Open AccessNovelty Ranking Approach with Z-Score and Fuzzy Multi- Attribute Decision Making Combination
Author(s) -
Basri Basri,
Syarli
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.7.27363
Subject(s) - ranking (information retrieval) , weighting , analytic hierarchy process , score , data mining , computer science , novelty , rank (graph theory) , artificial intelligence , fuzzy logic , product (mathematics) , machine learning , statistics , mathematics , operations research , medicine , philosophy , geometry , theology , combinatorics , radiology
This study aims to recommend a new approach in the ranking system by analyzing the combination of the Z-Score method and the Fuzzy Multi-Attribute Decision Making (FMADM) method. This fusion is based on the merging of the advantages of Z-Score and FMADM as a superiority method in statistical rank data processing with weighting data distribution. The lack of Z-Score in processing multi-attributes weighted data can be improved by the FMADM method. In this study, the integration of the Analytical Hierarchy Process (AHP) and Weighted Product (WP) methods was used as the FMADM method with the Z-Score statistical technique. The results of the analysis in the case study show that the integration of the Z-Score and AHP-Weighted Product (Z-WeP) methods can provide maximum results with similarities to the Z-Score results by 86%. Analysis of criterion values on alternatives also shows that Z-WeP can work better than some other of FMADM approaches.