<![CDATA[Identity (ID) card forgery remains a significant issue in Indonesia, often leading to crimes such as identity theft and fraud. To address this challenge, this study proposes the development of an identity authentication system that integrates near field communication (NFC) and facial recognition based on K-nearest neighbors (KNN) algorithm. The primary objective of this system is to enhance the security of ID card (KTP) data and to ensure efficient and accurate access to services requiring identity verification. The system stores facial data and ID card information securely in Firebase, which serves both as a user authentication platform and a secure cloud-based storage solution. The application, developed using Flutter, incorporates facial recognition for biometric verification, while NFC is employed as an additional authentication layer to provide dual-factor verification and reinforce identity security. Experimental results demonstrate that the facial recognition based on KKN achieved an accuracy rate of 100% with a false acceptance rate (FAR) of 0%, indicating a highly reliable performance. These findings confirm that the integration of facial recognition and NFC technologies offers a robust and effective solution to combat ID card forgery, thereby improving the overall reliability and security of the population data authentication system in Indonesia.]]>
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