Abstract. Hoax news is fake news that contains information that intentionally misleads people and has a specific political agenda. Along with the development of technological developments, the news is increasingly unclear whether the truth is only in accordance with facts or mere hoaxes. Based on this problem, hoax news is carried out, one of which uses a machine that can process news classification automatically. Machine learning is implemented using a framework called the Flask framework that can run on both on-premises servers and cloud computing. Local servers with computational limitations that are static in nature have problems running large computations on the hoax news classification system framework which is characterized by a predictable time schedule so that a distributed automatic-scaling computing system can handle cloud computing loads. Cloud computing offers compute load-sharing automatic scalability that can provide stable compute computing. So this research focuses on the application of the machine learning hoax news classification model into the framework of the machine learning deployment Platform as a Service (PaaS) model in Cloud computing called Google App Engine (GAE). The application of the hoax news classification system in the Google App Engine environment runs with an average prediction time of 11.53 seconds, better and more stable than the local server's average prediction of 17.50 seconds.