<![CDATA[In the era of continuously developing information technology, website-based attendance systems have become an efficient and effective solution for managing employee attendance in various industries. This research proposes the development of a website-based attendance system using NodeMCU ESP32 and the K-Nearest Neighbors (KNN) algorithm to identify employee attendance patterns. The NodeMCU ESP32 acts as hardware that connects to the RFID sensor, sends data to the server via the Wi-Fi network, and communicates wirelessly with the web server via the HTTP protocol. The KNN algorithm will be implemented on the server side to process attendance data and classify attendance patterns based on existing history. This research aims to increase the efficiency and accuracy of the attendance system in managing employee attendance, with the hope of reducing the administration time required and increasing company productivity. It is hoped that the results of this research can become the basis for the development of a more sophisticated and adaptive attendance management system, utilizing the latest technology in the context of human resource management. Thus, the use of NodeMCU ESP32 and the KNN algorithm as part of a website-based attendance system opens up opportunities for more effective and efficient solutions in attendance management in the modern business environment.]]>
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