Identifikasi Gejala Kerusakan Motor Matic Tipe Lexi Merk Yamaha dengan Menggunakan Metode Forward Chaining

Abstract

The Motorcycle Industry Association (AISI) announced that automatic motorcycle sales data has increased. The high use of automatic motorbikes at this time is not accompanied by the ability to repair damage to motorbikes by users. due to lack of information on how to maintain motorbikes, negligence in monthly service, and delaying repairs that should have been done but were postponed until they were seriously damaged. The expert system is an alternative to help mechanics and motorbike users to consult early symptoms of motor damage. Developing the Expert System application provides an overview of motor matic damage. The data comes from interviews with mechanics and data on the types of problems given by experts. After data collection, analysis and problem solving were carried out using the Forward Chaining method with the preparation of rules or rules. The results of the rule formulation are implemented into a system that aims to determine the extent to which the PHP programming language is applied in identifying damage to motorbike matic lexi. Followed by testing the results so that the results of the process carried out with the help of the application match the results of the process carried out manually. The results of the application are that it can provide early symptom clues to the lexi matic motor damage. The application of the Forward Chaining method is applied to systems that have an accuracy level of up to 80%, therefore the system can be said to be good enough to be implemented.