Penerapan Text Mining Untuk Klasifikasi Judul Berita Hoax Vaksinasi COVID-19 Menggunakan Algoritma Support Vector Machine - Aditya Wijaya; Chaerur Rozikin; Betha Nurina Sari (Peneliti.net, 2022)
Covid-19 has become a worldwide pandemic and eventually spread to Indonesia. The government is taking preventive measures by COVID-19 vaccination program. People looking for this vaccination information program through online media. However, hoax news about the covid-19 vaccination is spreading more and more because of the lack of ability of the public to distinguish between valid news and hoaxes. This makes hoax news increase its spread quickly. So this study will utilize text mining in classifying hoax news texts for the Covid-19 vaccine using 4 kernels of Support Vector Machine. The data collected from 2 sources, hoax news title data are collected from Kominfo and non-hoax news title data are collected from Kompas. The research methodology used is Knowledge Discovery in Databases. The data will go through several preprocessing stages before testing the model. The results show that the best test results for the model obtained by the linear kernel in the 80:20 data split scenario which after going through an evaluation using a confusion matrix produces an accuracy value of 89,43%, precision 94,93%, recall 87,20%, and f1-score 90,90%.