KLASIFIKASI BERITA BERBAHASA INDONESIA MENGGUNAKAN NAÏVE BAYES CLASSIFIER

MUTHMAINNAH, QURROTA 'AINI and Rini, Dian Palupi and Rodiah, Desty (2020) KLASIFIKASI BERITA BERBAHASA INDONESIA MENGGUNAKAN NAÏVE BAYES CLASSIFIER. Undergraduate thesis, Sriwijaya University.

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Abstract

News was initially published through media such as television, radio and newspapers, but with the current technological advancements making a digitizing information gets easier. News in a form of digital text can be published faster, actual and inexpensive which enable it to increased gradually. Therefore, there is a need for a system that can classify news automatically according to existing news categories by using the text classification method. Thus a very large collection of documents can be organized in order to simplify and speed up the search for information related. In this research, the news text classification used were Naïve Bayes Classifier method which able to classify into four categories namely, natural disasters, health, sports and education. The test is carried out four times with different data sharing, and the accuracy obtained is the first test 100%, the second test 100%, the third test 98.33% and the fourth test 96.25%. From these results, it can be concluded that the results of news text classification are good. Keywords : Text Classification, Naïve Bayes Classifier.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Text Classification, Naïve Bayes Classifier
Subjects: Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning
Divisions: 09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User: Qurrota 'Aini Muthmainnah
Date Deposited: 18 Aug 2020 06:55
Last Modified: 18 Aug 2020 06:55
URI: http://repository.unsri.ac.id/id/eprint/33143

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