A Combination of Text Similarity And Latent Semantic Analysis (LSA) Methods in Automatic Scoring Essay 
Deddy Atmajaya1, Purnawansyah2, Siti Rahayu3
1Deddy Atmajaya, Faculty of Computer Science, Universitas Muslim Indonesia, Makassar Indonesia.
2Purnawansyah, Faculty of Computer Science, Universitas Muslim Indonesia, Makassar Indonesia.
3Siti Rahayu, Faculty of Computer Science, Universitas Muslim Indonesia, Makassar Indonesia.
Manuscript received on 02 September 2019 | Revised Manuscript received on 12 September 2019 | Manuscript Published on 23 September 2019 | PP: 1432-1434 | Volume-8 Issue-5C, May 2019 | Retrieval Number: E12060585C19/19©BEIESP | DOI: 10.35940/ijeat.E1206.0585C19
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Description of type exam (essay) is considered by many experts as the most appropriate test to reap the results of a complex learning activities, because essay writing will involve the student’s ability to remember, organize, express, and integrate the ideas of the students. Just to correct the essay exam results, requiring a longer time if done manually because most do by reading an essay one by one. So that, lecturers needs to spend a lot of time to assess the answers of student’s exam. Therefore, in implementation, automatic scoring system is needed on the answer essay exam. Automated essay assessment method used in this study is a combination of Text Similarity and Latent Semantic Analysis (LSA) to look for a match and similarity level student answers with the answer key that has previously been inputted into the system. Data used in this test is 15 students with each student to answer 5 questions. Data obtained from subjects essay Basis Data I. The correlation results of that two assessment shows grades 0,946085 with an average increment of 2,08. Which means the results of the assessment system is not much different from the results of the assessment of the lectures, so that the automatic scoring system can be applied to essay type exam.
Keywords: Automatic Scoring Essay, Text Similarity, Latent Semantic Analysis.
Scope of the Article: Data Mining Methods, Techniques, and Tools