<![CDATA[In this digital era, social media users are growing more rapidly and more mediasocial applications. One of the most widely used social media today is Twitter, with users reaching over hundreds of millions of people in the world. Twitter is a mobile or desktop application where users can create an article that can reflect their emotions through a short text form status with a maximum of 140 characters. With so many active users up to now then on every status created by Twitter users can reflect their emotions. It takes a pesikolog to see an emotion from the status of people in social media because there is no automatic system to determine one's emotions through its status on Twitter. The system in this research is made using Fuzzy C-Means (FCM) method. The FCM method can be used to generate rules that can replace the role of a psychologist to determine a person's emotions from a status he or she creates on Twitter's social media. The Term Frequency & Invers Document Frequency (TF-IDF) weighting method in text mining is used to process textual data into numerical data to be able to be processed by FCM. Based on the test results, this system produces an highest accuracy of 70% so it can be concluded that the FCM method is good used in the formation of a person's emotional determination of a status on social media Twitter.]]>
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