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All Journal Majalah Ilmiah Teknologi Elektro
Kadek Ary Budi Permana
Univesitas Udayana
Electrical & Electronics Engineering

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Analisis Rating Sentimen pada Video di Media Sosial Youtube Menggunakan STRUCT-SVM Kadek Ary Budi Permana; Made Sudarma; Wayan Gede Ariastina
Jurnal Teknologi Elektro Vol 18 No 1 (2019): (Januari - April) Majalah Ilmiah Teknologi Elektro
Publisher : Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (327.817 KB) | DOI: 10.24843/MITE.2019.v18i01.P17

Abstract

Sentiment analysis on comments can be used to determine sentiment rating. The comments used are comments on Youtube. The type of video used is the official trailer video Indonesian movie. This paper contains steps to determine sentiment rating by notice the structure of comments. The structure of comments is needed because not all comments are relevant to the topic. Classes on comments are divided into seven classes including positive films, neutral films, negative films, positive not films, neutral not film, negative not film, and spam / off-topic. Comments that have a positive film or film negative class are used to determine sentiment rating. The number of likes in comments also determines the sentiment rating. Comment classification using STRUCT-SVM. The results of STRUCT-SVM show accuracy of 69.68% for linear kernels and 71.34% for RBF kernels.
Co-Authors Made Sudarma Wayan Gede Ariastina