Integrasi N-gram, Information Gain, Particle Swarm Optimation di Naïve Bayes untuk Optimasi Sentimen Google Classroom

  • Fajar Pramono STMIK Nusa Mandiri Jakarta
  • Didi Rosiyadi Universitas Bina Sarana Informatika
  • Windu Gata STMIK Nusa Mandiri
Keywords: N-gram, Information Gain, Particle Swarm Optimization, Naïve Bayes, Google Classroom

Abstract

The use of Learning Management System (LMS) applications made by Google with name Google Classroom since 2015 in junior and senior high schools in Bekasi City helps the learning process become easier. However, its use can have positive and negative effects on students. Google Class Sentiment by integrating N-grams, Information Gain, Particle Swarm Optimization, and Naïve Bayes Classifiers that have never been done by researchers before. From the experiments carried out, N-gram can increase the accuracy of 6.7% and AUC 4%, while using PSO can increase the Accuracy of 9.9% and AUC of 10.4%.

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Published
2019-12-02
Section
Artikel Rekayasa Sistem Informasi