Implementation Of Text Mining And Pattern Discovery With Naive Bayes Algorithm For Classification Of Text Documents
Abstract Classification of text documents can be managed manually by using human-made classification rules. However, as many text document files exist today, the application of machine learning can help to classify the documents more effectively and the structured. Data mining with the Naïve Bayes a...
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Published in: | Digital zone Vol. 14; no. 1; pp. 88 - 102 |
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Main Authors: | , , |
Format: | Journal Article |
Language: | Indonesian |
Published: |
Universitas Lancang Kuning
01-05-2023
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Subjects: | |
Online Access: | Get full text |
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Summary: | Abstract Classification of text documents can be managed manually by using human-made classification rules. However, as many text document files exist today, the application of machine learning can help to classify the documents more effectively and the structured. Data mining with the Naïve Bayes algorithm can help the process of searching for a set of patterns or characteristics that explain and separate a classification of data based on the aim that the model can used to predict and classify the the data that has been used. This study uses text mining and pattern discovery techniques with the naïve Bayes algorithm used in the Indonesian language online news classification process with an accuracy test result of 63.9 and a low error rate of 41.02%. |
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ISSN: | 2086-4884 2477-3255 |
DOI: | 10.31849/digitalzone.v14i1.13596 |