<![CDATA[Asset management in educational laboratory environments is often conducted manually, making it vulnerable to recording errors, delayed information, and equipment loss. These limitations necessitate the development of a system capable of capturing asset activities automatically, accurately, and in real time. This study aims to develop and evaluate the performance of a Smart IoT Asset Management System integrating Radio Frequency Identification (RFID), the NodeMCU ESP8266 microcontroller, and Google Sheets as an efficient and economical inventory solution for educational laboratories. This research adopts a system engineering approach with a descriptive–experimental design following the Network Development Life Cycle (NDLC) model. All 26 units of laboratory equipment were included as samples, and 10 respondents participated in the user evaluation. Data were collected through observation, semi-structured interviews, functional device testing, and user questionnaires. The analysis focused on RFID reading accuracy, system response time, data synchronization performance, and user perceptions. The results indicate a 100% RFID reading accuracy rate and a data synchronization time ranging from 7 to 10 seconds. The system successfully recorded all borrowing and returning activities without synchronization failures. User evaluation yielded an average satisfaction score of 4.8 out of 5, reflecting the system’s usability and practical benefits. This study provides important implications for laboratory digitalization, offering a low-cost, easily replicable, and IoT-based inventory solution suitable for educational institutions seeking modern asset management practices.]]>
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