Document Classification using Naïve Bayes for Indonesian Translation of the Quran

Syopiansyah Jaya Putra, Syopiansyah Jaya Putra and Yuni Sugiarti, Yuni Sugiarti and Galuh Dimas, Galuh Dimas and Muhamad Nur Gunawan, Muhamad Nur Gunawan and Tata Sutabri, Tata Sutabri and Agung Suryatno, Agung Suryatno Document Classification using Naïve Bayes for Indonesian Translation of the Quran. IEEE. ISSN 978-1-7281-2909-9

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Abstract

Classification for Indonesian language documents was increased. But the application of classification for question and answer system needs is still few. The purpose of this paper is to maximize the classification of Indonesian documents especially the Qur'an translation to support the question and answer system. In the process of creating a question and answer system that is still ongoing, testing the Naïve Bayes algorithm becomes very important besides other algorithms. The Naïve Bayes method is the first choice in this test as it has practicality in calculating. The result of this study is the classification of ITQ documents with 4 categories: morality, faith, knowledge, and Muamalah. The average accuracy rate of 90.5% indicates that the Naïve Bayes method is still relevant for use.

Item Type: Article
Subjects: L Education > L Education (General)
Q Science > Q Science (General)
T Technology > T Technology (General)
Depositing User: Dr. Tata Sutabri
Date Deposited: 01 Apr 2023 01:16
Last Modified: 01 Apr 2023 01:16
URI: http://eprints.binadarma.ac.id/id/eprint/17450

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