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Design and implementation of a website quality system with fuzzy neural network
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Abstract Internet has become ubiquitous and organizations have moved from having their information only in physical files to having them online via their websites. Over the years, different websites‘ evaluation tools have been developed to assist web administrators with the maintenance of their websites. Before a proper website assessment can be done with these evaluation tools, the web administrator would have to access many of these evaluation tools from different locations. Reasons have been that different tools were developed to measure different parameters that contribute to having a good quality website. Later, Fuzz-web was developed to capture more parameters but with a limitation of the system having to depend on some of these evaluation tools for inputs, meaning unavailability of these tools will lead to the failure of fuzz-web. To overcome these problems, this research establishes a Fuzzy-Based Website Quality Assurance System using fuzzy logic principles and Java programming language to develop the system. The result of the developed system is the detection of broken links, slow loading pages, Hypertext Transfer Protocol related errors in websites, and the overall quality status of the website. The developed system eradicates the dependence on external evaluation tools and with the information provided, allows web administrators to be proactive in amending errors