Expert Systems: Web-Based Motorcycle Detection Solutions

Dewi Amelia Lestari, Wahyu Wijaya Widiyanto

Abstract

Motorcycles are one of the main means of transportation for some people in carrying out their daily activities. Efficient, cost-effective time to the destination, as well as maintenance tools that are quite easy to obtain, make this motorcycle a priority among the community, and this is evidenced by the number of motorcycle users compared to other means of transportation on the road. From the description above, the author makes a system that can make it easier for users to find out problems that occur in the motor, which cause damage so that it can interfere with the activities to be carried out. The system that will be made is an expert system for detecting web-based motorcycle damage. This expert system is made using the BFS method, which is a combination of the two methods so as to produce the best decision from the two searches. The Best First Search method is a merger or combination of the Depth First Search and Breadth First Search methods. Depth First Search method or in-depth search, in this method the expert system will conduct an intensive and in-depth search of the given value or variable. And the Breadth First Search method works by analyzing each root node for immediate testing. From these results it can be concluded that the system is feasible to use and can be used as an alternative solution for the community. Make it easy for motorcycle users to find solutions for motorcycle damage, and make it easier for mechanics to repair motorcycles if they forget the symptoms of motorcycle damage experienced.

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