foundation for further testing.
The project reached a functional MVP and was successfully defended in April 2025. It demonstrated how a locally grounded rental problem could be approached with both product design and decision-support methods.
The next meaningful step would be deeper testing with local renters and owners, followed by tighter verification and listing operations.