Analisis Sentimen Ulasan pada Aplikasi E-Commerce dengan Menggunakan Algoritma Naïve Bayes
The rapid development of E-commerce has given rise to many marketplaces in Indonesia such as Tokopedia, Shopee, Lazada. Tokopedia, Shopee and Lazada applications are applications that help sellers and buyers to make sales and purchase transactions for goods and services. Until now, of the three majo...
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| Format: | Article |
| Language: | English |
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Politeknik Negeri Batam
2022-12-01
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| Series: | Journal of Applied Informatics and Computing |
| Subjects: | |
| Online Access: | https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/4725 |
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| author | Bintang Zulfikar Ramadhan Riza Ibnu Adam Iqbal Maulana |
| author_facet | Bintang Zulfikar Ramadhan Riza Ibnu Adam Iqbal Maulana |
| author_sort | Bintang Zulfikar Ramadhan |
| collection | DOAJ |
| description | The rapid development of E-commerce has given rise to many marketplaces in Indonesia such as Tokopedia, Shopee, Lazada. Tokopedia, Shopee and Lazada applications are applications that help sellers and buyers to make sales and purchase transactions for goods and services. Until now, of the three major E-Commerce applications, around 100 million users have downloaded the three E-Commerce applications. With the launch of some of these applications, it has caused a lot of opinions and criticisms from the public. Based on this, a sentiment analysis of the Naïve Bayes algorithm was carried out to find out how the sentiment of users compares to the E-Commerce application on the Google Play Store. This research uses the Knowledge Discovery in Database (KDD) method which consists of 5 stages, namely data selection, preprocessing, transformation, data mining, and evaluation. The data used is a review of 500 E-Commerce applications per each application. At the data mining stage, it is carried out with 3 scenarios data sharing is 80:20, 70:30 and 60:40. The best results were obtained in scenario 1 (80:20) on the Shopee application using the Naïve Bayes algorithm which resulted in an accuracy of 92%, precision of 92.13%, recall of 98.8% and f1-score of 95.35%. |
| first_indexed | 2024-04-12T01:10:52Z |
| format | Article |
| id | doaj.art-3fbaae21694a43c894f679801d0b595e |
| institution | Directory Open Access Journal |
| issn | 2548-6861 |
| language | English |
| last_indexed | 2024-04-12T01:10:52Z |
| publishDate | 2022-12-01 |
| publisher | Politeknik Negeri Batam |
| record_format | Article |
| series | Journal of Applied Informatics and Computing |
| spelling | doaj.art-3fbaae21694a43c894f679801d0b595e2022-12-22T03:54:05ZengPoliteknik Negeri BatamJournal of Applied Informatics and Computing2548-68612022-12-016222022510.30871/jaic.v6i2.47254725Analisis Sentimen Ulasan pada Aplikasi E-Commerce dengan Menggunakan Algoritma Naïve BayesBintang Zulfikar Ramadhan0Riza Ibnu Adam1Iqbal Maulana2Universitas Singaperbangsa KarawangUniversitas Singaperbangsa KarawangUniversitas Singaperbangsa KarawangThe rapid development of E-commerce has given rise to many marketplaces in Indonesia such as Tokopedia, Shopee, Lazada. Tokopedia, Shopee and Lazada applications are applications that help sellers and buyers to make sales and purchase transactions for goods and services. Until now, of the three major E-Commerce applications, around 100 million users have downloaded the three E-Commerce applications. With the launch of some of these applications, it has caused a lot of opinions and criticisms from the public. Based on this, a sentiment analysis of the Naïve Bayes algorithm was carried out to find out how the sentiment of users compares to the E-Commerce application on the Google Play Store. This research uses the Knowledge Discovery in Database (KDD) method which consists of 5 stages, namely data selection, preprocessing, transformation, data mining, and evaluation. The data used is a review of 500 E-Commerce applications per each application. At the data mining stage, it is carried out with 3 scenarios data sharing is 80:20, 70:30 and 60:40. The best results were obtained in scenario 1 (80:20) on the Shopee application using the Naïve Bayes algorithm which resulted in an accuracy of 92%, precision of 92.13%, recall of 98.8% and f1-score of 95.35%.https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/4725sentiment analysisnaïve bayese-commerce |
| spellingShingle | Bintang Zulfikar Ramadhan Riza Ibnu Adam Iqbal Maulana Analisis Sentimen Ulasan pada Aplikasi E-Commerce dengan Menggunakan Algoritma Naïve Bayes Journal of Applied Informatics and Computing sentiment analysis naïve bayes e-commerce |
| title | Analisis Sentimen Ulasan pada Aplikasi E-Commerce dengan Menggunakan Algoritma Naïve Bayes |
| title_full | Analisis Sentimen Ulasan pada Aplikasi E-Commerce dengan Menggunakan Algoritma Naïve Bayes |
| title_fullStr | Analisis Sentimen Ulasan pada Aplikasi E-Commerce dengan Menggunakan Algoritma Naïve Bayes |
| title_full_unstemmed | Analisis Sentimen Ulasan pada Aplikasi E-Commerce dengan Menggunakan Algoritma Naïve Bayes |
| title_short | Analisis Sentimen Ulasan pada Aplikasi E-Commerce dengan Menggunakan Algoritma Naïve Bayes |
| title_sort | analisis sentimen ulasan pada aplikasi e commerce dengan menggunakan algoritma naive bayes |
| topic | sentiment analysis naïve bayes e-commerce |
| url | https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/4725 |
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