Abstract

 Damage to the motor occurs due to negligence in carrying out maintenance. Currently, the process of checking motorcycle damage in a workshop generally still uses manual methods in analyzing motorcycle damage. This results in inefficient and time-consuming motor checking. The purpose of this study was to design and build an expert system to detect such damage using the Naïve Bayes algorithm method. It is hoped that with the expert system, the checking time will be more efficient. An expert system is a computer program created to solve a problem in a particular field based on knowledge, facts and reasoning techniques from an expert in solving problems. The method of data collection carried out includes interviews with mechanics, so that reliable data can be obtained. The symptoms used in motor damage detection are eroded pulleg nut (G13), eroded V-belt (G15), eroded gear (G16). So that two damages were identified, namely damage to the CVT engine (K3) and the basic clutch (K5). Based on the percentage results of each damage, namely K3 of 83.33% and K5 of 16.66%. So it can be concluded the probability of damage that occurs, namely damage to the CVT engine (K3).
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