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Naïve Bayes is a prediction method that contains a simple probabilistic that is based on the application of the Bayes theorem (Bayes rule) with the assumption that the dependence is strong. K-Nearest Neighbor (K-NN) is a group of instance-based learning, K-NN is also a lazy learning technique by searching groups of k objects in training data that are closest (similar) to objects on new data or testing data. Classification is a technique in Data mining to form a model from a predetermined data set. Data mining techniques are the choices that can be overcome in solving this problem. The results of the two different classification algorithms result in the discovery of better and more efficient algorithms for future use. It is recommended to use different datasets to analyze comparisons of naïve bayes and K-NN algorithms. the writer formulates the problem so that the research becomes more directed. The formulation of the problem in this study is to find the value of accuracy in the Naïve Bayes and KNN algorithms in classifying data.

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The transmission of infectious disease in epidemiological models usually is based on the assumption that population within random-mixing. Although medical developments can reduce the consequences of the spread of infectious diseases, prevention of plague remains a major toehold. After a model is formulated containing the main fitur the development and transmission of infectious disease, onward to the model can be used to predict, making eradication strategies, control or prevent the spread. Modeling the spread of the disease has the potential to improve the quality of human life. The social life of humans far more complex exceed a diverse population. The transmission dynamics of infectious diseases is sensitive to patterns the interaction between the individual vulnerable (susceptible) and contracted (infectious). Human social contact very heterogeneous group. To predict the impact of this pattern against the transmission of infectious diseases, the use of epidemiological random network model, where the nodes serves individuals exposed, contracting or cured and connectedness presents contact transmission. Type the model spread (epidemic) that examined the model type is exposed, tetular exposed, and cured, or better known as a type of SIRS.