doi: 10.18178/ijmlc.2019.9.6.889
Development of Intelligent Decision Support System for Selection of Quality Tools and Techniques
M. D. Mohd Amran
,
A.W. Mohamad Ikbar ,
S. Khairanum ,
A. B. Fairul Anwar ,
B. Rahmat Roslan
- Quality Engineering Department, Universiti Kuala Lumpur, Malaysian Institute of Industrial Technology, Johor Bahru, Johor, Malaysia
- Manuscript receivedAugust 20, 2019
- revisedOctober 11, 2019
Abstract
This research derives systematic analysis and synthesize previous research published with aim to highlight and develop a decision aid for Quality Tools and Techniques (QTT) selection which enable practitioner make a rational and structured decision though development of Intelligent Decision Support System (IDSS). Vast numbers of QTT for problem-solving and improvement activities give a significant challenge to determine the suitable QTT. The chosen QTT affect the effectiveness of improvement activity and misused of QTT can slow down the improvement process and flawed the conclusion. The IDSS namely eCIFOD was produced by translating the QTT mapping into the SQL Union and SQL Inner Join. PHP scripts were developed to run the system and uploaded to online after the Black Box Testing show good result. A single case with a single unit of the case study research strategy was used to conduct the user acceptance testing unveil the positive feedback from the user in term of feasibility, usability, and utility. Development of empirical IDSS for selection of QTT through providing structured and intelligent decision making provides holistic decision support for practitioner to select most optimize QTT to be used for improvement purpose.
Keywords
- Intelligent Decision Support System (IDSS)
- Quality Tool and Technique (QTT)
- selection method
How to Cite
M. D. Mohd Amran, A.W. Mohamad Ikbar, S. Khairanum, A. B. Fairul Anwar, and B. Rahmat Roslan, "Development of Intelligent Decision Support System for Selection of Quality Tools and Techniques," International Journal of Machine Learning, vol. 9, no. 6, pp. 893-898, 2026. https://doi.org/10.18178/ijmlc.2019.9.6.889
Copyright & License
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).