Klasifikasi Komponen Argumen Secara Otomatis pada Dokumen Teks berbentuk Esai Argumentatif

By automatically recognize argument component, essay writers can do some inspections to texts that they have written. It will assist essay scoring process objectively and precisely because essay grader is able to see how well the argument components are constructed. Some reseachers have tried to do argument detection and classification along with its implementation in some domains. The common approach is by doing feature extraction to the text. Generally, the features are structural, lexical, syntactic, indicator, and contextual. In this research, we add new feature to the existing features. It adopts keywords list by Knott and Dale (1993). The experiment result shows the argument classification achieves 72.45% accuracy. Moreover, we still get the same accuracy without the keyword lists. This concludes that the keyword lists do not affect significantly to the features. All features are still weak to classify major claim and claim, so we need other features which are useful to differentiate those two kind of argument components.