Luthfiana, Lulu and Young, Julio Cristian and Rusli, Andre (2020) Implementasi Algoritma Support Vector Machine dan Chi Square untuk Analisis Sentimen User Feedback Aplikasi. Ultimatics : Jurnal Teknik Informatika, 12 (2). ISSN 2085-4552
Full text not available from this repository.Abstract
In order to adapt with evolving requirements and perform continuous software maintenance, it is essential for the software developers to understand the content of user feedback. User feedback such as bug report could provide so much information regarding the product from user’s point of view, especially parts that need improvements. However, it is often difficult to read all the feedback for products with enormous number of users as manually reading and analyzing each feedback could take too much time and effort. This research aims to develop a model for automatic feedback classification by implementing Support Vector Machine for the classifier’s algorithm and Chi-square method for feature selection. The model is developed using Python programming language and is then evaluated under different scenarios in order to measure its performance. Using a ratio of training and testing set of 80:20, our model achieved 77% accuracy, 50% precision, 55% recall, and 73% F1-score with 6.63 critical value and C=100 and gamma 0.001 as the SVM hyperparameters.
| Item Type: | Article |
|---|---|
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming 500 Science and Mathematic > 510 Mathematics > 519 Probabilities and Applied Mathematics |
| Divisions: | Faculty of Engineering & Informatics > Informatics |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 05 Oct 2021 09:53 |
| Last Modified: | 05 Oct 2021 09:53 |
| URI: | https://kc.umn.ac.id/id/eprint/18539 |
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