Deteksi Potensi Menyontek Menggunakan Feedforward Neural Network Pada Ujian Daring
DOI:
https://doi.org/10.31598/sintechjournal.v7i2.1585Keywords:
Deteksi Potensi Menyontek, Feedforward Neural Network, MediaPipe Face Landmark, PendidikanAbstract
Pendidikan di Indonesia merupakan salah satu faktor pendukung yang dapat menjadikan Indonesia menjadi negara maju. Akan tetapi masih banyak pelajar yang melakukan praktik menyontek sehingga menurunkan kualitas pendidikan di Indonesia. Untuk mengurangi praktik menyontek di Indonesia, penelitian ini bertujuan untuk membuat sebuah model deep learning dengan menggunakan metode feedforward neural network untuk mendeteksi potensi menyontek. Penelitian ini menggunakan 51 video dataset diperoleh dari orang-orang yang pada akhirnya diubah menjadi titik-titik koordinat menggunakan Mediapipe Face Landmark yang disimpan pada file CSV. Pada penelitian ini terdapat 7 class pada dataset yang sudah dibuat yaitu netral, hadap_atas, hadap_bawah, hadap_kiri, hadap_kanan, retina_kiri dan retina_kanan. Indikator utama yang paling menentukan untuk mendeteksi potensi tidak menyontek adalah class netral. Akan tetapi, class retina_kiri dan retina_kanan juga ikut berpartisipasi karena ada pertimbangan dari segi pembacaan soal. Indikator yang menentukan untuk mendeteksi potensi menyontek adalah class hadap_kiri, hadap_kanan, hadap_atas, dan hadap_bawah. Penelitian ini menghasilkan model yang dapat memprediksi potensi menyontek dengan akurasi sebesar 91.6% dengan menggunakan metode feedforward neural network. Dari model yang dihasilkan, dapat diimplementasikan kedalam sebuah sistem ujian daring.
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References
W. W. Muhlishottin and M. V. Roesminingsih, "Pelaksanaan Fungsi Fungsi Manajemen Kelompok Bermain RA Kartini Desa Trutup Kecamatan Plumpang Kabupaten Tuban," Jurnal Pendidikan Untuk Semua, vol. 4, no. 1, pp. 116-123, 2020.
A. Anitasari, O. Pandansari, R. Susanti, K. Kurniawati and A. Aziz, "Pengaruh Efikasi Diri terhadap Perilaku Menyontek Siswa Sekolah Dasar selama Pembelajaran Daring," Jurnal Penelitian Ilmu Pendidikan, vol. 14, no. 1, pp. 82-90, 2021.
M. Undorf, E. Y. Mah, D.-L. L. McDonald, Z. I. Hamzagic, R. Burnell, M. Garry and D. M. Bernstein, "People who cheat on tests accurately predict their performance on future tests," Learning and Instruction, vol. 66, no. 101295, 2020.
M. S. Y. Lubis, "IMPLEMENTASI ARTIFICIAL INTELLIGENCE PADA SYSTEM MANUFAKTUR TERPADU," SEMNASTEK UISU 2021, vol. 4, no. 1, pp. 1-7, 2021.
S. Z. Ong, T. Connie and M. K. O. Goh , "Cheating Detection for Online Examination Using Clustering Based Approach," JOIV International Journal on Informatics Visualization, vol. 7, no. 3-2, p. 2075, 2023.
R. K. Kadthim and Z. H. Ali, "Cheating Detection in online exams using machine learning," Journal Of AL-Turath University College, vol. 2, no. 35, pp. 35-41, 2023.
W. Alsabhan, "Student Cheating Detection in Higher Education by Implementing Machine Learning and LSTM Techniques," Sensors, vol. 23, no. 8, p. 4149, 2023.
Y. Liu, J. Ren, J. Xu, X. Bai, R. Kaur and F. Xia, "Multiple Instance Learning for Cheating Detection and Localization in Online Examinations," IEEE Transactions on Cognitive and Developmental Systems, pp. 1-12, 2024.
S. N. Budiman, S. Lestanti, S. M. Evvandri and R. K. Putri, "FINGER GESTURE RECOGNITION TO CONTROL VOLUME ON COMPUTER USING OPENCV AND MEDIAPIPE LIBRARY," ANTIVIRUS: Jurnal Ilmiah Teknik Informatika, vol. 16, no. 2, pp. 223-232, 2022.
P. D. Saputri and P. P. Oktaviana, "Comparison of Feedforward Neural Network and Classical Statistics Methods: Application in Finance Authors," Jurnal Matematika, Statistika dan Komputasi, vol. 19, no. 3, pp. 537-548, 2023.
