Approaching 3 years of leadership, the Governor of DKI Jakarta has always been under the spotlight due to his underperformance. Not only the citizens of Jakarta but the Indonesian people gave their views on the performance of the Governor of DKI Jakarta during his tenure. There were those who submitted complaints and at the same time provided input for Anies to lead in the future. People now
tend to be smarter and more critical in responding to this problem through social media, Twitter. They can immediately refer to the DKI Jakarta Governor's account on twitter if they want to provide criticism, suggestions or even complaints. Therefore, to find out the performance of the Governor of DKI Jakarta based on the public response on Twitter, it is easily obtained through this application by
utilizing the branch of text mining. This application is built using the Naive Bayes Classifier analysis method. The software development method used is the Waterfall method and application design using the Unified Modeling Language
(UML). The data instrument used for this sentiment is data from Twitter regarding the Governor of DKI Jakarta over the past year. This application was tested using the Black Box method trial. It is hoped that the results of this study indicate that the application of this analyst sentiment can help users to find out the performance of the Governor of DKI Jakarta which is more accurate and efficient.