IMPLEMENTASI METODE NATURAL LANGUAGE PROCESSING (NLP) PADA AUTOMATED ESSAY SCORING (AES)

Evaluation in the educational process is necessary to determine the success rate of students' learning. One of the methods used is through essay exams. Challenges arise during the essay exam assessment process as it requires significant time and effort. Additionally, there are issues with inconsistent grading, such as differences in scores despite similar meaning in the answers. Therefore, a practical and efficient method for essay answer assessment is needed. Information technology can be applied in this case using Transformer networks. The method used is to assess essay answers based on the semantic similarity between the key answers and the students' answers through the semantic similarity task. This research aims to implement an NLP model trained in Indonesian, namely IndoBERT, in Automated Essay Scoring. The results of the research, from 10 sets of essay questions, showed a Quadratic Weighted Kappa score ranging from a minimum of 0.17771 to a maximum of 0.80654, and a Root Mean Square Error ranging from a minimum of 1.6329 to a maximum of 5.0197.