Today, the diagnosis of diseases is a vital and intricate job in medicine. Medical diagnosis is regarded as an important yet complicated task that needs to be executed accurately and efficiently. Regrettably all doctors do not possess expertise in every sub specialty and moreover there is a shortage of resource persons at certain places. In this situation, an automatic medical diagnosis system is beneficial by bringing all of them together. For this diagnosis system, many classifiers are essential and needed for disease classification. So, this system is proposed as the performance comparison system about classifiers to know which classifier is more effective than other. To compare the performance, this system classifies the heart disease dataset by using K-nearest neighbor(KNN) and naive bayesian (NB) classifiers.