EXPERT SYSTEM TO DIAGNOSE COMPUTER VISION SYNDROME (CVS)”.

muhammad noval - noval, leni - novianti

Abstract

This study aims to provide comparative information to determine which method is more accurate, effective and efficient in diagnosing CVS from the symptoms described by an ophthalmologist or CVS. The methods used for comparison are the Forward Chaining Inference method and the Naive Bayes method, so that the final result of the comparison of these two methods is expected to be able to get the right solution for the symptoms of people with CVS disease. System design using the Unified Modeling Language (UML). The tools used to build are xampp (App Server), Visual Studio Code, the programming language used is php and the CodeIgniter framework. The application designed in this study is expected to facilitate the process of diagnosing computer vision syndrome (CVS).

Keywords

computer vision syndrome (CVS), Inferensi Forward Chaining dan metode Naive Bayes, Unified Modeling Language (UML).

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References

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DOI: https://doi.org/10.1593/jreec.v3i1.4247
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