The Similarity of Essay Examination Results using Preprocessing Text Mining with Cosine Similarity and Nazief-Adriani Algorithms

Article History: Received: 10 November 2020; Revised: 12 January 2021; Accepted: 27January 2021; Published online: 05April 2021 Abstract. Exams are one way to measure the level of students' ability to participate in learning. One type of exam given to students is the essay type. This study focuses on making automatic assessments for essay-type exams using cosine similarity. This method has several stages such as folding Case, tokenizing, filtering, stemming, analyzing, weighing of words in documents with cosine similarity. The stemming process uses the Nazief & Adriani algorithm. The results of this study are to conclude that the choice of words that are considered as keywords in the answer key greatly affects the results of the system's assessment. This is evidenced by testing applying the cosine law of 89.5%. However, there are several types of questions that are significantly different because there are unique characters in the database and answer keys that do not contain keywords that match the correct answer.