ANALISIS SENTIMEN CYBERBULLYING DATA TWITTER MENGGUNAKAN METODE DECESION TREE CLASSIFIER C5.0

Decision Tree C5.0 is one of the classification algorithms used in classifying several cases. Decision Tree is a structure that resembles a tree (Tree). Where each internal node represents a test on an attribute, each branch represents the test result and a leaf node represents a class or class distribution. In this study, it was conducted to conduct a sentiment analysis using Tweet data about Cyberbullying, which is still common in the digital world. The classification method used in this study is to use the Decision tree C5.0 algorithm to process sentiment analysis in the hope of optimizing the performance generated in sentiment analysis. The results of the study using the Decision Tree C5.0 algorithm without applying Stopword removal with an accuracy of 63% on the use of 1000 data with 500 attributes and producing 63% Precision and 63% Recall. Meanwhile, by using Stopword removal using the same algorithm, the results obtained are 63% accuracy with 1000 data and 1500 attributes with lower precision results, namely 62% and Recall 62%. The results show that the use of a lot of data using the Decision Tree C5.0 algorithm without applying Stopword removal can produce a high accuracy value compared to using a lot of data by applying Stopword removal