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All Journal Majalah Ilmiah Teknologi Elektro Majalah Ilmiah Teknologi Elektro
Komang Nova Artawan
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Perancangan Fitur Deteksi Kemiripan Dokumen Jawaban Tugas Mahasiswa pada Sistem Manajemen Pembelajaran dengan Metode K-Shingling dan Cosine Similarity Komang Nova Artawan; Rukmi Sari Hartati; Yoga Divayana
Majalah Ilmiah Teknologi Elektro Vol 22 No 1 (2023): (Januari - Juni) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2023.v22i01.P06

Abstract

Technology development can be used to support the teaching and learning process so it can runs more effectively and efficiently, and one of the applications that can be used to support this process is the Learning Management System (LMS). LMS provides an integrated platform starting from delivering learning materials to students, and evaluating learning process. The evaluation method that can be done at the LMS is giving assignments to students, and students can do submission by uploading their documents assignment answer. The common problem is many students do plagiarism by duplicate the answers of other students. To overcome these problems, this study will implement feature in Course Assignment Menu in LMS to detect the similarity of student assignment document using K-Shingling and Cosine Similarity methods. The K-Shingling algorithm is used to form shingles or word fragments based from all text in the task answer document that has gone through the pre processing stage, then each document have shingle value vector which will be used to compare the similarity values between documents using Cosine Similarity. The results obtained in this study is the developed feature is capable to detecting the similarity percentage of the assignment answer documents from each student, and from that percentage value it can indicate whether the students assignment answers is plagiarism to other students assignment answers. Keyword : LMS; plagiarism; K-Shingling; Cosine Similarity
Perancangan Fitur Deteksi Kemiripan Dokumen Jawaban Tugas Mahasiswa pada Sistem Manajemen Pembelajaran dengan Metode K-Shingling dan Cosine Similarity Komang Nova Artawan; Rukmi Sari Hartati; Yoga Divayana
Jurnal Teknologi Elektro Vol 22 No 1 (2023): (Januari - Juni) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2023.v22i01.P06

Abstract

Technology development can be used to support the teaching and learning process so it can runs more effectively and efficiently, and one of the applications that can be used to support this process is the Learning Management System (LMS). LMS provides an integrated platform starting from delivering learning materials to students, and evaluating learning process. The evaluation method that can be done at the LMS is giving assignments to students, and students can do submission by uploading their documents assignment answer. The common problem is many students do plagiarism by duplicate the answers of other students. To overcome these problems, this study will implement feature in Course Assignment Menu in LMS to detect the similarity of student assignment document using K-Shingling and Cosine Similarity methods. The K-Shingling algorithm is used to form shingles or word fragments based from all text in the task answer document that has gone through the pre processing stage, then each document have shingle value vector which will be used to compare the similarity values between documents using Cosine Similarity. The results obtained in this study is the developed feature is capable to detecting the similarity percentage of the assignment answer documents from each student, and from that percentage value it can indicate whether the students assignment answers is plagiarism to other students assignment answers. Keyword : LMS; plagiarism; K-Shingling; Cosine Similarity
Analisis Deteksi Kemiripan Dokumen Tugas Mahasiswa pada LMS Undiknas Menggunakan Metode K-Shingling dan Cosine Similarity Komang Nova Artawan; Made Sudarma; Nyoman Gunantara
Jurnal Teknologi Elektro Vol 23 No 1 (2024): (Januari - Juni ) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2024.v23i01.P08

Abstract

Aplikasi LMS (Learning Management System) pada salah satu perguruan tinggi swasta di Bali yaitu Universitas Pendidikan Nasional (Undiknas) mulai dikembangan sejak adanya kewajiban untuk melakukan pembelajaran secara daring saat pandemi COVID melanda, dan hingga saat ini penggunaan LMS Undiknas digunakan untuk menunjang implementasi dari proses pembelajaran jarak jauh agar dapat dilakukan secara digital. Salah satu hal yang perlu diperhatikan dari metode pembelajaran jarak jauh tersebut adalah terkait bagaimana memastikan bahwa mahasiswa telah paham dengan materi pembelajaran yang diberikan secara daring. Hal tersebut dapat dilakukan dengan memberikan tugas yang harus dikerjakan oleh mahasiswa. Namun, pemberian tugas melalui LMS juga dapat menjadi celah untuk mahasiswa melakukan kecurangan dengan kerap ditemukannya bahwa antar mahasiswa melakukan duplikasi jawaban tugas dari mahasiswa yang lain. Sehingga, dalam penelitian ini dilakukan upaya untuk mengatasi permasalahan tersebut dengan melakukan analisis fitur deteksi kemiripan dokumen tugas mahasiswa pada LMS Undiknas dengan metode K-Shingling dan Cosine Similarity agar dapat digunakan oleh dosen untuk mendeteksi persentase kemiripan dari dokumen pengumpulan tugas tiap mahasiswa. Berdasarkan tahap training dan tahap testing yang telah dilakukan, didapatkan kesimpulan bahwa pada rasio partisi data 70% (training) dan 30% (testing), deteksi kemiripan dokumen tugas mahasiswa dengan menggunakan preprocessing teks dan nilai parameter K = 9 pada metode KShingling diperoleh nilai akurasi sebesar 73,55% pada tahap testing yang menunjukkan performa dan tingkat keberhasilan sistem dalam melakukan deteksi kemiripan dokumen jawaban tugas mahasiswa, dan nilai akurasi pada tahap testing ini lebih tinggi 8.24% dibandingkan nilai akurasi pada tahap training. Kata Kunci— LMS Undiknas, Kemiripan Dokumen Tugas, KShingling, Cosine Similarity.
Co-Authors I Nyoman Gunantara Made Sudarma Rukmi Sari Hartati Yoga Divayana