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All Journal Jurnal ilmiah teknologi informasi Asia
Yasin, Andrew Arjunanda
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Computer Science & IT

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Analisis Sentimen Tiktok Shop Menggunakan Metode Multinomial Naïve Bayes Dan BM25 Yasin, Andrew Arjunanda; Prasetya, Dwi Arman; Fahrudin, Tresna Maulana
Jurnal Ilmiah Teknologi Informasi Asia Vol 18 No 2 (2024): Volume 18 nomor 2 2024 (8)
Publisher : LP2M Institut Teknologi dan Bisnis ASIA Malang

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Abstract

In the current digital era, TikTok has emerged as a popular application among internet users. One prominent feature is the TikTok Shop, which allows users to shop directly through the platform. However, on October 4, 2023, TikTok Shop was temporarily suspended by the government due to online trade regulation policies. After reopening on December 12, 2023, various responses from the public emerged in reaction to this phenomenon. This research conducted sentiment analysis on TikTok Shop by observing public responses on Twitter using the Multinomial Naïve Bayes classification method with word weighting using the BM25 and TF-IDF methods. The analysis results showed a majority of positive sentiment regarding TikTok Shop, indicating disapproval of the previous closure policy. In testing with a 10% test sample size, BM25 showed slightly better performance than TF-IDF.
Co-Authors Dwi Arman Prasetya Fahrudin, Tresna Maulana