Puspita, Nabila Ayu (2024) PENGARUH PENGGUNAAN SELEKSI FITUR CHI SQUARE DAN INFORMATION GAIN TERHADAP PERFORMANSI ALGORITMA NAÏVE BAYES CLASSIFIER PADA ANALISIS SENTIMEN ULASAN APLIKASI GOOGLE PLAY STORE (STUDI KASUS : APLIKASI MY F&B ID). Undergraduate thesis, UPN Vetera Jawa Timur.
|
Text (COVER)
19081010006_Cover.pdf Download (1MB) | Preview |
|
|
Text (BAB 1)
19081010006_Bab1.pdf Download (281kB) | Preview |
|
![[img]](http://repository.upnjatim.ac.id/style/images/fileicons/text.png) |
Text (BAB 2)
19081010006_Bab2.pdf Restricted to Registered users only until 22 January 2026. Download (567kB) |
|
|
Text (BAB 3)
19081010006_Bab3.pdf Restricted to Registered users only until 22 January 2026. Download (411kB) |
|
|
Text (BAB 4)
19081010006_Bab4.pdf Restricted to Registered users only until 22 January 2026. Download (1MB) |
|
|
Text (BAB 5)
19081010006_Bab5.pdf Download (154kB) | Preview |
|
|
Text (DAFTAR PUSTAKA)
19081010006_Daftar_pustaka.pdf Download (133kB) | Preview |
Abstract
In the era of increasingly sophisticated technology, it encourages all aspects of life to participate in its development, one of which is in the field of food or culinary. The sophistication of this is making food companies compete to create mobile applications to make it easier for people to buy the products they sell. One form of real implementation of this is with the My F&B ID Application. On the Google Play Store, apart from being able to download applications, people can also give opinions on these applications. Opinions in the form of giving feedback, criticism, praise, complaints about the application. . So in this study, sentiment analysis will be carried out on My F&B ID application reviews on Google Playstore. This research uses the Naïve Bayes Classifier algorithm with Chi Square and Information Gain feature selection with a dataset comparison for training data and test data of 80:20, 70:30, 60:40. Dataset comparison is done to determine the performance of the accuracy value of each classification model. The results of the study obtained the highest accuracy value produced by the Multinomial Naïve Bayes Classifier Classification model with Chi Square Feature Selection (α=0.5) and Multinomial Naïve Bayes Classifier Classification without Feature Selection with a value of 85%.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Contributors: |
|
||||||||||||
| Subjects: | Q Science > QA Mathematics > QA76.6 Computer Programming Q Science > QA Mathematics > QA76.625 Internet Programming T Technology > T Technology (General) |
||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | Nabila Ayu Puspita | ||||||||||||
| Date Deposited: | 23 Jan 2024 01:59 | ||||||||||||
| Last Modified: | 23 Jan 2024 01:59 | ||||||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/20506 |
Actions (login required)
 |
View Item |