<![CDATA[Digital public services often require account-based authentication that can create access barriers for citizens with limited digital literacy. In housing assistance services, such barriers may reduce the accessibility of systems intended to support vulnerable groups. This study aimed to develop and evaluate a low-barrier decision support system for housing assistance by integrating Guest Mode access with the Simple Additive Weighting (SAW) method. The study used a design-oriented development approach in collaboration with Dinas Perkim Minahasa. System requirements were identified through staff interviews, and the prototype was tested in the agency environment using real housing data. Validation was conducted by comparing system-generated SAW results with manual calculations performed by agency staff and by testing the main system functions operationally. The results showed that the system produced the same ranking results as the manual calculations in the tested cases, while staff evaluation indicated that the Guest Mode design simplified the submission process and reduced administrative barriers. This study contributes to inclusive e-government practice by proposing a citizen-centered, low-barrier architecture for housing assistance services that maintains decision support accuracy while improving service accessibility.]]>
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