<![CDATA[Twitter is a social media that is most often used by internet users to exchange opinions on various topics, discuss news or current issues and even share personal life. Without realizing it, what happens when communicating using social media is indirect communication, so that other users who see or read only know from written tweets without knowing the user's expression. Knowing someone's question or statement on social media regarding POLRI requires pre-processing and analysis of tweets written by Twitter users discussing this matter. This study aims to analyze the level of public trust in POLRI using the Multiclass Support Vector Machine (SVM) method on Twitter social media by classifying tweets. The data used in this study are 4200 tweets which are divided into 80% training data, and 20% test data, from each of the 3 classes namely positive, negative and neutral. Based on the results of research and testing of the SVM method to classify the level of public trust in POLRI with Indonesian language tweets using TF-IDF feature extraction, it is concluded that the use of the SVM method has an accuracy value of 94.79, 95% precision, 95% recall and 95% precision. F1-Score which means good. in the study of the classification of the level of public trust in POLRI using Indonesian-language Tweets.]]>
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