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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi)
Anak Agung Kompiang Oka Sudana
Department of Information Technology, Udayana University, Bali, Indonesia
Computer Science & IT

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Text Classification System Using Text Mining with XGBoost Method Ni Kadek Dwi Rusjayanthi; Anak Agung Kompiang Oka Sudana; I Nyoman Prayana Trisna
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 11 No 2 (2023): Vol. 11, No. 2, August 2023
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2023.v11.i02.p01

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%.
Co-Authors I Nyoman Prayana Trisna Ni Kadek Dwi Rusjayanthi