<![CDATA[The administration of motor vehicle services at the Samsat Banjarnegara office still faces challenges in terms of efficiency and accuracy, particularly in the manual data entry process of the Vehicle Registration Certificate (STNK). These issues result in service queue delays of up to 25% per year and data entry errors at a similar rate. This study aims to design and implement the Samsat Pintar (Si SAPI) application, an Android-based system integrated with Optical Character Recognition (OCR) technology to automatically read and extract data from STNK documents. The system development method employed is the Waterfall model with a Research and Development (R&D) approach. The application was implemented using the Kotlin programming language in Android Studio, with Tesseract OCR as the main engine. Data were collected through observation, interviews, and literature study, while the system testing was conducted using the black box testing method.The testing results showed that all application features functioned as expected, with no system errors found during trials, and the application response time was relatively fast (±5 seconds). Furthermore, testing with 25 Samsat Banjarnegara staff members through questionnaires consisting of five evaluation indicators produced a total score of 549 out of a maximum score of 600, resulting in a satisfaction percentage of 91%. This indicates that the Si SAPI application was very well accepted by users and is proven to help accelerate and simplify the process of motor vehicle administration services.on the questionnaire evaluation with a Likert scale, the system received a user satisfaction percentage of 86.4%.]]>
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