JISA (Jurnal Informatika dan Sains)
Vol 3, No 2 (2020): JISA(Jurnal Informatika dan Sains)

Implementation of TF-IDF Algorithm and K-mean Clustering Method to Predict Words or Topics on Twitter

Muhammad Darwis (Universitas Budi Luhur)
Gatot Tri Pranoto (Universitas Budi Luhur)
Yusuf Eka Wicaksana (Universitas Budi Luhur)
Yaddarabullah Yaddarabullah (Universitas Trilogi)

Article Info

Publish Date
27 Dec 2020

Abstract

The social media time line, especially Twitter, is still interesting to follow. Various tweets delivered by the public are very informative and varied. This information should be able to be used further by utilizing the topic of conversation trends at one time. In this paper, the authors cluster the tweet data with the TF-IDF algorithm and the K-Mean method using the python programming language. The results of the tweet data clustering show predictions or possible topics of conversation that are being widely discussed by netizens. Finally, the data can be used to make decisions that utilize community sentiment towards an event through social media like Twitter.  

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Journal Info
JISA (Jurnal Informatika dan Sains)
Website

Abbrev

JISA

Publisher

Universitas Trilogi

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Description

JISA (Jurnal Informatika dan Sains) is an electronic publication media which publishes research articles in the field of Informatics and Sciences, which encompasses software engineering, Multimedia, Networking, and soft computing. Journal published by Program Studi Teknik Informatika Universitas ...