<![CDATA[This study evaluates the policy implementation of the face recognition system at Surabaya Gubeng Station as a digital innovation in public service by PT Kereta Api Indonesia (Persero). Using a qualitative approach and the policy evaluation model by William N. Dunn, the study assesses six key indicators: effectiveness, efficiency, adequacy, responsiveness, accuracy, and equity. The findings indicate that the system is effective in accelerating the boarding process, reducing queues, and improving passenger convenience. Efficiency is achieved through reduced staff workload and automated identity verification. However, several challenges remain, including technical disruptions, data input errors, and low digital literacy among users. Personal data protection is also a concern as most users are not fully aware of how their biometric data is managed. Therefore an adaptive governance strategy is needed, involving infrastructure improvement, staff training, public education, and greater transparency in data policy. With these measures, the face recognition system can serve not only as a tool for technical efficiency but also as a form of inclusive and sustainable public service transformation.]]>
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