Skripsi

KLASIFIKASI DOKUMEN BERITA OLAHRAGA MENGGUNAKAN NAIVE BAYES CLASSIFIER

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107002392	T40902	T409022021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T409022021

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2021

Collation

xiv, 73 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Pemrosesan Data, Teknik Informatika
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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