Smartphones are devices that have advantages over other communication tools. Damage to Smartphones is natural and normal, as well as damage to iPhones, examples of damage ranging from fast battery drain, no image on the screen, camera not working etc. However, technicians face obstacles when diagnosing iPhone defects, which results in less than optimal technician performance. This expert system uses the Dempster-Shafer method. Inferences are made based on the symptoms of existing iPhone damage, and the frequency of each symptom is determined by the Smartphone technician. From the calculation of the visible density of damage that occurs on the iPhone, the system has 20 symptoms of damage and 14 types of damage. The purpose of this study is to help technicians determine the damage that occurs on the iPhone, which will select symptoms and give the results of this study an accuracy score of 90%.
Copyrights © 2023