<![CDATA[Computer networks play an important role in supporting information systems across sectors such as education, government, industry, and private organizations. The growing reliance on stable, reliable networks makes network disruptions a serious concern. Common issues such as internet disconnections, IP address conflicts, device failures to connect, and DNS errors often require a fast, accurate diagnosis. In practice, however, the handling of these problems is often limited by the number of available technicians and by users lack of technical understanding. This study aims to develop an expert system to automatically monitor and detect network faults. The system applies the Analytical Hierarchy Process (AHP) to assign weights to each symptom through pairwise comparisons, thereby prioritizing and yielding more relevant diagnostic results. The knowledge base was developed using secondary data from previous studies that utilized forward chaining. The system is implemented as a web-based application with a user-friendly interface. System evaluation was conducted using 50 network fault test cases, and the results showed that the proposed system achieved 92% accuracy, 91% precision, 90% recall, and an F1-score of 90.5% based on expert validation. In addition, the AHP consistency test produced a Consistency Ratio (CR) value of 0.08, indicating that the pairwise comparison matrix was logically consistent. These results demonstrate that the proposed system improves the efficiency and effectiveness of network fault diagnosis for both technical and non-technical users.]]>
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