Implementation of Document Clustering in Online News Using K-Means Clustering

  • Yogiswara Dharma Putra Department of Electrical and Computer Engineering, Post Graduate Program, Udayana University
  • Ni Wayan Sri Ariyani Department of Electrical and Computer Engineering, Post Graduate Program, Udayana University
  • Ida Bagus Alit Swamardika Department of Electrical and Computer Engineering, Post Graduate Program, Udayana University

Abstract

The development of technology when making an explosion of the number of news or news documents that are very much on the internet, it is necessary to have clustering done in dividing these documents so that they can be adjusted based on the category of the online news. Application of document clustering can increase the effectiveness of information retrieval by referring to a hypothesis that relevant documents will tend to be in the same cluster if a collection of documents has been clustered. This research aims to try to do clustering on online news about Covid-19 taken from three online news websites contained in XML files. K-Means clustering is used as a grouping of online news by using an open-source application, Carrot2 Workbench which turns out to be able to generate nine clusters of "Covid-19" queries entered in the Carrot2 application.

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Published
2020-12-13
How to Cite
DHARMA PUTRA, Yogiswara; ARIYANI, Ni Wayan Sri; SWAMARDIKA, Ida Bagus Alit. Implementation of Document Clustering in Online News Using K-Means Clustering. International Journal of Engineering and Emerging Technology, [S.l.], v. 5, n. 2, p. 61-65, dec. 2020. ISSN 2579-5988. Available at: <https://ojs.unud.ac.id/index.php/ijeet/article/view/60059>. Date accessed: 21 nov. 2024. doi: https://doi.org/10.24843/IJEET.2020.v05.i02.p10.