Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal International Journal of Engineering, Science and Information Technology
Abdullah, Azma
Unknown Affiliation
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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

Found 1 Documents
Search

 1 
Safety Function Model for Requirement Specification in Critical Systems: A Case Study of Generic Patient Controlled Analgesia Pump Model (CGPA) Abdullah, Azma; Abu Bakar, Rohani; Abdul Farid, Fairus; Abdulhak, Mansoor
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.1370

Abstract

Developing safety-critical systems (SCS) involves a systematic method for assuring and providing safety and dependability. Conventional approaches rely on expert intervention, which can introduce bias, cause delays, and promote inconsistency. This work proposes a model that enhances efficiency and accuracy by extracting safety functions from requirements specifications. The model is made up of three main steps: (1) preprocessing, which involves getting rid of stop words; (2) string selection and matching using a database of safety properties variables based on literature and expert knowledge; and (3) putting safety and non-safety functions into a structured safety function log. The model was trained and tested with the CGPA insulin pump and got a 94% F1 measure score, which means it was 91% accurate, 96% accurate, 92% precise, and 96% recall. This shows that it is good at making things clearer and less biased when finding functions for safety against failures, malfunctions, operational hazards, and inconsistencies in safety-critical specifications. All these enhancements contribute towards Sustainable Development Goal (SDG) 11: Sustainable Cities and Communities, aiming to develop safer, resilient, and sustainable infrastructure in safety-critical regions.
Co-Authors Abdul Farid, Fairus Abdulhak, Mansoor Abu Bakar, Rohani