CD Skripsi

Klasifikasi Berita Dengan Natural Language Processing Menggunakan Metode Tf-Idf Dan Naïve Bayes Di Badan Pusat Statistik Provinsi Riau

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The existence of online news sites is used by the Central Bureau of Statistics (CBS) Riau to collect phenomena that occur in society as supporting data for the data they publish. The long time for collecting and processing news data as well as other work that must be done by officers means that news data collection activities tend to be postponed so that the CBS Riau does not have sufficient supporting data for the data or information they publish. This research aims to classify news into certain categories according to the needs of the CBS Riau. The method used in this research is Natural Language Processing. In classifying text, NLP utilizes Machine Learning which in this research uses the Multinomial Naïve Bayes (MNB) algorithm. The MNB algorithm will predict the class of a text based on the appearance probability of words within the text. This research uses Research and Development (R&D) as a research method which involves a number of systematic steps to classify news using Natural Language Processing into several categories required by Riau Central Bureau of Statistics. The research carried out succeeded in obtaining an accuracy validation value of 83%, accuracy test value of 90% and the average result of precision result of 0.85 and recall 0.93.


Keywords: News, Classification, NLP

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

2007114460

Penerbit

Pekanbaru : Universitas Riau - F. Teknik - Teknik Informatika., 2024

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

2007114460

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

TEKNIK INFORMATIKA

Info Detail Spesifik

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Pernyataan Tanggungjawab

Zenny

Versi lain/terkait

Lampiran Berkas

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