Bulletin of Computer Science Research
Vol. 3 No. 4 (2023): June 2023

Rekomendasi Berita Berkaitan dengan Menerapkan Algoritma Text Mining dan TF-IDF

Natalia Silalahi (Universitas Negeri Medan, Medan)
Guidio Leonarde Ginting (Universitas Budi Darma, Medan)



Article Info

Publish Date
25 Jun 2023

Abstract

News presentation is generally structured in such a way that the information presented is well grouped, but the use of electronic media does not necessarily offer complete news categories because not all of the space offered can be filled with good presentation, so special treatment is needed so that readers get the news. needed which is arranged based on recommendations. To arrange this research to be more structured, the authors carried out several stages in completing the research, namely the Problem Identification Stage, Literature Study Stage, Data Collection Stage, Text Mining and TF-IDF Algorithm Implementation Stage, and conclusions. The author implements the text mining and TF-IDF algorithms in processing news title data starting with the Text Mining Algorithm where this stage is a preprocessing stage with the aim that the data to be processed is a basic word so that the weighting process in the TF-IDF Algorithm is not too broad. After the text mining stage, it will proceed to the TF-IDF stage, namely weighting the terms in each document. Text mining and TF-IDF algorithms are able to provide appropriate news recommendations based on the highest similarity in meaning both in terms of topic and object of the news title, for future research it is recommended to use other algorithms such as cosine similar so that recommendations are not only generated from the suitability of words but can also see the similarity of meaning so that research results can be even better.

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Journal Info

Abbrev

bulletincsr

Publisher

Subject

Computer Science & IT

Description

Bulletin of Computer Science Research covers the whole spectrum of Computer Science, which includes, but is not limited to : • Artificial Immune Systems, Ant Colonies, and Swarm Intelligence • Bayesian Networks and Probabilistic Reasoning • Biologically Inspired Intelligence • Brain-Computer ...