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All Journal JURIKOM (Jurnal Riset Komputer)
Izzan Faikar Ramadhy
Telkom University, Bandung
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Analisis Trending Topik Twitter dengan Fitur Ekspansi FastText Menggunakan Metode Logistic Regression Izzan Faikar Ramadhy; Yuliant Sibaroni
JURIKOM (Jurnal Riset Komputer) Vol 9, No 1 (2022): Februari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i1.3791

Abstract

Twitter is a social media that contains information such as the latest news, a person's biography, and tweets from users. Twitter has a feature called trending topics that serves to find out information on certain topics that are currently popular. In fact, it is often difficult to understand what trending topics are happening. Therefore, it is necessary to classify trending topics into a general category. This study aims to analyze and classify Twitter topic trending information by dividing several topic trend labels using the FastText expansion feature method. The FastText expansion feature is used to reduce vocabulary mismatches in a tweet. The classification process of this system will use the Logistic Regression method. The best results were obtained in this study using test data scenarios, 90:10 training data with 76.39% accuracy. The most discussed trending topic from September 2021 to October 2021 was politics with a percentage of 15.83%, followed by religion 12.64% and technology 10.42%
Co-Authors Yuliant Sibaroni