KLASIFIKASI DOKUMEN BERITA OLAHRAGA MENGGUNAKAN NAIVE BAYES CLASSIFIER

SILABAN, OJHI GUSTI MAROJAHAN and Utami, Alvi Syahrini and Abdiansah, Abdiansah (2020) KLASIFIKASI DOKUMEN BERITA OLAHRAGA MENGGUNAKAN NAIVE BAYES CLASSIFIER. Undergraduate thesis, Sriwijaya University.

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Abstract

Document classification aims to group unstructured documents into groups that describe the contents of the document. Documents can be text documents such as news articles. One type of news that is in great demand is sports news, especially by men. The number of sports makes readers confused looking for sports news that they want to read. Therefore, document classification is needed in order to classify sports news according to the sports news group. To solve this problem, software was developed using the Naïve Bayes Classifier with simple computation and a fairly high degree of accuracy. The Naïve Bayes Classifier predicts future probabilities based on past experiences. There are three stages, namely, preprocessing, training, and classification. This study uses secondary data taken from online news portals with various categories, namely football, basketball, badminton, MotoGP, formula1, and MMA. The resulting accuracy rate from the software is 73.33% by using 30 training documents and 30 test documents.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Klasifikasi dokumen, berita olahraga, Naïve Bayes Classifier
Subjects:	P Language and Literature > P Philology. Linguistics > P98-98.5 Computational linguistics. Natural language processing
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 10201 not found.
Date Deposited:	25 Jan 2021 06:41
Last Modified:	25 Jan 2021 06:41
URI:	http://repository.unsri.ac.id/id/eprint/40902

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