PENERAPAN ALGORITMA NAÏVE BAYES CLASSIFICATION UNTUK KLASIFIKASI SENTIMENT TWEET TERHADAP PLATFORM STREAMING ILEGAL

Angga Sukma Wahyu; Jati Sasongko Wibowo; I Putu Brama Arya Di Putra

doi:10.35959/jik.v11i02.433

Angga Sukma Wahyu UNIVERSITAS STIKUBANK
Jati Sasongko Wibowo UNIVERSITY OF STIKUBANK
I Putu Brama Arya Di Putra Institut Teknologi Bisnis Dan Bahasa Dian Cipta Cendikia

DOI: https://doi.org/10.35959/jik.v11i02.433

Keywords: Illegal streaming, Naïve bayes classification algorithm, Sentiment analisys, Twitter

Abstract

According to a survey by the Coalition Against Piracy (CAP) of the Asia Video Industry Association, 63% of online
streaming service users in Indonesia prefer to watch illegal streaming platforms for free with various "consequences." This makes Indonesia become one of the nations with the highest percentage of users of illegal streaming platforms.In the other side, illegally stream can also violate broadcasting rights rules, which can result some of comments from internet users, including those with both positive and negative feeling about the existence of this illegal streaming platforms.Comments in the form of these sentiments may be found in a variety of media, one of which is the social media site Twitter. Twitter serves as a platform for the expression of thoughts and sentiments as well as for enjoy free time. This research was conducted to find out the comments and opinions of netizens about illegal streaming platforms and will be classified into positive and negative sentiments using the Naïve Bayes Classification Algorithm with the help of the TF-IDF (Term Frequency – Inverse Document Frequency) weighting method. In this study, balanced results were obtained where positive sentiment data was 50% while negative sentiment data was 50% with the value of accuracy 50%, precission 53%, recall 51%, and f-measure 51.

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