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All Journal KURVA S JURNAL MAHASISWA Jurnal Konstruksia Jurnal Media Gizi Indonesia (MGI) QALAMUNA: Jurnal Pendidikan, Sosial, dan Agama AGREGAT Jurnal AKP JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Teknik Informatika UNIKA Santo Thomas Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan Jurnal Teknik Informatika (JUTIF) jurnal dikdas bantara Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Multidisiplin Madani (MUDIMA) Jurnal Pengabdian Masyarakat Bhinneka International Journal of Civil Engineering and Infrastructure (IJCEI) Jurnal Pengabdian Masyarakat Bangsa Prosiding Seminar Nasional Rekayasa dan Teknologi (TAU SNAR- TEK) Mu'asyarah Media of Computer Science Prosiding Seminar Nasional CORISINDO
Andika Setiawan, Andika
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Journal : Media of Computer Science

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Identification of Fatigue from Facial Expressions Using Transfer Learning Manurung, Jefri; Setiawan, Andika; Cahyo Untoro, Meida
Media of Computer Science Vol. 1 No. 1 (2024): June 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i1.180

Abstract

Initially, teaching and learning activities were carried out face-to-face in the provided room, but now they have switched to online. Online learning has an impact on student learning disengagement, which is known through indicators of aspects of emotional exhaustion, physical fatigue, cognitive fatigue, and loss of motivation. Besides, the teacher must provide the material that has been provided. The teacher must also pay attention to all students who are participating in the online learning. This can be overcome by a system that can detect student disengagement using a camera device. The system works by scanning the direction of students' faces and views using OpenCV technology and Transfer Learning methods. Using context, facial expressions, and heart rate can be used to recognize student disengagement. However, with the widespread availability of cameras, it is easier to identify disengagement using facial expressions. The facial expression recognition system in this study will use the FER2013 dataset and Transfer Learning method. Facial expression recognition using the FER-2013 dataset and Transfer Learning method has a reading accuracy rate of 68% in 25 epochs. Then, after being implemented as an impression parameter in the disengagement identification system using 7 scenarios, the accuracy rate is 83.33%, precision is 100%, recall is 75%, and the f1-score is 85.71%.
Identification of Leaf Spot Diseases in Eggplant Using Gray Level Co-Occurrence Matrix (GLCM) Feature Extraction and Support Vector Machine (SVM) Classification Pahlevi, Reza; Setiawan, Andika; Kesuma, Rahman Indra
Media of Computer Science Vol. 2 No. 1 (2025): June 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i1.202

Abstract

Eggplant (Solanum melongena L.) is one of the widely cultivated vegetables in Indonesia, belonging to the Solanaceae family. This plant is susceptible to several diseases, one of which is leaf spot disease. Leaf spot disease, caused by the pathogenic fungus Alternaria sp., is characterized by irregularly shaped brown spots with a diameter of approximately 0.5 cm. To address this issue, a digital image processing-based system was developed to identify whether the plant is infected. The proposed system employs feature extraction using the Gray Level Co-Occurrence Matrix (GLCM) combined with the Support Vector Machine (SVM) classification algorithm. The study utilized a dataset of 100 images for training and 50 images for testing. The highest achieved accuracy was 100%, obtained by applying Laplace of Gaussian (LoG) edge detection along with Linear Kernel and Polynomial Kernel SVM classifiers.
Co-Authors Adi Sucipto, Adi Afit Miranto agung nusantoro Agung, Ahmad Anggraria Jaya Aji, Abdul Alrando, Raja Aksana Anas Tamsuri Anggraini, Leslie Aprilianda, Mohamad Meazza Arif Ashari Astuti, Resti Dwi Badaruddin Badaruddin Badaruddin Bagaskara, Radhinka Basit Al Hanif Ba’its, Alfian Kafilah Cahyo Untoro, Meida Deby Puspitaningrum Demi Dama Yanti Desty Ervira Puspaningtyas Drantantiyas, Nike Dwi Grevika Dwi Yulina Abdi Jayanti Eko Prasetyo, Harwidyo Elityasari, Cindy Nur Faisal, Amir Farahdiba Farahdiba Febrianto, Andre Fil’aini, Raizummi Fitrawan, Mhd. Kadar Habeahan, Angelina Hanif, Farhan Harmiansyah Hartanto Tantriawan Harwidyo Eko Prasetyo Haryo Koco Buwono Heri Khoeri Herlina, Idra Himawan, Prasta Genie Ichwani, Arief Indarto Indarto Irwanto, Rachmad Kisna Pertiwi, Kisna Kuswidyanarko , Arief Listiani, Amalia Manurung, Jefri Marhamah . Mario, Frisel Martin Clinton Tosima Manullang, Martin Clinton Tosima Miranda, Anne Putri Mufidah, Zunanik Muhammad Yogi Saputra Mustakim, Fahmi Novriani, Shinta Nusyura Al Islami, Aulia Pratama, Rizky Nisa Putri, Arie Pradina Rahman Indra Kesuma Rahmat Kurniawan Raidah Hanifah Rakhman, Arkham Zahri Ramadhani, Uri Arta REZA PAHLEVI Satiawan, Budi Satya Soeratmodjo, Irnanda Satya Soerjatmodjo, Irnanda Siska Puspita Sari Sitorus, Iwan Romadhan Soerjatmodjo, Irnanda Satya Sofiana, Dini sutik, sutik Tuta, Gabriel Vanes Sabat Untoro, Meida Cahyo Wicaksana, Galih Wicaksono, Imam Eko Wijayanti, Rini Windasari, Liska Yulia, Alya Yulita, Winda Yuni Afriani, Yuni Yusmita, Yusmita