KLASIFIKASI ABSTRAK JURNAL KOMPUTASI MENGGUNAKAN METODE TEXT MINING DAN ALGORITMA SUPPORT VECTOR MACHINE

DOI: https://doi.org/10.23960/pepadun.v1i1.13

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Published: Dec 1, 2020
Abstract views: 165
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Keywords:
Text Mining, TFIDF, Support Vector Machine, 10-Fold Cross Validation

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Eliza Fitri
Jurusan Ilmu Komputer, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Lampung
Favorisen R. Lumbanraja
Jurusan Ilmu Komputer, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Lampung
Ardiansyah Ardiansyah
Jurusan Ilmu Komputer, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Lampung

Abstract

The University of Lampung especially Computer Science Departement has an online journal that publishes various scientific articles written by researchers both students and lecturers. This scientific article is called the online Computating Journal which is published once every 6 months. But, this online Computating Journal has not been structured and classified into the category of science that more specific. Therefore, in this research the abstract Computating Journal will be classified using text mining techniques to process the abstract become more structured and retrieve information in it. Then, the information in the abstract is extracted as a feature by the TFIDF weighting technique. The proposed classification model uses the support vector machine algorithm that has strong consistency. The model classification will be validated by applying the 10-Fold Cross Validation technique.

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How to Cite
Fitri, E., Lumbanraja, F. R. ., & Ardiansyah, A. (2020). KLASIFIKASI ABSTRAK JURNAL KOMPUTASI MENGGUNAKAN METODE TEXT MINING DAN ALGORITMA SUPPORT VECTOR MACHINE. Jurnal Pepadun, 1(1), 83–88. https://doi.org/10.23960/pepadun.v1i1.13
Issue
Vol. 1 No. 1 (2020): December
DOI
https://doi.org/10.23960/pepadun.v1i1.13
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References

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