Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar
Afdal, Rahmat
Unknown Affiliation
Other

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
PENGEMBANGAN SISTEM PAKAR UNTUK MENDETEKSI GEJALA KERUSAKAN PADA KOMPUTER LABOR SMK NEGERI 8 PADANG MENGGUNAKAN METODE FORWARD CHAINING Afdal, Rahmat; Ami Anggraini Samudra; Satrio Junaidi
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 01 (2026): Volume 11 No. 01, Maret 2026 Release
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i01.42815

Abstract

The rapid development of information technology requires increased use of computer devices in educational environments, particularly at SMK Negeri 8 Padang, which has a high intensity of computer laboratory use. However, the limited time available to technicians to diagnose computer malfunctions means that many devices are not used optimally. This study aims to develop a web-based expert system capable of detecting symptoms of computer malfunctions using the forward chaining method. This method works based on IF-THEN rules to draw conclusions from symptom data input by users. The system was developed using an iterative model approach within the SDLC framework and tested using the black box method and validated by experts and users. The results of the testing show that the system is feasible and effective to use, and is able to assist teachers, students, and technicians in accurately diagnosing damage. The evaluation results show that this system is capable of detecting computer damage according to its symptoms, accelerating the process of detecting computer damage, and increasing the accuracy and time efficiency of the computer damage checking process. The system has a validity rate of 84.17% and a practicality validity of 90.8%.
Co-Authors Samudra, Ami Anggraini Satrio Junaidi