MODEL PENILAIAN ESAI OTOMATIS MENGGUNAKAN ALGORITMA RABIN-KARP, DICE COEFFICIENT SIMILARITY DAN SYNONYM RECOGNITION STUDI KASUS PADA UNIVERSITAS BUDI LUHUR

  • Heru Saputro Universitas Budi Luhur
  • Utomo Budiyanto Universitas Budi Luhur
Keywords: Assessment, Essay, Rabin-Karp Algorithm, Dice Coefficient Similarity, Synonym Recognition

Abstract

The exam is one way to find out the results of students' material understanding abilities from the teaching and learning process taught by educators. In general, the exam system itself has several types of questions, namely multiple choice questions and essays. Implementation of automatic exam assessment is generally only a multiple-choice exam on the e-learning page. One of them is that Budi Luhur University in conducting student exam assessments in the form of multiple choice questions already has an automatic scoring system on the e-learning page. However, there is no automatic system for assessing essays. So for the assessment of essay questions, Budi Luhur University lecturers are still correcting them manually. From the manual essay scoring system it takes quite a long time and is less effective. Based on this background, it is necessary to have a website-based automatic essay assessment system that can assist Budi Luhur University lecturers in assessing student learning outcomes. The method proposed in this study is to use the Rabin-Karp Algorithm, Dice Coefficient Similarity and Synonym Recognition. This study aims to create an automatic essay scoring system that can assist Budi Luhur University lecturers in correcting student learning outcomes. This system can produce the highest accuracy percentage of student grade correction results and is close to the lecturer's manual assessment with an accuracy value of 93.75%.

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References

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Published
2024-01-30
How to Cite
[1]
H. Saputro and U. Budiyanto, “MODEL PENILAIAN ESAI OTOMATIS MENGGUNAKAN ALGORITMA RABIN-KARP, DICE COEFFICIENT SIMILARITY DAN SYNONYM RECOGNITION STUDI KASUS PADA UNIVERSITAS BUDI LUHUR”, SKANIKA, vol. 7, no. 1, pp. 1-11, Jan. 2024.