@thesis{thesis,
		author={Jatnika  Hendra and Latemamala  I Wayan Vicar Daeng and Widiyanto  Max Teja Ajie Cipta},
		title ={Sentiment, Analisys, Twitter, Text Mining, Naive Bayes Classifier,
Waterfall, Unified Modelling Language (UML), Black Box, Web.},
		year={2020},
		url={http://156.67.221.169/4071/},
		abstract={JPKP (Jaringan Pendamping Kebijakan Pembangunan) volunteers rely on houses and laptops as storage media for document archives, the number of archive categories is recorded as 5 categories and the number of archives per category is in the tens to hundreds. Searching for documents also takes a lot of time because the storage is still manual and not well-structured. Files that are stored in a room can also be damaged due to several factors, namely floods, fires, humid room temperature and files eaten by termites and rats. Then the archived document files can be lost or scattered if the storage is not structured properly or neatly. This is the basis for making this application with automatic document categorization. It is hoped that this application will be able to provide precise categorization results. The cosine similarity method and the TF-IDF method are able to assist in web-based automatic categorization according to predetermined categories.}
		}