<![CDATA[The high density of population in Jakarta increases mobility and community activity, causing various problems such as housing, garbage, traffic congestion and the lack of public facilities that make urban areas more and more dense. Various efforts have been made by the DKI Jakarta City Government to reduce congestion and air pollution, one of which will implement the Electronic Road Pricing system. (ERP). This leads to the pros and cons of the general public, especially on social media. Therefore, appropriate techniques are required to evaluate such opinions, so that the opinions are automatically classified into positive and negative categories. To do this, an analysis of the opinion about the ERP treatment in the Jakarta Capital Street using the Support Vector Machine algorithm was carried out. (SVM). The aim of this study is to be able to help governments in the decision-making process in ERP-related policy-making by knowing the level of public opinion, which can be seen from the sample of Twitter comment data as well as know the degree of accuracy, recall, and precision and display the emotional classification of tweets obtained. This phase begins with crawling 1000 Indonesian-language tweet data, pre-processing, labelling, implementation, validation and evaluation. Based on this study, it was concluded that the SVM algorithm had good accuracy results with a value of 87.63%, recall 98.32% and precision of 81.10%.]]>
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