Tyas, Salsabila Mazya Permataning and Rintyarna, Bagus Setya and Suharso, Wiwik (2022) (Similarity) The Impact of Feature ExtractiontoNaïve Bayes Based Sentiment Analysis on Review Dataset of Indihome Services. Digital Zone: Jurnal Teknologi Informasi dan Komunikasi.
![[img]](http://repository.unmuhjember.ac.id/style/images/fileicons/text.png) |
Text
10 The Impact of Feature.pdf.pdf Download (490kB) |
Abstract
Indihome is a product of PT Telekomunikasi Indonesia as an internet service provider or internet service provider (ISP) in Indonesia. Every product or service offered to the public certainly has its advantages and disadvantages, as well as Indihome. From the advantages and disadvantages of Indihome services, wecan do a technique, namely sentiment analysis. In this study, sentiment analysis was carried out regarding public responses or reviews about IndiHome services on Twitter social media. This study usesa comparison of TF-IDF and Word2Vecfeature extraction, and the classification method used is the nave Bayes classifier. The accuracy results obtained in this study were 96% using the TF-IDF feature extraction and testing was carried out using an unseen data test that was selected randomly resulting in an accuracy of 92%. While the accuracy value obtained by using the Word2Vec feature extraction is 60% by testing using unseen test data that was selected randomly resulting in an accuracy value of 44%.
| Item Type: | Peer Review |
|---|---|
| Uncontrolled Keywords: | Sentiment Analysis; Indihome; TF-IDF; Word2Vec; Naïve Bayes |
| Subjects: | 600 Technology and Applied Science > 620 Engineering |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering (S1) |
| Depositing User: | Bagus Setya Rintyarna |
| Contact Email Address: | bagus.setya@unmuhjember.ac.id |
| Date Deposited: | 23 Dec 2022 01:38 |
| Last Modified: | 24 Jan 2023 04:34 |
| URI: | http://repository.unmuhjember.ac.id/id/eprint/15687 |
Actions (login required)
 |
View Item |