Aristoteles, Aristoteles and Djatna, Taufik (2011) KEAKURASIAN ALGORITMA ITERATIVE DICHCOTOMISER 3 (ID3), NAÏVE BAYES, DAN K-NEARST NEIGHBOR (KNN) untuk KLASIFIKASI DOKUMEN BAHASA INDONESIA. In: SEMINAR NASIONAL SAINS DAN TEKNOLOGI IV, 29-30 Novenber 2011, Bandar Lampung, Indonesia.

[img] Text
2012_03_aristoteles.pdf

Download (652kB)
Official URL: http://satek.unila.ac.id

Abstract

Classification of text documents is a fundamental problem and important. In a text document, which contained writings is a natural human language, which is a language with a complex structure and the number of words very much. Therefore, this problem is very challenging due to the use of natural language. This paper discusses the document classification method by using the concept of ID3 algorithm, by taking into account the number of times the word appears in the text document. In contrast to these methods, such methods are also discussed Naive Bayes Classifier, which is a method to calculate the chance appearance of the word, and the method of K-Nearest Neighbor (KNN), which is a method that takes into account the number of times the word similarity between a document with other documents. In this study, we tried to do experiments on the data to determine the accuracy of ID3 algorithm, Naive Bayes and KNN for use in a text document classification problem the Indonesian language. The contribution of this research is to provide a comparison of the accuracy of ID3 algorithm, Naïve Bayes and KNN for classification of documents Indonesian news.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Ilmu Komputer
Depositing User: Aristoteles Aristoteles
Date Deposited: 29 Oct 2018 04:22
Last Modified: 29 Oct 2018 04:22
URI: http://repository.lppm.unila.ac.id/id/eprint/8888

Actions (login required)

View Item View Item