Implementasi Natural Language Processing (NLP) dan Algoritma Cosine Similarity dalam Penilaian Ujian Esai Otomatis

Authors

  • Daniel Oktodeli Sihombing Institut Teknologi dan Bisnis Sabda Setia, Pontianak

DOI:

https://doi.org/10.30865/json.v4i2.5374

Keywords:

Natural Language Processing, Cosine Similarity, Document Similarity, Evaluation, Essay

Abstract

Evaluation of learning is an activity that is routinely carried out in the lecture process. The essay exam is a test in the form of questions that aim so that the answers given are in the form of descriptions based on student’s understanding in accordance with what they know. The results of the various answers are a separate consideration in correcting whether the answer is in accordance with the answer key or not. This resulted in each question on the essay exam having its own weight which would later be added up cumulatively to get a total score. This study implements Natural Language Processing (NLP) and Cosine Similarity algorithms to automatically assess essay exams. Document Similarity is one of the tasks in Natural Language Processing (NLP) to check the degree of document similarity. The algorithm used to check the level of similarity is Cosine Similarity which uses two vectors to measure the degree of similarity of documents with the results ranging from 0 to 1. Processing student answer data for three essay questions gets the expected results. The results of the Cosine Similarity calculation in question no 1 show that M3 students have answers with a similarity level of 90.58%. Whereas for question no 2 M1 students had answers with a similarity level of 87.71% and finally for question no 3 M1 students had answers with a similarity level of 76.70%.

References

I. Mufiid, S. Lestanti, and N. Kholila, “APLIKASI PENILAIAN JAWABAN ESAI OTOMATIS MENGGUNAKAN METODE SYNONYM RECOGNITION DAN COSINE SIMILARITY BERBASIS WEB,†Jurnal Mnemonic, vol. 4, no. 2, pp. 31–37, Sep. 2021, doi: 10.36040/mnemonic.v4i2.4067.

G. G. Chowdhury, “Natural language processing,†Annual Review of Information Science and Technology, vol. 37, no. 1, pp. 51–89, Jan. 2005, doi: 10.1002/aris.1440370103.

E. D. Liddy, “Natural Language Processing,†in Encyclopedia of Library and Information Science, 2nd Ed, New York: Marcel Decker, Inc, 2001.

E. L. Amalia, A. J. Jumadi, I. A. Mashudi, and D. W. Wibowo, “Analisis Metode Cosine Similarity Pada Aplikasi Ujian Online Otomatis (Studi Kasus JTI POLINEMA),†Jurnal Teknologi Informasi dan Ilmu Komputer, vol. 8, no. 2, p. 343, Mar. 2021, doi: 10.25126/jtiik.2021824356.

H. Arfandy and I. A. Musdar, “Rancang Bangun Sistem Cerdas Pemberian Nilai Otomatis Untuk Ujian Essai Menggunakan Algoritma Cosine Similarity,†Inspiration: Jurnal Teknologi Informasi dan Komunikasi, vol. 10, no. 2, p. 123, Dec. 2020, doi: 10.35585/inspir.v10i2.2580.

H. Rumapea, “DETEKSI KEMIRIPAN ARTIKEL MELALUI KEYWORDS DENGAN METODE FUZZY STRING MATCHING DALAM NATURAL LANGUAGE PROCESSING,†METHOMIKA Jurnal Manajemen Informatika dan Komputerisasi Akuntansi, vol. 5, no. 1, pp. 60–66, Apr. 2021, doi: 10.46880/jmika.Vol5No1.pp60-66.

I. Mawanta, T. S. Gunawan, and W. Wanayumini, “Uji Kemiripan Kalimat Judul Tugas Akhir dengan Metode Cosine Similarity dan Pembobotan TF-IDF,†JURNAL MEDIA INFORMATIKA BUDIDARMA, vol. 5, no. 2, p. 726, Apr. 2021, doi: 10.30865/mib.v5i2.2935.

A. R. S. Nasution, “Identifikasi Permasalahan Penelitian,†ALACRITY : Journal of Education, pp. 13–19, Jul. 2021, doi: 10.52121/alacrity.v1i2.21.

Salmaa, “Studi Literatur: Pengertian, Ciri-Ciri, dan Teknik Pengumpulan Datanya,†https://penerbitdeepublish.com/studi-literatur/, Jun. 07, 2021.

E. Commission et al., Natural language processing for public services. Publications Office of the European Union, 2022. doi: doi/10.2799/304724.

Harshith, “Text Preprocessing in natural language processing using Python,†https://towardsdatascience.com/text-preprocessing-in-natural-language-processing-using-python-6113ff5decd8, Nov. 21, 2019.

A. R. Lahitani, “Automated Essay Scoring menggunakan Cosine Similarity pada Penilaian Esai Multi Soal,†Jurnal Kajian Ilmiah, vol. 22, no. 2, pp. 107–118, May 2022, doi: 10.31599/jki.v22i2.1121.

Rianita Giovanni Katryn, “Text Preprocessing: Tahap Awal dalam Natural Language Processing (NLP),†https://medium.com/mandiri-engineering/text-preprocessing-tahap-awal-dalam-natural-language-processing-nlp-bc5fbb6606a, Sep. 28, 2020.

P. M. Prihatini, “IMPLEMENTASI EKSTRAKSI FITUR PADA PENGOLAHAN DOKUMEN BERBAHASA INDONESIA,†JURNAL MATRIX, vol. 6, no. 3, pp. 174–178, Nov. 2016, [Online]. Available: http://ojs.pnb.ac.id/index.php/matrix/article/view/151

S. Shevira, I. M. A. D. Suarjaya, and P. W. Buana, “Pengaruh Kombinasi dan Urutan Pre-Processing padaTweets Bahasa Indonesia,†JITTER - Jurnal Ilmiah Teknologi dan Komputer, vol. 3, no. 2, Aug. 2022, [Online]. Available: https://ojs.unud.ac.id/index.php/jitter/article/view/88613

Y. Miftahuddin, J. Pardede, and R. Dewi, “Penerapan Algoritma Lemmatization pada Dokumen Bahasa Indonesia,†MIND Journal, vol. 3, no. 2, pp. 47–56, Feb. 2019, doi: 10.26760/mindjournal.v3i2.47-56.

A. Apriani, H. Zakiyudin, and K. Marzuki, “Penerapan Algoritma Cosine Similarity dan Pembobotan TF-IDF System Penerimaan Mahasiswa Baru pada Kampus Swasta,†Jurnal Bumigora Information Technology (BITe), vol. 3, no. 1, pp. 19–27, Jul. 2021, doi: 10.30812/bite.v3i1.1110.

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Published

2022-12-31

How to Cite

Sihombing, D. O. (2022). Implementasi Natural Language Processing (NLP) dan Algoritma Cosine Similarity dalam Penilaian Ujian Esai Otomatis. Jurnal Sistem Komputer Dan Informatika (JSON), 4(2), 396–406. https://doi.org/10.30865/json.v4i2.5374

Issue

Vol. 4 No. 2 (2022): Desember 2022

Section

Articles

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