Jurnal Teknik Komputer AMIK BSI
Vol 8, No 2 (2022): JTK Periode Juli 2022

Analisa Sentimen Perkembangan Vtuber Dengan Metode Support Vector Machine Berbasis Smote

Normah Normah (Universitas Nusa Mandiri, Informatika)
Bakhtiar Rifai (Universitas Nusa Mandiri, Informatika)
Satrio Vambudi (Universitas Nusa Mandiri, Informatika)
Rifki Maulana (Universitas Nusa Mandiri, Informatika)



Article Info

Publish Date
02 Aug 2022

Abstract

Vtuber (Virtual Youtuber) is a content creator who creates content for the YouTube platform. Unlike other content creators, Vtuber uses 2D or 3D animated characters to interact with viewers. Vtubers usually use iconic anime characters to represent them, this is intended to attract viewers who usually come from Weaboo circles or commonly called Otaku. For this reason, it is necessary to make a sentiment analysis about vtuber to provide knowledge about vtuber for the Indonesian. The purpose of this study is to be able to model sentiment classification using the Support Vector Machine (SVM) method using a balancing method, namely the Synthetic Minority Oversampling Technique (SMOTE) found in RapidMiner, and to find out the vtuber trend in Indonesia based on Twitter can be done to find out how many people think about vtuber in this regard can be done by utilizing the API provided by twitter. From the results of the classification using a dataset of 321 comments data, it is known that there are 220 positive data and 101 negative data, resulting in an accuracy of 88.18% and 89% positive

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Journal Info

Abbrev

jtk

Publisher

Subject

Computer Science & IT

Description

Jurnal Teknik Komputer merupakan jurnal ilmiah yang diterbitkan oleh LPPM Universitas Bina Sarana Informatika. Jurnal ini berisi tentang karya ilmiah hasil penelitian yang bertemakan: Networking, Robotika, Aplikasi Sains, Animasi Interaktif, Pengolahan Citra, Sistem Pakar, Sistem Komputer, Soft ...