Document Classification using Naïve Bayes for Indonesian Translation of the Quran
| Autor: | Yuni Sugiarti, Agung Suryatno, Galuh Dimas, Syopiansyah Jaya Putra, Muhamad Nur Gunawan, Tata Sutabri |
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| Rok vydání: | 2019 |
| Předmět: |
Questions and answers
Computer science business.industry Process (engineering) Document classification computer.software_genre Translation (geometry) language.human_language Test (assessment) Indonesian Naive Bayes classifier language Artificial intelligence business computer Natural language processing |
| Zdroj: | 2019 7th International Conference on Cyber and IT Service Management (CITSM). |
| DOI: | 10.1109/citsm47753.2019.8965390 |
| Popis: | 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 Naive Bayes algorithm becomes very important besides other algorithms. The Naive 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 Naive Bayes method is still relevant for use. |
| Databáze: | OpenAIRE |
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