Sentimen Analisis Operasi Tangkap Tangan KPK Menurut Masyarakat Menggunakan Algoritma Support Vector Machine, Naive Bayes Berbasis Particle Swarm Optimizition

Sentimen Analisis Operasi Tangkap Tangan KPK Menurut Masyarakat Menggunakan Algoritma Support Vector Machine, Naive Bayes Berbasis Particle Swarm Optimizition

• By HERNAWATI; GATA,WINDU;
• Jurnal Nasional Terakreditasi
• 422
• 230-243

It is known from various public sentiments conveyed through comments on social media twitter against the capture operations carried out by the corruption eradication commission (KPK) that currently it does not meet the expectations of the community, where officials who are only officials have small corruption rates, not corruption As for the classification algorithms that have strong accuracy at this time are Support Vector Machine and Naïve Bayes algorithms, calculation of Support Vector Machine method for tweet data from 78 positive tweet data and 78 negative tweet data, resulting in an accuracy of 80.77% and AUC 0.867. Whereas the results of accuracy with the Naïve Bayes method are 76.92% and AUC 0.729. Having a difference in accuracy of 3.3%, and after optimizing with the Operator Vector Machine (PSO) weight Particle Swarm Optimization the accuracy is 83.79% and AUC 0.910, while for Naïve Bayes (PSO) produces an accuracy of 80.13% and AUC 0.771 Has a difference in accuracy of 3.6%.

• Katakunci KPK, Support Vector Machine, Naïve Bayes, Sentimen Analisis, Particle Swarm Optimization.
• URL https://journal.lppmunindra.ac.id/index.php/Faktor_Exacta/article/view/4992
• Penerbit ,

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