A. S. A. Anshari, M. A. Ihsan, R. A. Duyo and H. Nirwana, "ANALISA TENAGA SURYA TERKONSENTRASI PADA KONVERSI CAHAYA SINAR MATAHARI MENJADI ENERGI LISTRIK TERHADAP SUPLAI AIR," Vertex Elektro, vol. 15, no. 2, pp. 11-18, 2023.
M. M. Masud, K. Hayawi, S. S. Mathew, T. Michael and M. E. Barachi , "Smart Online Exam Proctoring Assist for Cheating Detection," Advanced Data Mining and Applications, vol. 13087, p. 118–132, 2022.
A. Zaffar, M. Jawad and M. Shabbir, "A Novel CNN-RNN Model for E-Cheating Detection Based on Video Surveillance," University of Wah Journal of Computer Science , vol. 5, pp. 1-13, 2023.
S. G. Rabiha, Cheating Scenario Dataset in Online Exam, Mendeley Data, 2024.
Y. Atoum , L. Chen, A. X. Liu and S. D. H. Hsu , "Automated Online Exam Proctoring," IEEE Transactions on Multimedia, vol. 19, no. 7, pp. 1609 - 1624, 2017.
N. K. Pratama, "DETEKSI LAMPU LALU LINTAS DAN ZEBRA CROSS MENGGUNAKAN MOBILENETV2 SINGLE SHOT DETECTOR,," Jurnal Informatika Kaputama (JIK), vol. 7, no. 2, pp. 225-232, 2023.
R. D. Romadhona, "emanfaatan Teknik Clustering untuk Mencapai Kecerdasan Bisnis Menggunakan Algoritma K-Means," Seminar Nasional Sistem Informasi (SENASIF), vol. 6, no. 1, pp. 3015-2023, 2022.
S. Nawoya, F. Ssemakula, R. Akol, Q. Geissmann, H. Karstoft, K. Bjerge, C. Mwikirize, A. Katumba and G. Gebreyesus, "Computer vision and deep learning in insects for food and feed production: A review," Computers and Electronics in Agriculture, vol. 216, p. 108503, 2024.
E. R. Fitria and F. Rozci , "Penerapan Metode Regresi Least Absolute Shrinkage and Selection Operator (LASSO) dan Regresi Linier untuk Memprediksi Tingkat Kemiskinan di Indonesia," Jurnal IlmiahSosio Agribis (JISA), vol. 22, no. 2, pp. 123-132, 2022.
H. Santoso, R. A. Putri and S. Sahbandi, "Deteksi Komentar Cyberbullying pada Media Sosial Instagram Menggunakan Algoritma Random Forest," Jurnal Manajemen informatika (JAMIKA), vol. 13, no. 1, pp. 62-72, 2023.
D. Martinez-Mosquera, R. Navarrete and S. Lujan-Mora, "Modeling and Management Big Data in Databases—A Systematic Literature Review," Sustainability, vol. 12, no. 2, p. 634, 2020.
R. E. Nogales and M. E. Benalcázar , "Analysis and Evaluation of Feature Selection and Feature Extraction Methods," International Journal of Computational Intelligence Systems, vol. 16, no. 153, pp. 1-13, 2023.
T. P. Tan, C. K. Lim and W. R. E. A. Rahman, "Sliding Window and Parallel LSTM with Attention and CNN for Sentence Alignment on Low-Resource Languages," Pertanika Journal Science & Technology, vol. 30, no. 1, pp. 97-121, 2022.
L. Priyambodo, H. L. Fuadi, N. Nazhifah, I. Huzaimi, A. B. Prawira, T. E. Saputri, M. A. Afandi, E. S. Nugraha, A. Wicaksono and P. K. Goran, "Klasifikasi Kematangan Tanaman Hidroponik Pakcoy Menggunakan Metode SVM," Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 6, no. 1, pp. 153-160, 2022.
L. Qadrini, A. Seppewali and A. Aina, "Decision Tree dan Adaboost pada Klasifikasi Penerima Program Bantuan Sosial," Jurnal Inovasi Penelitian, vol. 2, no. 7, pp. 1959-1966, 2021.
A. Tasnim, M. Saiduzzaman, M. A. Rahman, J. Akhter and A. S. M. M. Rahaman, "Performance Evaluation of Multiple Classifiers for Predicting Fake News," Journal of Computer and Communications, vol. 10, no. 9, pp. 1-21, 2022.
R. K. Kadthim and Z. H. Ali, "Cheating Detection in online exams using machine learning," Journal Of AL-Turath University College, vol. 2, no. 35, pp. 35-41, 2023.
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