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All Journal Semantik MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Knowledge Engineering and Data Science SMARTICS Journal Applied Information System and Management Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Information System,Graphics, Hospitality and Technology Applied Technology and Computing Science Journal Teknika Journal of Electrical Engineering and Computer (JEECOM) Journal of Applied Data Sciences International Journal of Engineering, Science and Information Technology Insyst : Journal of Intelligent System and Computation J-Intech (Journal of Information and Technology) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Sistem Cerdas dan Rekayasa Jurnal Inovasi Teknologi dan Edukasi Teknik Nusantara Journal of Computers and its Applications Bulletin of Social Informatics Theory and Application Jurnal Informatika: Jurnal Pengembangan IT Journal of Information Technology
Joan Santoso
Institut Sains Dan Teknologi Terpadu Surabaya
Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Journal : J-Intech (Journal of Information and Technology)

 1 
Pemanfaatan Deep Convolutional Auto-encoder untuk Mitigasi Serangan Adversarial Attack pada Citra Digital Kurniawan S, Putu Widiarsa; Kristian, Yosi; Santoso, Joan
J-INTECH (Journal of Information and Technology) Vol 11 No 1 (2023): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v11i1.845

Abstract

Adversarial attacks on digital images pose a serious threat to the utilization of machine learning technology in various real-life applications. The Fast Gradient Sign Method (FGSM) technique has proven to be effective in conducting attacks on machine learning models, including digital images found in the ImageNet dataset. This research aims to address this issue by utilizing the Deep Convolutional Auto-encoder (AE) technique as a method for mitigating adversarial attacks on digital images.The results of the study demonstrate that FGSM attacks can be performed on the majority of digital images, although there are certain images that are more resilient to such attacks. Furthermore, the AE mitigation technique proves to be effective in reducing the impact of adversarial attacks on most digital images. The accuracy of the attack and mitigation models is measured at 14.58% and 91.67%, respectively.
Prediksi Student Performance Pada Hasil Penilaian Proses Pembelajaran Online Mata Pelajaran Informatika Di SMA Dipa, Sasra; Santoso, Joan; Chandra, Francisca H.
J-INTECH (Journal of Information and Technology) Vol 12 No 1 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i1.1259

Abstract

In the Corona Endemic, we are not just returning to offline education patterns but are already moving towards education 5.0. Online, normal, blended learning patterns have become commonplace. Online learning assessment requires fast and precise predictions of student performance (high accuracy). The reason is first, due to limited direct interaction. Second, normal learning usually involves an assessment of the learning process and character assessment to be able to provide an accurate final assessment, which is difficult to implement in online learning accurately. Third, there is a lot of data to be processed quickly and precisely so that it can be reported to educational institutions and to students' families. Fourth, Informatics is a lesson that is 80% practical and 20% theory so that the assessment instruments used are 80% performance instruments (Bloom's taxonomy: C2, C3, C4, C5) and 20% multiple choice instruments (C1). Informatics correction and assessment requires more time because 80% cannot be assessed automatically. This research aims to predict student performance (Pass (1) or Intervention (0)) on the results of the online learning process assessment for informatics subjects in high school. If the student performance prediction results in an intervention, it will be immediately followed up by providing an intervention strategy to increase student performance. The target of the research results is to achieve > 70% accuracy on the processed dataset. This research uses the ensemble learning method random Forest Classification and XG Boosting classification. The research results of Student Performance Prediction using XG Boost Classification produce higher accuracy than RF Classification which has an average accuracy value = 93% while RF Classification has an average accuracy result = 92%. The research objectives have been achieved because the results of the 2 methods used have met the desired targets.
Co-Authors Aditya Dwi Aryanto Adriel Ferdianto Afandi, Acxel Derian Agung Dewa Bagus Soetiono Ahdan, Syabith Umar Ahmad Syaifuddin Ali Djamhuri Ananta Tio Putra Andik Jatmiko Anita Guterres Budi Irawan Cahyadi, Billy Kelvianto Chandra, Francisca H. Christian Nathaniel Purwanto Devi Dwi Purwanto Dewi, Nindian Puspa Dipa, Sasra Edwin Pramana Eka Rahayu Setyaningsih Eko Mulyanto Yuniarno Elizabeth Shirley, Stephanie Endang Setyati Esther Irawati S. Esther Irawati Setiawan Eunike Kardinata F.X. Ferdinandus Fachrul Kurniawan Febriantoro, Erfan Ferdinandus, F. X. Francisca Chandra Fujisawa, Kimiya Gunawan Gunawan Gunawan Gunawan Gunawan Gunawan Halim, Kevin Jonathan Hans Juwiantho Hans Keven Budi Prakoso Harianto, Reddy Alexandro Hartarto Junaedi Hartono, Patrick Hendrawan Armanto Heppi Siswanto Herman Budianto Imron, Syaiful Indra Maryati Irawati Setiawan, Esther Jatmiko, Andik Kristian Indradiarta Gunawan Kristina, Natalia Kurniawan S, Putu Widiarsa Langgeng, Yudo Sembodo Hastoro Leonel Hernandez Lim, Ernest Luhfita Tirta Lukman Zaman Machfudin, Mohammad Farid Mauridhi Hery Purnomo Mochamad Hariadi Muhammad Amfahtori Wijarnoko Mustaqin, Farhan Faisal Zainul Nagari, Widean Nindian Puspa Dewi Ong, Hansel Santoso Putra, Bayu Anggara Putu Widiarsa Kurniawan S Rossy P. C. Rully Widiastutik Samuel Budi Wardhana Kusuma Saputra, Daniel Gamaliel Setiawan, Esther Setya Ardhi Soetiono, Agung Dewa Bagus Stefanie Hilda Kusumahadi Surya Sumpeno Sutanto, Patrick Sutanto, Ricky Syaiful Huda Syaiful Imron Tjendika, Patrick Tjwanda Putera Gunawan Tri Septianto Tuesday saka gustaf Ubaidi Ubaidi Ubaidi, Ubaidi Vania, Stella Vu, Tong Nam Tuan Wardoyo, Nikko Riestian Putra Yosi Kristian