Autism Spectrum Disorder (ASD) is abrain evelopment disorder that affects the ability to communicate and interact socially. There have been many studies using machine learning methods to classify autism including support
vector machines, decision trees, naïve Bayes, random forests, logistic regression, K-nearest Neighbors and others. In this study provides a review on autism spectrum disorder by using a machine learning algorithm that is supervised learning. The initial study of the article was collected from a website provided articles were in according with this study, after going through
the process of selecting articles 11 articles were eligible in this
study. Based on the results obtained, that the most widely used
algorithm in the literature study in this study is support vector
machine (SVM) of 63.63%, with the application of machine
learning in the case of ASD expected to be able to accelerate and
improve accuracy in determining a diagnosis