Comparison between naive bayes method and support vector machine in sentiment analysis of the relocation of the Indonesian capital
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Abstract
Moving the capital city of Indonesia has drawn pros and cons among the public. Therefore, it is important to analyze public sentiment towards moving the Indonesian capital to Kalimantan. In this study, we used data from Twitter and YouTube comments as many as 3895 and 1884 data, starting from 18 May to 6 July 2022. The purpose of this study was to classify public sentiment towards the move of the Indonesian capital city into positive, negative and neutral, as well as compare the results of sentiment analysis using the Naïve Bayes and Support Vector Machine methods. The K-Fold Validation method is used to measure the accuracy of sentiment analysis results. The results of the analysis show that SVM has better accuracy than Naïve Bayes with an accuracy percentage of 0.897 and 0.802 respectively. The resulting comment labels indicated that 56% were positive, 32% neutral, and 11% negative. In this study, we also compared the results of previous studies using the same method, namely Naïve Bayes and SVM. This research can assist the government in evaluating public opinion on the relocation of the Indonesian capital and can be a reference for future researchers in analyzing public sentiment in the future.
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