Decision Support System for Sentiment Analysis of Youtube Comments on Government Policies

I Putu Agus Eka Darma Udayana; I Gusti Agung Indrawan; I Putu Dwi Guna Ambara  Putra

doi:10.47709/cnahpc.v5i1.1999

Authors

I Putu Agus Eka Darma Udayana Institut Bisnis dan Teknologi Indonesia (INSTIKI)
I Gusti Agung Indrawan Institut Bisnis dan Teknologi Indonesia (INSTIKI)
I Putu Dwi Guna Ambara Putra Institut Bisnis dan Teknologi Indonesia (INSTIKI)

DOI:

10.47709/cnahpc.v5i1.1999

Keywords:

Decision Support System, Sentiment Analysis, Government Policy, Text-Mining, Naïve Bayes

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Abstract

Sentiment analysis is the process of classifying a text dataset as positive, negative or neutral. Youtube is one of the popular media used to provide responses to a problem. In the Jokowi era, infrastructure development was carried out massively and evenly, one of which was in Bali Province, namely the construction of the Mengwi-Gilimanuk Toll Road. The construction of the Mengwi-Gilimanuk Toll Road consumed a lot of people's agricultural land, which resulted in various pro and con responses from the community. From these problems, sentiment analysis is carried out to get community reviews related to the object being analyzed by utilizing algorithms to be able to classify opinions, in the construction of this system the naïve bayes algorithm is used with testing methods namely accuracy, precision, and recall. From the sentiment analysis conducted by utilizing 18 video links on YouTube with 701 comments, it produces positive sentiment as much as 50.64%, negative sentiment as much as 7.70% and neutral sentiment as much as 39.23%.

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