<p><em>The purpose of this research is to monitor the sentiments of a brand and classify it into positive</em><em>,</em><em>  negative or neutral</em><em> </em><em>sentiments</em><em>. The steps of research </em><em>have</em><em> started from collecting data, indexing, searching and weighting process</em><em>.</em><em> Data are collected by crawling data from social media, such as Facebook and Twitter.</em><em> </em><em>After collecting data, then weighting process is done with a fuzzy logic method, where the fuzzy set is determined based on the highest number of positive and negative words in a sentence. Weighting process is calculated from TF (Term Frequency) which is the number of words that sought in the document. From the results, TF can be used to find the fuzzy set value and the number of positive or negative sentiments in a document. Mamdani method used to calculate the value of the final sentiment. From the calculation results, it can be shown that the average of sentiment analysis is 63.15%.</em><em></em></p><p><strong><em> </em></strong><strong><em>Keywords:  </em></strong><em>Information, </em><em>Sentiment</em><em> analysis, brand, fuzzy logic, social media.</em></p><p> </p>