APPLICATION OF OPINION CLASSIFICATION FOR FASTFOOD RESTAURANT POPULARITY USING INSTAGRAM

Elvandio Frinandy, Dedi Trisnawarman, Ery Dewayani

Abstract


The purpose of this study is to identify several opinions regarding Instagram account of fast food restaurant in Indonesia. By using a system that can provide the information about the popularity ranking of fast food restaurants, researcher conduct an analysis using Naïve Bayes Classifier. To identify the popularity ranking, researcher collected restaurants data from Instagram, preprocessing text, using Naïve Bayes classification, and implementing the programing. The design of this system be able to determine the popularity ranking of fast food restaurants using collected data (number of likes and comments on Instagram’s post). All of the predictions obtained exceeds of 90%, indicating a fairly accurate prediction of the popularity ranking, where all results almost touch the maximum score. Data collected from the restaurants’ Instagram account, indicating positive results and ratings, based on number of likes and comments per post. The result of this research shows that, Burger King restaurants are the most popular, second is Kentucky Fried Chicken, third is McDonalds, fourth is Hokben, and fifth are Wingstop..

Keywords


Instagram; Naïve Bayes; Fast Food Restaurant; Sentiment Analysis

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