Perbandingan Metode Klasifikasi Support Vector Machine dan Naïve Bayes untuk Analisis Sentimen pada Ulasan Tekstual di Google Play Store
| Main Authors: | Ilmawan, Lutfi Budi, Mude, Muhammad Aliyazid |
|---|---|
| Format: | Article info application/pdf Journal |
| Bahasa: | eng |
| Terbitan: |
Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia
, 2020
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| Subjects: | |
| Online Access: |
http://jurnal.fikom.umi.ac.id/index.php/ILKOM/article/view/597 http://jurnal.fikom.umi.ac.id/index.php/ILKOM/article/view/597/pdf http://jurnal.fikom.umi.ac.id/index.php/ILKOM/article/downloadSuppFile/597/189 |
Daftar Isi:
- In this research, the performance of SVM classification method will be compared with other classification methods, by using the Naïve Bayes classification method. Naïve Bayes classification method is a light classification method and has a high accuracy if applied to the text classification according to some previous studies. The accuracy of the classifier is measured using the K-fold cross validation method whose results will be tabulated in a confusion matrix table, with a value of K = 3. In this study, the data processed are textual reviews of applications in the Indonesian language Google Play Store obtained from previous research. The test results obtained from the 3-fold cross-validation method produce that SVM Classifier has a higher value of accuracy when compared with the accuracy of the Naïve Bayes classifier, the SVM classifier gets an accuracy of 81.46% and Naïve Bayes classifier by 75.41%.