ANALISIS SENTIMEN LAYANAN TRANSPORTASI ONLINE PADA TWITTER MENGGUNAKAN METODE K-NEAREST NEIGHBOR (K-NN)

The development of transportation will make it easier for human to do activities. The existence of online transportation make it easy for user to place an order. The more services provided online transportation make people it talk though social media. This research uses twitter as a data base. Tweets on twitter we will get two sentiment analyzes which are negative sentiment and positive sentiment. And the next step we do the classification. For the classification we use K-Nearest Neighbor (K-NN). From this we get 920 data with 640 negative sentiment and 280 positive sentiment. And for the final result classification is 81,52% for accuracy point and 0,878 for Area Under Curve (AUC)