M Ali Fauzi, Djoko Cahyo Utomo, Eko Sakti Pramukantoro, Budi Darma Setiawan
E-Learning is one of the great innovations in teaching methods. In the E-learning, there are several assessment methods; one of them is the essay examination. Essay assessment takes a long time if corrected manually. Therefore, researches on automatic essay scoring have been growing rapidly in recent years. The method that is usually used for automatic essay scoring is Cosine Similarity by utilizing bag of words as the feature extraction. However, the feature extraction by using bag of words did not consider to the order of words in a sentence. Meanwhile, the order of words in an essay has an important role in the assessment. In this study, an automatic essay scoring system based on n-gram and cosine similarity was proposed. N-gram was used for feature extraction and modified to split by word instead of by letter so that the word order would be considered. Based on evaluation results, this system got the best correlation of 0.66 by using unigram on questions that do not consider the order of words in the answer. For questions that consider the order of the words in the answer, bigram has the best correlation value by 0.67. © 2017 Association for Computing Machinery.
Fakultas Ilmu Komputer, Universitas Brawijaya, Malang, Indonesia
