Analysis of the Level of Public Satisfaction on the Tiktok Application as an E-Commerce
DOI:
10.33395/sinkron.v8i4.13040Keywords:
Keywords: TikTok App; K-Nearest Neighbor (kNN); Decision Trees; Confusion Matrix; Ecommerce; ROC AnalysisAbstract
Abstract: Online shopping has become one of the alternatives used by society today. This happens because doing online shopping saves a lot of time. There are many online shops in Indonesia and are used by many people, such as Shopee, Lazada and Tokopedia. But now there is an application that initially only acted as a social media platform, but now also doubles as an E-commerce application, namely TikTok. TikTok has now become an E-commerce application. The prices given are also very cheap and there are lots of promotions given to customers. But there are still some people who don't want to shop online on TikTok on the grounds that the goods are not good. So from these 2 things, research needs to be made to determine the level of public satisfaction with the TikTok application as an E-commerce. The aim of this research is to see how many people are satisfied shopping on TikTok. This research was carried out using a classification model in data mining using the K-Nearest Neighbor (kNN) method and the Decision Tree method. The classification results obtained were 119 community data (for representation of 96.74%) and for people who were dissatisfied with the TikTok application as an E-commerce it was 4 community data (for representation of 3.25%). These results provide the conclusion that many people are satisfied shopping on the TikTok application as E-commerce
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