An Expert System for Laptop Fault Diagnostic Assistance - Wee Jern, Samuel Tan; Samsudin, Noor Azah; Aswad, Firas Mohammed; Khalaf, Bashar Ahmed (Journal of Soft Computing and Data Mining, 2021)
Laptop has always been a very useful tool for studies and most university students own at least one laptop. However, not all university student knows how to diagnose and troubleshoot their laptop when it is not working right. Most university student would rather hire computer technician to fix their laptop even though the solution to their laptop problem is rather simple. As cost of living increases every year, so does the cost of hiring a computer technician. Therefore, an expert system for laptop fault diagnostics was proposed to be developed. The objective of this study is to develop an expert system capable of diagnosing the cause of a laptop problem by analyzing user’s answers to the questions displayed by the system. The proposed system would also provide easy to follow solution to the user on how to solve the problem. The methodological approach to developing this system is by following waterfall model. There are five phases in a waterfall model, however only four phases will be executed namely requirement, design, implementation, testing phase. By using this system, user can easily identify possible root causes to their laptop problem by answering few questions related to their laptop problem. On top of that, the expert system will provide appropriate recommendation to the diagnosed laptop problem. Using this system, the time required to diagnose a computer as compared to manual diagnosis will reduce drastically. Most process in manual diagnosis will be automated and handled by the expert system. Lastly, user can save up unnecessary expenditure used to hire a computer technician.