Authors:

Ni Kadek Dwi Rusjayanthi, Anak Agung Kompiang Oka Sudana, I Nyoman Prayana Trisna

Abstract:

“Large data nowadays can be used for analysis; thus, it can obtain important/valuable knowledge in various domains. Text analysis can be carried out by utilizing text mining using computational methods so that knowledge extraction can be carried out on large text data, including processing related to unstructured text data, which is written in natural language. Classification in text mining is a type of work with the searching process for a set of models or functions that describe and differentiate text data classes with the aim that the model can be used to predict the class of an object (text data) whose class is unknown. Text mining was carried out in this research to analyze text data through the Text Classification System using a classification method, namely the XGBoost (eXtreme Gradient Boosting) Method. A text classification system was developed to classify text in the form of articles. The highest accuracy obtained from the test is 77%.”

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PDF:

https://jurnal.harianregional.com/merpati/full-100799

Published

2023-08-21

How To Cite

RUSJAYANTHI, Ni Kadek Dwi; SUDANA, Anak Agung Kompiang Oka; TRISNA, I Nyoman Prayana. Text Classification System Using Text Mining with XGBoost Method.Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi), [S.l.], v. 11, n. 2, p. 61-70, aug. 2023. ISSN 2685-2411. Available at: https://jurnal.harianregional.com/merpati/id-100799. Date accessed: 08 Jul. 2024. doi:https://doi.org/10.24843/JIM.2023.v11.i02.p01.

Citation Format

ABNT, APA, BibTeX, CBE, EndNote - EndNote format (Macintosh & Windows), MLA, ProCite - RIS format (Macintosh & Windows), RefWorks, Reference Manager - RIS format (Windows only), Turabian

Issue

Vol 11 No 2 (2023): Vol. 11, No. 2, August 2023

Section

Articles

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