Hoax Classification Corona Virus (COVID-19) News in Indonesian using the Support Vector Machine (SVM) Method

Abstract

The development of information technology more widely, rapidly and quickly provide convenience to the public in access information. Internet is a container or online media makes the information hasn’t been verified or proved to be true which is rapidly spreading in the community. The purpose of this study is to facilitate in determining the hoax news or facts about corona virus in Indonesia and appoint the performance text mining classification with SVM algorithm. Stages The hoax classification process is carried out with the preprocessing then weighting is carried out using TF-IDF method and classified using the support vector machine algorithm then tested by cross validation and k-folds testing. The data used in this study consisted of 535 text message containing information about facts and news text 425 contains information on hoaxes. The results obtained on testing the highest accuracy to 7 on the k-fold 9 with accuracy of 83.82%. Thus, the SVM algorithm can be used in the classification of Corona Virus Hoax news or COVID-19.