Muhammad Irfan, . (2022) ANALISIS SENTIMEN PADA ULASAN APLIKASI SAMSAT MOBILE JAWA BARAT (SAMBARA) MENGGUNAKAN ALGORITMA NAIVE BAYES CLASSIFIER DENGAN SELEKSI FITUR CHI SQUARE. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
The Sambara application is an innovation for motor vehicle tax payment services in the West Java area made by the West Java Bapenda. With the presence of Sambara, it is hoped that it will accelerate the obligation to pay the annual vehicle tax. The success of the application can be seen from the many user reviews after using the application. In this study, a sentiment analysis process will be carried out by classifying user reviews of the Sambara application into positive sentiment and negative sentiment. The data used is the review data of the Sambara application on the Indonesian-language Play Store from April 20 to December 31, 2021. This study uses the Naïve Bayes Classifier algorithm and Chi Square feature selection with a significance level of 0.01 to 0.99. Then the distribution of training data and test data with a ratio of 80:20, the results of the study using the chi square feature selection with a critical value of 0.837 at a significance level of 0.36 and the number of selected features as many as 244 features getting the highest accuracy value of 94.4%, specificity 93.5%, and recall 95.3%.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 1810511039] [Pembimbing 1: Didit Widiyanto] [Pembimbing 2: Jayanta] [Penguji 1: Bayu Hananto] [Penguji 2: Nurul Chamidah] |
| Uncontrolled Keywords: | Sambara, Naïve Bayes Classifier, Chi Square |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Muhammad Irfan |
| Date Deposited: | 10 Aug 2022 06:32 |
| Last Modified: | 10 Aug 2022 06:32 |
| URI: | http://repository.upnvj.ac.id/id/eprint/19859 |
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