Quality Function Deployment and Fuzzy TOPSIS Methods in Decision Support System for Internet Service Provider Selection

Internet Service Provider (ISP) is a company or business organization that provides access to intenet and services related for individual consumer or companies. There are many ISP in Indonesia recently, and they have almost the same product to offered. This problem makes internet service provider selection become a major issue. Decision support system can be used to recommend the best ISP company based on need. The aim of this research is to used Quality Function Deployment with Fuzzy TOPSIS sequentially to select the best ISP company as needed, and implemented in decision support system for internet service provider selection. Quality Function Deployment and Fuzzy TOPSIS methods used to evaluate, and then recommend the ISP company by ranked. Quality Function Deployment method used to find out customers requirements about internet network, the weighting of the criteria and the assessment of each ISP company. Fuzzy TOPSIS used to rank ISP company. These two methods produce consistent ratings when sensitivity analysis is performed for fuzzy and crisp value. These two methods make decision support system result can be trusted

Evaluation of e-learning web sites using fuzzy axiomatic design based approach

High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM