Search Results - "Rasmani, Khairul A."

Data-driven fuzzy rule generation and its application for student academic performance evaluation by Rasmani, Khairul A., Shen, Qiang

“…Several approaches using fuzzy techniques have been proposed to provide a practical method for evaluating student academic performance. However, these…”
Get full text

The potential of using fuzzy clustering in generating consumer profile by Jalaluddin, Aini Suria, Rasmani, Khairul A., Shahari, Nor Azni

“…A good consumer profile can be developed by forming a suitable group of criteria. However, the most common existing consumer profile was created based on…”
Get full text

Fuzzy delphi method: Issues and challenges by Saffie, N. Amira M., Shukor, Nur'Amirah Mohd, Rasmani, Khairul A.

“…The Fuzzy Delphi Method (FDM) is the modified and enhanced version of the classical Delphi technique. Improvement was made to rectify the imperfection of…”
Get full text

Job Satisfaction Evaluation Using Fuzzy Approach by Rasmani, K.A., Shahari, N.A.

“…Likert-type scale that employs ordinal values to represent linguistics terms has been very popular in the studies on job satisfaction evaluation. In this work,…”
Get full text

Subsethood-based Fuzzy Rule Models and their Application to Student Performance Classification by Rasmani, K.A., Shen, Q.

“…The focus of this paper is the use of fuzzy approaches to classify student academic performance, which so far has not been performed satisfactorily by existing…”
Get full text

Prediction of residential households' water leakage using consensus method by Ismail, N. F., Rasmani, K. A., Shahari, N., Rashid, N. R. M., Hanif, H. M., Noh, N. A. M.

“…Consensus method is a means of communication between experts who assist the formation of a group judgment. This technique has great potential to be adopted to…”
Get full text

Linguistic rulesets extracted from a quantifier-based fuzzy classification system by Rasmani, K.A., Garibaldi, J.M., Qiang Shen, Ellis, I.O.

“…The use of linguistic rulesets is considered one of the greatest advantages that fuzzy classification systems can offer compared to non-fuzzy classification…”
Get full text

Variability in Classification Outcomes Based on Fuzzy and Non-fuzzy Input Values: A Case Study by Rasmani, K.A., Shahari, N.A., Ali, R.

“…This paper presents a case study on the possibility of achieving similar classification outcomes when different types of input datasets were employed in…”
Get full text