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Maria Eve Angeline
Program Studi Teknik Informatika, Universitas Kristen Petra Surabaya

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Sistem Pakar untuk Mendiagnosa Kerusakan pada Sepeda Motor Kawasaki KLX 150 Menggunakan Metode Forward Chaining dan Certainty Factor Maria Eve Angeline; Djoni Haryadi Setiabudi; Kartika Gunadi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

The Kawasaki KLX 150 is an all-road or dual sport motorcycle, which means it can be used on the road or off-road. Nowadayas dirt bike riders are not just crossers, ordinary people are starting to like dirt bikes to be used as daily vehicles. Dirt bikes have engines and various kinds of devices or parts that can be damaged or be problematic. The damage that often occurs on a dirt bike is considered trivial and not understood. Therefore, an expert system was created that can detect damage to the Kawasaki KLX 150 motorcycle, with the hope that this research can help replace the role of mechanics to diagnose damage based on the symptoms experienced. The expert system to diagnose damage to the Kawasaki KLX 150 will use the Forward Chaining method and the Certainty Factor method. The use of forward chaining method in this expert system is to collect facts obtained from users so that the system will produce conclusions. The use of Certainty Factor in this study is to provide a level of confidence from the results of system diagnosis in the form of metrics. From this expert system, it can provide information about the name of the damage, how to handle it and the level of confidence in the diagnosis. Application testing for the diagnosis of damage to the Kawasaki KLX 150, using real data with experts, resulted in a system accuracy of 90%. The application for the diagnosis of damage to the Kawasaki KLX 150 is also considered complete, accurate, appropriate and easy to use (user friendly) by the user.