Anggraini, Mila2021-12-272021-12-272021-06wahyu sari yenihttps://repository.unri.ac.id/handle/123456789/10358The level of public health welfare in a country can determine the quality and circumstances of the country. The purpose of this study is to classify the level of public health welfare of Pekanbaru City in 2019. The study used C4.5 and Naïve Bayes algorithms with k-fold cross validation to predict the accuracy of classification and performance evaluation measure as evaluation of both models. Performance evaluation measure results with k-fold cross validation show that models with Naïve Bayes have better classification results than C4.5 algorithm models. This is because Naïve Bayes' accuracy, precision, sensitivity and specificity are greater than the C4.5 algorithm by 100%. This is also because Naïve Bayes obtained the result from the probability value of each attribute being free of each other.enalgorithm, Naïve Bayesk-fold cross validationperformance evaluation measurehealth wellbeing levelArticle