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Yolanda, Nedya
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Computer Science & IT

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Analisis Sentimen Analisis Sentimen Popularitas Aplikasi Moodle dan Edmodo Menggunakan Algoritma Support Vector Machine Yolanda, Nedya; Santi, Indyah Hartami; Permadi, Dimas Fanny Hebrasianto
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 3 No 1 (2022): Oktober 2022 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i1.3313

Abstract

Pandemic Covid-19 in Indonesia has caused face-to-face learning to be temporarily suspended, resulting in online learning. Indirectly encouraging an E-Learning application to have a high usage rate and number of downloads on the Play Store. The best application is always given to the application with highest number of downloads and ratings on the Play Store. Meanwhile comments from users need to be taken into account because many E-learning applications have the same number of downloads and ratings Moodle and Edmodo, therefore a sentiment analysis of the popularity of Moodle and Edmodo is carried out using the SVM Algorithm. User comments on Play Store are used as data source. From 250 data scraping results from user comments, the preprocessing process and TF IDF extraction were carried out. Based on results of testing using confusion matrix it can be concluded that user sentiment the Edmodo application has a better percentage compared to the Moodle application which can be shown by the emergence of a positive sentiment 67% with accuracy 84% and precision 93%, recall 82% and f1-score 87%. Moodle application has a negative sentiment percentage 67% with an accuracy 82% and a precision test of 79%, 100% recall and 88% f1-score.
Co-Authors Dimas Fanny Hebrasianto Permadi Santi, Indyah Hartami