KLASIFIKASI ULASAN PENGGUNA MENGGUNAKAN METODE SUPPORT VECTOR MACHINE PADA APLIKASI HALODOC - Fachran Sandi (2023)
Due to the COVID-19 outbreak, all services have switched to online. The Halodoc application is a popular telemedicine application in Indonesia that provides online health services. The Halodoc application needs improvement to reduce its shortcomings in providing information to users. Sentiment analysis can carry out user classification. In this study, 2 classes will be used, namely the sentiment class, namely positive and negative, as well as the category class, where the category class is taken from the attributes of ISO 9126, which is a software standard made by ISO and IEC as a measurement standard for software quality assurance. This research will create two models: a model with two classes for the sentiment class and a multiclass model for the category class; each model will use the support vector machine algorithm and the TF-IDF algorithm. The results of the classification of the Halodoc application for the sentiment class obtained a result of 96.02% with a linear kernel, and the results for the class category used the one vs. rest method, and the results for the sigmoid kernel were obtained at 78.97%.