Analysis of the SVM Method to Determine the Level of Online Shopping Satisfaction in the Community
DOI:
10.33395/sinkron.v8i2.12261Keywords:
Confusion Matrix, Data Mining, Online Shopping, Orange, Roc Analysis, Support Vector Machine (SVM)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
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Copyright (c) 2023 Arini Mawaddah, Muhammad Halmi Dar, Gomal Juni Yanris

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.