<p>IoT-enabled biometric attendance systems are increasingly used to securely record attendance in organizational environments. However, ensuring the authenticity and immutability of attendance data while maintaining computational efficiency remains a challenge for resource-constrained IoT devices. This. paper proposes a lightweight blockchain-based fingerprint attendance framework that employs MD5 hashing for integrity verification within a private institutional environment. Although SHA- 256 offers stronger cryptographic security, its higher computational cost and 256-bit output increase latency and energy consumption, making it less suitable for embedded IoT processors. In contrast, MD5 provides faster execution and reduced cycle counts while ensuring tamper-evident record linking through blockchain storage. Experimental analysis compares MD5 and SHA-256 across metrics such as execution time, cycle count, and hash-chain consistency, demonstrating that MD5 achieves a 40% reduction in computation time under identical test conditions. The proposed design thus balances efficiency and verifiable integrity for scalable and energy-efficient biometric attendance management systems in closed-loop IoT environments.</p>