Comparison of CPU damage prediction accuracy between certainty factor and forward chaining techniques

CPU plays a vital role in determining the performance of a computer system in contemporary computing. If the CPU sustains damage, it may result in significant interruption to the computer's functioning. This study presents a computational technique that aims to enhance the accuracy of CPU damag...

Full description

Saved in:
Bibliographic Details
Main Authors: Tri Ginanjar Laksana, Ade Rahmat Iskandar, Wan Nooraishya Wan Ahmad
Format: Article
Language:en
Published: Jurnal_Pekommas 2024
Subjects:
Online Access:https://eprints.ums.edu.my/id/eprint/43552/1/FULL%20TEXT.pdf
https://eprints.ums.edu.my/id/eprint/43552/
https://doi.org/10.56873/jpkm.v9i1.5531
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:CPU plays a vital role in determining the performance of a computer system in contemporary computing. If the CPU sustains damage, it may result in significant interruption to the computer's functioning. This study presents a computational technique that aims to enhance the accuracy of CPU damage predictions. The system utilizes fundamental knowledge of damage diagnosis and is validated by evaluating 11 early damage symptoms that are often seen. The Certainty Factor and Forward Chaining approaches ascertain CPU damage by quantifying the degree of truth in the expert's opinion conclusions by comparing the harm symptoms. The second algorithm assesses the confidence level in a development by considering the value assigned to the system by two parties: the user and the expert. The suggested algorithm yields the mean accuracy of the certainty factor approach in diagnosing computer damage utilizing the constructed system. The diagnostic system has a precision rate of 84.9%, indicating that 9 out of 10 diagnoses made by the system align with those made by an expert. Next the outcomes of the Forward Chaining algorithm test. All questions about symptoms were answered affirmatively, except for one test which had a negative response. A total of 39 diagnoses were obtained, with an average value of 82.9%. The study findings indicate that the suggested Certainty Factor method is more suited for use in embedded systems or web-based applications, however it is constrained by low processing.