Aditya Samiaji, . (2022) ANALISIS SENTIMEN REVIEW APLIKASI BERITA ONLINE PADA GOOGLE PLAY MENGGUNAKAN METODE NAÏVE BAYES STUDI KASUS: TRIBUNNEWS.COM. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
The Tribunnews application is an online news application that has been downloaded by more than 500 thousand users. The development of handheld cellular technology has had a huge impact on mankind in the use of smartphones and the internet. The number of people who search for news in online makes people download online news applications. News has become a daily information need for the public to know the development of various events. Tribunnews.com is one of the online news portals that has many downloaders. So that the author conducts sentiment analysis research by classifying sentiment using the Naïve Bayes method. The test results of several models using feature selection and not using feature selection, the highest accuracy is the model with feature selection and oversampled undersampled has an accuracy value of 0.96; precision value of 0.97; recall value of 0.98; specificity value of 0.88; and an AUC value of 0.93.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 1810511052] [Pembimbing 1: Bayu Hananto] [Pembimbing 2: Desta Sandya Prasvita] [Penguji 1: Henki Bayu Seta] [Penguji 2: Nurul Chamidah] |
| Uncontrolled Keywords: | Sentiment Analysis, Tribunnews.com, Naïve Bayes, Classifying, Feature Selection. |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Aditya Samiaji |
| Date Deposited: | 23 Aug 2022 02:21 |
| Last Modified: | 23 Aug 2022 02:21 |
| URI: | http://repository.upnvj.ac.id/id/eprint/19743 |
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