Track: Modeling and Simulation

Abstract

Herpes is a type of skin disease characterized by unilateral radicular pain and the appearance of vesicular lesions limited to the skin area. This c4.5 algorithm method is included in the decision tree algorithm to build computational models to predict accurately. According to statistical research ever released by the World Health Organization, one in six people has herpes. Estimates from this study show that about 67% of people worldwide have the herpes virus. Estimates from this study show that about 67% of people worldwide have the herpes virus. Prediction and early detection to reduce the risk of exposure to other people so that medical action can be taken for healing. This prediction is carried out using the Decision tree c4.5 method. This research predicts herpes using eight variables, namely Chlamydia, sugar, alcohol, hepatitis, pregnancy, HIV, Ethylparaben, and Butylparaben. Based on the test results, it was found that the resulting model used the decision tree method, which was 90%. We also recommend using other ways to increase or as a comparison of.

Keywords

Prediction, Herpes, C4.5, Decision Tree, Algorithm.