Analisis Sentimen Kegiatan Pembersihan Sampah Pada Media Sosial X Menggunakan SVM dan Naïve Bayes - Nugroho, Dendy Aprilianto; Hasan, Firman Noor (Universitas Budi Darma, 2024)
Human daily activities inevitably produce waste, which negatively impacts environmental balance due to the bad habit of indiscriminately disposing of waste. As a result of this issue, there is a youth community named Pandawara Group that wants to help clean up trash on Sukabumi Beach. However, their initiative faced rejection from the local village chief and youth organization, sparking various opinions on social media platform X. Consequently, this research seeks to analyze public sentiment towards Pandawara Group's waste cleanup efforts at Sukabumi Beach using Support Vector Machine and Naïve Bayes methods. The objective is to gauge positive and negative sentiments and compare the accuracy of Support Vector Machine and Naïve Bayes. In this sentiment analysis using 2,339 datasets, the highest accuracy was achieved using the Support Vector Machine method at 91.67%, whereas the Naïve Bayes method only achieved 63.89%. Thus, it can be concluded that Support Vector Machine is superior in classifying sentiments regarding Pandawara Group's waste cleanup activities at Sukabumi Beach compared to Naïve Bayes.