To reduce the crowds during the COVID-19 pandemic, the Bogor City Government implemented an odd-even system for all vehicles in the city of Bogor at the end of the operation. Since the implementation of this policy, many opinions have been conveyed through social media. An analysis is needed to find out how effective the policy is based on public opinion. For this reason, an analysis of the sentiment application of the odd-even system for vehicles in the city of Bogor was carried out during the pandemic. The purpose of this study is to determine the accuracy, recall, and precision and calculate the amount of emotion obtained from sentiment analysis by using several algorithms for the application and application of selection features that can provide sentiment information related to the effectiveness of the software system in Bogor City. The research stages started from the selection of data, pre-processing, implementation, validation, and evaluation. Based on this research, it can be found that the Support Vector Machine algorithm with the application of Particle Swarm Optimization shows the results of the greatest assessment on the system sentiment analysis test in the city of Bogor during the pandemic with a value of 73.07%. In total, the sentiment of implementing the odd-even system to declare in Bogor City shows an expression of the joy of 45.45%.