@thesis{thesis,
		author={Taufiqurrahman  Bagoes Ihsan},
		title ={Analisis Sentimen Produk Kosmetik Melalui Online Review Dengan Metode Support Vector Machine},
		year={2022},
		url={https://sipora.polije.ac.id/15064/},
		abstract={During the COVID-19 pandemic, all activities in society have switched to using the internet, including shopping for daily necessities. In addition to daily necessities, cosmetics are also items that are often purchased during the COVID-19 pandemic. The shift from purchasing cosmetic goods to online causes consumer uncertainty to buy goods because the reviews left by other consumers are too many so that it takes a long time to read them, while if only part of the reviews are read, the information obtained is biased. Therefore we need a model that can classify sentiments, especially reviews in Indonesian. This research was conducted using the Support Vector Machine classification method with the selection of the Binary Particle Swarm Optimization feature. By using the Support Vector Machine, the score accuracy is 78% and the results of the system evaluation are 78% precision and 85% recall.}
		}