Analisis Sentimen Pada Twitter Mahasiswa Menggunakan Metode Backpropagation
In a learning environment, emotional factors influence student motivation. Students emotion have an important role in students' capability to learn. The tendency of the students emotion are not easily recognizable in a short time. Twitter is a popular micro blogging system especially for students. Students post tweet about activities, experiences, their feelings anywhere, anytime and in real time. Sentiment analysis on twitter produce content sentiment that represents the feelings and emotions of students. Sentiment analysis system was built using backpropagation method at the stage of classification. In this research backpropagation network and the classification results were tested using WEKA with multilayer perceptron classifier. The results of sentiment analysis with 30 student respondents are 33.33% tendency of positive emotions, neutral emotions tendency 53.33% and 13:33% negative motional tendencies. The results are used as reference in providing the appropriate treatment of the students during the process of learning.