WEBSITE RANKING ESTIMATION THROUGH FUZZY LOGICAL HIERARCHY PROCESS

  • Rodrick Symon Katete Texila American University Zambia
  • Rajamuthu Rajendran Texila American University Zambia
  • Ravi sankar VIT University, Department of Mathematics
  • Given Kalonga Texila American University Zambia
Keywords: Fuzzy Analytical Hierarchy Processes (FAHP), Multi Criteria Decision Making (MCDM), Fuzzy Numbers.

Abstract

The purpose of this paper is to provide case study on website evaluation and ranking by fuzzy analytic hierarchy process (FAHP). Many people have misconception about website evaluation and ranking mistaking good design and user interface alone as high ranking. To measure the website quality, various factors are taken into consideration. The quality metrics that are considered for evaluating website are accessibility, performance, usability, search engine optimization (SEO), website visibility, security, technology and design used for developing website. Analytic hierarchy process (AHP) breaks down complexity into simple hierarchical decision making methods. Fuzzy AHP is a multi-purpose judgement technique which is often used to guide website creation and can further be used to find out website ranking. This approach tells the ranking of website based on multiple conflicting criteria of the website. But all these parameters and metrics considered are qualitative and not measurable which is slight challenging to deal with traditional theory. The drawbacks of AHP is eliminated by use of FAHP. Here, fuzzy decision matrix is constructed by using multi-criteria decision making (MCDM) approach and final weight is calculated of each website based on their qualities.

References

Aikhuele, D.O., Souleman, F.S., and Amir, A. 2014. Application of Fuzzy AHP for Ranking Critical Success Factors for the Successful Implementation of Lean Production Technique. Australian Journal of Basic and Applied Sciences, 8 (18), 399-407.

Bard, J. F. and Sousk, S. F. 1990. A Trade Analysis for Rough Terrain Cargo Handlers Using The AHP: An Example of Group Decision Making. IEEE Transactions on Engineering Management, 37 (3), 222-228.

Bevilacqua, M., D’Amore, A. and Polonara, F. 2004. A Multi-Criteria Decision Approach to Choosing The Optimal Blanching-Freezing System. Journal of Food Engineering, 63, 253-263.

Boender, C. G. E., De Graan, J. G. and Lootsma, F. A. 1989. Multi criteria Decision Analysis with Fuzzy Pairwise Comparisons. Fuzzy Sets and Systems, 29, 133-143.

Bouyssou, D., Marchant, T., Pirlot, M., Perny, P., Tsoukias, A. and Vincke, P. 2000. Evaluation Decision Models. A Critical Perspective, Kluwer, Boston.

Bozbura, F. T., Ahmet, B. and Cengiz, K. 2007. Prioritization of human capital measurement indicators using fuzzy AHP. Expert Systems with Applications, 32(4), 1100-1112.

Chen, S. J. and Hwang, C. L. 1992. Fuzzy Multiple Attribute Decision Making: Methods And Applications. Springer-Verlag, New York, Inc. Secaucus, NJ, USA.

Ho, W. 2008. Integrated analytic hierarchy process and its applications–A literature review. European Journal of operational research, 186(1), 211-228.

Kong, F. and Hongyan, L. 2005. Applying fuzzy analytic hierarchy process to evaluate success factors of e-commerce. International Journal of Information and Systems Sciences, 13(4), 406-412.

Pakkar, M. S. 2014. Using DEA and AHP for Ratio Analysis. American Journal of Operations Research, 4, 268-279.

Ribeiro, R. A. (1996). Fuzzy Multiple Criterion Decision Making: A Review and New Preference Elicitation Techniques. Fuzzy Sets and Systems, 78, 155-181.

Saaty, T. L. 1980. The Analytical Hierarchy Process, McGraw Hill, New York.

Saaty, T. L. 1994. Fundamentals of Decision Making and Priority Theory with The Analytical Hierarchy Process. RWS Publications, Pittsburgh.

Saaty, T. L. 2001. Decision Making with Dependence and Feedback: Analytic Network Process, RWS Publications, Pittsburgh.

Zadeh, L. A.1965. Fuzzy sets. Information Control, 8(3), 338–353.

Zadeh, L. A. 1975. The concept of a linguistic variable and its application to approximate reasoning (Part II). Information Science, 8:301–357.

Published
2020-06-23
Section
Articles