Indriani, Fauzillah (2021) Analisis Sentimen Data Twitter Opini ShopeePayLater Menggunakan Metode Naive Bayes Classifier. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pandemi Covid-19 mengakibatkan masyarakat melakukan transaksi berbelanja secara online dari pada offline untuk mencegah tersebarnya virus Covid-19. Adanya fitur paylater tentu saja masyarakat Indonesia lebih dimudahkan dalam berbelanja dengan mengambil pinjaman dana. Shopee merupakan salah satu marketplace yang mempunyai layanan paylater yaitu ShopeePayLater yang merupakan salah satu metode pembayaran dalam platform Shopee yang memungkinkan pengguna Shopee untuk berbelanja dan baru dilakukan pembayaran di kemudian hari saat jatuh tempo. Setiap pengguna baru ShopeePayLater pasti ingin mengetahui bagaimana respon pengguna sebelumnya sebagai bentuk testimoni setelah menggunakan fitur tersebut melalui twitter berupa tweets. Sehingga perlu dilakukan analisis sentimen untuk mengetahui opini masyarakat dengan adanya ShopeepayLater menggunakan metode Naïve Bayes Classifier sehingga dapat memberikan informasi yang berguna bagi pihak Shopee maupun masyarakat terhadap layanan ShopeePayLater. Perhitungan ketepatan klasifikasi dilakukan dengan menggunakan G-Mean dan AUC, karena sentimen data tweets masuk dalam kategori data imbalance menghasilkan nilai G-Mean sebesar 64,79% dan AUC sebesar 66,12%.
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The Covid-19 pandemic effect on online shopping transactions rather than offline in order to prevent the spread of the Covid-19 virus. The paylater service help Indonesian become more easier to shop by taking out a loan. Shopee is one of the marketplaces that has a paylater service, namely Shopee PayLater, which is one of the payment methods on the Shopee platform that allows Shopee users to shop and only pay at a later date when it is due. Every new ShopeePayLater user want to know how the previous user responded as a form of testimony after using this feature via Twitter in the form of tweets. So it is necessary to conduct a sentiment analysis to find out public opinion with the existence of ShopeepayLater using the Naïve Bayes Classifier method so that it can provide useful information for Shopee and the public regarding ShopeePayLater services. Calculation of classification accuracy is carried out using G-Mean and AUC, because the sentiment of the tweets data is included in the imbalance data category resulting in a G-Mean value of 64,79% and AUC of 66,12%.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Analisis Sentimen, Naïve Bayes Classifier, ShopeepayLater,Twitter,Sentiment Analysis |
| Subjects: | T Technology > T Technology (General) > T57.5 Data Processing |
| Divisions: | Faculty of Vocational > 49501-Business Statistics |
| Depositing User: | Fauzillah indriani |
| Date Deposited: | 15 Aug 2021 03:35 |
| Last Modified: | 29 Aug 2021 08:15 |
| URI: | http://repository.its.ac.id/id/eprint/86510 |
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