Arini Mawaddah, NPM 2007100003 (2023) ANALYSIS OF THE SVM METHOD TO DETERMINE THE LEVEL OF ONLINE SHOPPING SATISFACTION IN THE COMMUNITY. Tugas_ Akhir (Artikel) Sinkron : Jurnal dan Penelitian Teknik Informatika, 8 (2). pp. 838-855. ISSN 2541-2019 (e-ISSN) / 2541-044X (p-ISSN)
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Abstract
Online shopping is an activity of buying goods done online (virtual). This online shopping process is done because it doesn't waste a lot of time. With online shopping, it is very easy for people. Just need open mobile phone view and select the desired item and then order goods and goods will be delivered to the house. But online shopping sometimes also has drawbacks which are one of the reasons people don't want to shop online, such as long shipping times, expensive shipping costs. Therefore a study was made about the level of public satisfaction in online shopping. Researchers will make a data classification about the level of public satisfaction in online shopping using the SVM method. This study aims to see the level of public satisfaction with online shopping, many or nope satisfied people when shopping online. The first step is to collect data that will be used in the data mining process. After that, data preprocessing will be carried out planning the design of the SVM method and finally the prediction process to get Classification results. Then the classification results obtained using the SVM method in data mining show that 34 people are satisfied with online shopping (for a representation result of 59.65%), 23 people are dissatisfied with online shopping (for a representation result of 40.35%). These results state that there are still many people who are satisfied with shopping online and there are some people who are dissatisfied with online shopping. Keywords: Confusion Matrix, Data Mining, Online Shopping, Orange, Roc Analysis, Support Vector Machine (SVM)
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Confusion Matrix, Data Mining, Online Shopping, Orange, Roc Analysis, Support Vector Machine (SVM) |
| Subjects: | H Social Sciences > HF Commerce T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > Informatika Komputer |
| Depositing User: | Unnamed user with email repository@ulb.ac.id |
| Date Deposited: | 01 Nov 2023 03:33 |
| Last Modified: | 01 Nov 2023 03:33 |
| URI: | http://repository.ulb.ac.id/id/eprint/456 |
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