Classification Of Sexually Transmitted Infectional Diseases Using Artificial Neural Networks
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Abstract
Many diseases are caused by bacteria, some of which can be easily noticed by ordinary people for immediate treatment. However, not with this one disease, namely sexually transmitted infections (STIs). This STI disease can be spread mainly through sexual intercourse, both vaginal, anal and oral sex. Some STI diseases can also be transmitted in non-sexual ways, such as through needles, blood or other blood products. Indonesia is one of the countries whose handling can be said to be not optimal as in several other countries. This is the result of a lack of education on STI diseases in the community. Based on this background, it can be concluded that there is a need for an intelligent system to classify STI diseases based on their symptoms. Therefore, the authors propose this research topic by applying the Artificial Neural Network method. Based on the test results, the application of the Artificial Neural Network method shows that 80% of the predicted data is in accordance with the actual data.
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