Abstract
Automation of question generation from a text has been one of the focus of research in recent years. In the education field, question generation can be used to assist in the generation of questions to be used as evaluations of learning outcomes. The process of generating questions with different difficulty levels manually is not easy. Firstly, someone must understand the whole matter and then she or he is able to make questions according to the material. Generation of questions in large quantities and various learning materials will certainly require lot of effort and time. Therefore, it is necessary to automate the process of generating the question. This research introduces question generation automation methods based on Bloom's Taxonomy using text analysis. The method proposed in this study yielded an accuracy of 81.35%. The accuracy proves that the proposed method can be used to generate questions automatically
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