Analisis Sentimen Layanan Shopeefood Pada Twitter Dengan Metode K-Nearest Neighbor, Support Vector Machine, dan Decision Tree
DOI:
https://doi.org/10.35316/jimi.v7i2.95-106Kata Kunci:
K-Nearest Neighbor, Support Vector Machine, Decision Tree, Analysis, ShopeefoodAbstrak
Transportation is an infrastructure that connects one point to another. In an era like this, people's needs are getting wider, not just about delivering people, but more than that, for example delivering goods, groceries, or food and so on. Transportation that is supported by smartphones and the result of a combination of transportation services with communication technology is called online transportation. One of the online transportation that is on the rise is ShopeeFood. ShopeeFood is an online transportation that focuses on services that deliver food to its customers. The purpose of this study was to obtain classification results according to the level of accuracy of the Twitter community's perception of shopeeFood services. This study uses three methods, namely KNN, SVM and Decision Tree. The data used is twitter data obtained by crawling using RapidMiner software. Based on the test results, it was found that the KNN method has a higher value than the other methods with an accuracy of 71.49%, precision of 72.86% and recall of 76.94%.
Unduhan
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