Analisis Sentimen Publik Terhadap Kasus Affan Kurniawan menggunakan Metode Naïve Bayes

MAU, Septiana Helena Mali (2026) Analisis Sentimen Publik Terhadap Kasus Affan Kurniawan menggunakan Metode Naïve Bayes. Undergraduate thesis, Universitas Katolik Widya Mandira.

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Abstract

The rapid development of the digital era has made social media the primary platform for Indonesians to express their opinions on various social and political issues. One case that attracted widespread public attention was the death of Affan Kurniawan, a 21-year-old online motorcycle taxi driver who was run over by a Brimob Polri tactical vehicle during a labor demonstration in Pejompongan, Central Jakarta, on August 28, 2025. This study aims to implement the Naïve Bayes algorithm in classifying public sentiment towards the case on Platform X. The research stages include data collection, preprocessing (consisting of cleansing, case folding, tokenization, stopword removal, and stemming), manual data labeling, and word weighting using the TF-IDF method. The dataset is divided into 80% training data and 20% test data, then classified using the Naïve Bayes algorithm. Based on an analysis of 3,559 tweets, negative sentiment dominated at 40.6%, followed by positive sentiment at 29.6% and neutral sentiment at 27.4%. The dominance of negative sentiment indicates a tendency for public opinion to be critical and disappointed with the death of Affan Kurniawan. Model testing results showed that the Naïve Bayes algorithm was able to classify public sentiment with an accuracy of 72,13%, a precision value of 72,78%, a recall of 72,13%, and an F1-Score of 71,55%.

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