Automated Essay Scoring Using Natural Language Processing And Text Mining Method
Gunawansyah Gunawansyah, Riska Rahayu, Nurwathi Nurwathi, Bambang Sugiarto, Gunawan Gunawan
Abstract
The use of technology really helps to maximized the effectiveness and efficiency of work expecially in the education field. Elearning is the concept of education that has begun to be widely implemented at this covid-19 pandemic to avoid the spread of transmission through social distancing. One of elearning types is essay but for large participants, it need much effort for evaluate by human rater. The inconsistency of assessment by the rater due to fatigue can also affect the quality of the assessment. Developing a system that can learn and understand on its own without having to be repeatedly programmed by humans used machine learning and computational linguistics to study the interaction between computers and human natural language used natural language processing proposed in this research. Natural language processing and text mining methods are able to provide a good assessment which is influenced by several processes, namely tokenization, stopword, stemming and support with the number of keywords, and the synonym of more complex keywords. The automated essay scoring system is proven to provide consistent and objective assessments and is able to approach human raters assessments.