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  3. Rika Rosnelly
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Please use this identifier to cite or link to this item: http://repository.potensi-utama.ac.id/jspui/jspui/handle/123456789/5613
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dc.contributor.authorRosnelly, Rika-
dc.date.accessioned2023-04-27T04:21:26Z-
dc.date.available2023-04-27T04:21:26Z-
dc.date.issued2021-04-05-
dc.identifier.urihttp://repository.potensi-utama.ac.id/jspui/jspui/handle/123456789/5613-
dc.descriptionAt this time the world is feeling the impact of the Coronavirus Disease (Covid 19) pandemic. Indonesia is one of the countries that has been badly affected, especially in the field of education, causing schools and universities to be unable to carry out the face-to-face learning process. Learning is transferred by applying online methods or online learning using media such as google classroom, zoom, WhatsApp, and other methods[1]. The development of technology in the digital era as it is today certainly brings many benefits to society and one of them is education institutions[2]. The application of online learning methods is also applied to the implementation of the Mid-Semester Examination (UTS) and the Final Semester Examination (UAS). Exam questions given to students can be in the form of essays or multiple choices. Multiple choice questions are filled by selecting answers from those provided. It is different from essay questions which require students to provide the answers they have according to the student's understanding. The answers produced by students are not solely right or wrong, but there is also a possibility that it is close to correct. As an application, if the perfect answer is 100 then the wrong answer is given a value of 0 and the close answer is given a value of 40, and so on. Therefore, Previous research was conducted by Rahimi Fitri and Arifin Noor Asyikin by applying the Cosine Similarity algorithm to the student essay exam assessment cases. The Prepossessing Text Mining stage, precisely at the stemming stage, does not apply an algorithm, so the process of determining the root word is ineffective and does not have criteria[3]. The stemming process influences the accuracy of information retrieval. Stemming is done by removing the affixes contained in words. Another study was conducted by Saipech, Pongsakorn, and Pusadee in the case of detecting similarity in test results for Thai by applying the Cosine Similarity algorithm. In this study, the DCB approach was applied to Thai for the word segmentation process. Prepossessing in this study was limited to Word Segmentation and Stop word elimination[4].en_US
dc.description.abstractExams 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.en_US
dc.publisherTurkish Journalen_US
dc.relation.ispartofseriesVol.12 No.3 (2021);1415-1422-
dc.subjectautomatic, stemming, assessment, database, answer keyen_US
dc.titleThe Similarity of Essay Examination Results using Preprocessing Text Mining with Cosine Similarity and Nazief-Adriani Algorithmsen_US
dc.typeOtheren_US
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