Perbandingan Kinerja Metode Naïve Bayes dan Support Vector Machine dalam Analisis Sentimen Opini Masyarakat terhadap Dinasti Politik Keluarga Jokowi di Platform X

SALVATORIS, Mario Rinaldi (2026) Perbandingan Kinerja Metode Naïve Bayes dan Support Vector Machine dalam Analisis Sentimen Opini Masyarakat terhadap Dinasti Politik Keluarga Jokowi di Platform X. Undergraduate thesis, Universitas Katolik Widya Mandira.

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Abstract

Political dynasties generate a wide range of public opinion, much of which is expressed on the social media platform X. Diverse public opinion, ranging from support to rejection, can be analyzed using a sentiment analysis approach to understand public attitudes toward the issue. Political dynasties often spark debate because they are considered to hinder democracy and create inequality of opportunity for other competent individuals who do not have family ties to the political elite. This study aims to determine public sentiment on the X platform towards the issue of political dynasties, as well as to compare the performance of the Naïve Bayes and Support Vector Machine (SVM) methods in classifying opinions into positive, negative, and neutral sentiments. This study uses 3526 Indonesian-language tweet data. The results of this study show that sentiment towards political dynasties is 57.8% negative, 30.8% neutral, and 11.5% positive. The results of this study also show that the Support Vector Machine method has a slightly higher accuracy (65%) than the Naive Bayes method (62%).

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