Integrasi N-gram, Information Gain, Particle Swarm Optimation di Naïve Bayes untuk Optimasi Sentimen Google Classroom
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 inte...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Ikatan Ahli Informatika Indonesia
2019-12-01
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| Series: | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
| Subjects: | |
| Online Access: | http://jurnal.iaii.or.id/index.php/RESTI/article/view/1119 |
| Summary: | 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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| ISSN: | 2580-0760 |