Natural Language Processing Ekstraksi Akronim Dan Ekspansi Pada Artikel Berbahasa Indonesia Menggunakan Metode Text Mining Dan Term Frequency-Inverse Document Frequency

bahrus sobri pulungan

doi:10.47065/jogtc.v3i3.6256

bahrus sobri pulungan * Universitas Budi Darma, Medan, Indonesia

(*) Corresponding Author

DOI: https://doi.org/10.47065/jogtc.v3i3.6256

Keywords: Extraction; Acronyms; Expansion; Articles; Indonesian

Abstract

Acronyms are abbreviations of combinations of several letters or syllables written and pronounced as words according to the phonological rules of the affected language. The extension of an acronym is called expansion. Acronym extraction and expansion is one of the text mining tasks in the field of information retrieval used in search engines. Search engines require a database of acronyms and expansion in determining search results for relevant information. The problem is that it often occurs when someone or a researcher makes a scientific work, especially research in Indonesia, which ignores the extraction of acronyms from each word used or is not quite right, so a way is needed to overcome this by creating an application or media to detect the extraction of the acronym using applying the Text Mining Algorithm and Term Frequency-Inverse Document Frequency (TF-IDF). Based on the problems contained in this research, the author is interested in conducting research on a thesis with the title "Natural Language Processing Acronym Extraction and Expansion in Indonesian Articles Using Text Mining Methods and Term Frequency-Inverse Document Frequency (TF-IDF)". Based on the results of calculations with TF-IDF, in acronym extraction and expansion, the weight value obtained is with a weight value of -0.053. Based on this, the extracted sentence is obtained.

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