Buffer Informatika
Vol 7 No 1 (2021)

ANALISIS SENTIMEN MEDIA SOSIAL TIKTOK DENGAN METODE SUPERVISED LEARNING PADA ALGORITMA MACHINE LEARNING

Nur Az-zahra, Rizka Namira (Unknown)
Fitrialdi, Moh Rizqi (Unknown)
Nurjanah, Esa (Unknown)
Darmawan, Mardotilah (Unknown)
Firmansyah, Ricky (Unknown)



Article Info

Publish Date
25 Jan 2024

Abstract

TikTok is an application that is downloaded by many people nowadays, it is because the government policy pushes us to stay at home during this pandemic COVID-19. There are many content creators who made up their creative ideas on TikTok and also the netizens who watch them are entertained. Certainly, TikTok cannot be separated by a thing that is called hashtag. By using hashtag(s), the similar contents can be classified easily. Even the content can be added to FYP (For Your Page). If it is added to FYP, the content can go viral instantly. Of course, there are many pros and cons on the viral content. Sentiment analysist is a study of public judgement and opinion. This study uses Machine Learning method. It is a supervised learning on sentiment analysist of a video that is currently going viral, which is on that video there are positive, negative, and neutral opinion.

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Journal Info

Abbrev

buffer

Publisher

Subject

Computer Science & IT

Description

BUFFER INFORMATIKA adalah jurnal peer-review tentang Informasi dan Teknologi yang mencakup semua cabang IT dan sub-disiplin ilmu termasuk Algoritma, Jaringan Komputer, Game, Rekayasa Perangkat Lunak, Aplikasi Mobile, Kecerdasan Buatan, Image Processing, Grafik Komputer, Data Maining dan Informasi ...