CLASSIFICATION OF SPORTS NEWS USING THE NAÏVE BAYES CLASSIFIER METHOD

Sya’bani, Muhammad Hilmi Aziz (2022) CLASSIFICATION OF SPORTS NEWS USING THE NAÏVE BAYES CLASSIFIER METHOD. Tugas Akhir thesis, University of Technology Yogyakarta.

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Abstract

ABSTRACT News is a source of information about current events which can be found in newspapers, television, internet, and other media. News documents, especially sports news, have a large number in a short period of time. For easy access to documents, it is necessary to group news documents into several categories. It is intended that sports news are arranged according to the specified categories. News can be grouped manually by humans, but it takes a long time to categorize. The classification method proposed in this study is to automatically categorize sports news documents, so as to increase time efficiency. In this study, the Naïve Bayes Classifier method was used. Before classification, there is a preprocessing process, this aims to return to the basic form, so that news documents are reduced and the computational process becomes more efficient. For the training dataset there are 500 news data (100 news/type) and for the testing dataset there are 125 news data (25 news/type). From this research, it can be concluded that the Sports News Classification System using the Naïve Bayes Classifier method is able to classify sports news according to their respective categories. Such as Football, Badminton, Basketball, MotoGP, and Other Sports with an accuracy of 83.2 %. Keywords: Classification, Sports News, Naïve Bayes Classifier.

Item Type:	Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir)
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User:	Kaprodi S1 Informatika UTY
Date Deposited:	08 Apr 2022 02:42
Last Modified:	08 Apr 2022 02:42
URI:	http://eprints.uty.ac.id/id/eprint/9564

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