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This paper aims to predict outpatient visits from both the general category and BPJS based on the Naïve and the Exponential Smoothing method, which these two methods are compared to obtain the best method in predicting outpatient visits at XYZ hospitals.The data that is processed in this paper is based solely on the annual data collection over a period of 5 years from 2014-2018 which consists of 2 categories, namely general visit data and BPJS visit data, for the annual general category data has the following data amounts: 2014 = 11028, 2015 = 12950, 2016 = 17587, 2017 = 21951 and 2018 = 19049. As for the BPJS visit data, the data as follows 2014 = 16869, 2015 = 14059, 2016 = 14217, 2017 = 13019 and 2018 = 9641. Results of predictions number of outpatient visits from naïve method on the visit data which is categorized as general has MSE 5191788 and MAPE values of 16.335%, then the categorized BPJS has a value of MSE 13165490 and MAPE 19.081%. While the Exponential Smoothing method on the visit data that is categorized as general has MSE 7790587 and MAPE values of 21.808%, which categorizes BPJS as having MSE 13165490 and MAPE values of 20.718%. Of the two methods, the method considered better is the naïve method which has a percentage of MAPE values <20%