Expert System for Automatic Weather Station Instrument Malfunction Diagnosis Using the Certainty Factor Method (BMKG Regional North Sumatra Case Study)
Keywords:
Expert system, Certainty Factor, Automatic Weather Station, Damage Diagnosis, BMKG.Abstract
Expert systems are one of the methods that can be used to assist in decision-making, particularly in diagnosing equipment malfunctions. This research aims to design an expert system that can diagnose damage to weather measuring instruments on the Automatic Weather Station (AWS) using the Certainty Factor (CF) method. A case study was conducted at the BMKG Regional Office of North Sumatra, which has various types of weather equipment that require routine maintenance and damage diagnosis. This expert system relies on the knowledge of experts to identify symptoms of damage and provide repair solutions based on the certainty level calculated using the Certainty Factor method. The CF method is used to determine the confidence level in the possible diagnosis provided by the expert system. The results of this study show that the developed expert system can help improve the efficiency in diagnosing weather measuring instrument malfunctions and provide accurate repair recommendations. Thus, it is expected that the use of this expert system can accelerate the maintenance and servicing process of weather measuring instruments at BMKG, as well as reduce errors in diagnosis made by technicians.
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