Local Area Networks (LANs) play a crucial role in supporting learning activities at SMK Negeri 6 Padang, but they often experience disruptions due to hardware failures, configuration errors, and external factors. To address these issues, this study designed a web-based expert system using the backward chaining method to accelerate and improve the accuracy of the fault diagnosis process. The system was developed using the waterfall SDLC model, supported by the Laravel framework, Bootstrap, and the MySQL database. Testing was conducted through black-box testing and feasibility assessments by experts and users. The results showed that the system was able to detect various LAN faults with a validity rate of 97.78% and a practicality rate of 96.11%. Therefore, this expert system can be used as an effective tool to assist technicians and students in network troubleshooting.
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