Penerapan Jaringan Syaraf Tiruan Backpropagation Dalam Sistem Pakar Diagnosa Virus TORCH

Erwin Gunawan Walker, David David

Abstract


Virus TORCH is an acronym of the virus Toxoplasma, Rubella, Cytomegalo virus, and Herpes. TORCH virus causes many children born with disabilities. The purpose of this study is to generate and build an expert system software that can help the patient in making an early diagnosis of the TORCH virus, in order to reduce the risk of children born with disabilities caused by this virus. Method research design is a case study and interviews in finding out about the TORCH virus. This expert system making use of Visual Basic .NET in the making of the application. An expert system is paired with a forward chaining neural network Backpropagation as decision-making. This expert system featuring a large selection of symptoms that can be selected user, where each choice of symptoms will bring the user to the selection of the next symptom to get the final result. While the database used is MySQL. Design model used is UML (Unfield Modeling Language) and flowchart. Its design method is a prototype and testing software using black box testing systems have been built. The results of this study is to help the public to better understand and know TORCH suffered virus so that it can be treated promptly to avoid the children who are born with disabilities. Suggestions in the future is that this expert system can be online

Keywords


Expert System; Backpropagation; Forward Chaining; TORCH Virus

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References


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DOI: http://dx.doi.org/10.30700/jst.v10i1.947

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