@thesis{thesis,
		author={Kusuma  Dine Tiara and Sudirman  M. Yoga Distra and TURNIP  YUNI MAY CHYNTIA},
		title ={KLASIFIKASI STATUS K-POPERS MENGGUNAKAN COSINE SIMILARITY},
		year={2018},
		url={http://156.67.221.169/4608/},
		abstract={Social media like twitter and facebook do not have the ability to collect
information into a conclusion. For that we need an approach in drawing
conclusions from sentiments or opinions of K-Popers to obtain information to
classify emotions on sentiments or opinions in social media. This research is
based on the rules of System Development Life Cycle (SDLC) Prototype by
applying the Text Mining Cosine Similarity algorithm. This application is designed
using State Transition Diagram (STD) to describe the processes in the
application. Later will be tested against the application by using White Box testing
method. The test results of 50 status or opinion of K-Popers on social media
shows that the Cosine Similarity algorithm is able to classify the types of emotions
contained in that status. With the application of the classification of K-Popers
status is expected to provide information on how many opinions Happy, Sad,
Angry and Neutral circulating on social media twitter and facebook.}
		}