@thesis{thesis,
		author={Maghfirah  Ulfa and Palupiningsih  Pritasari and Yosrita  Efy},
		title ={Implementasi Algoritma Naïve Bayes dan Winnowing untuk Pengklasifikasian Topik pada Kemiripan Dokumen Project Assignment Peserta Diklat PT PLN (Persero) UPDL Jakarta},
		year={2020},
		url={http://156.67.221.169/4130/},
		abstract={Project Assignment document checking process in PT PLN (Persero) UPDL Jakarta is processed by reading the Project Assignment document which can cause human error. For reducing Project Assignment document similarity checking error, it can be used Winnowing Algorithm. But, in its implementation, the Project Assignment document will be checked to all documents in the database, so it will take more time to process it. In this research, for reducing the time process of Winnowing Algorithm, it will be used Naive Bayes Algorithm for classifying Project Assignment document that will be tested for its similarity measurement so it will reduce the time process of Winnowing Algorithm because the similarity measurement will only be done on documents with the same label with the test documents. The results of classification from Naïve Bayes algorithm divided into five class of topics, such as distribution, commerce, power plant, support and transmission. The data used are Project Assignment documents with 20 of training documents and 10 of test documents. The implementation of classification can reduce the time process of Winnowing algorithm up to seven time faster than without applying the classification algorithm. In this research, the result of classification modelling by using Naive Bayes algorithm is 70% accuracy.}
		}