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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Semantik Jurnal Teknologi Informasi dan Ilmu Komputer Seminar Nasional Informatika (SEMNASIF) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURIKOM (Jurnal Riset Komputer) Aptisi Transactions on Technopreneurship (ATT) Building of Informatics, Technology and Science Journal Sensi: Strategic of Education in Information System Jurnal Sistem Komputer dan Informatika (JSON) Aiti: Jurnal Teknologi Informasi Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Ilmiah Sains Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Theopillus J. H. Wellem
Universitas Kristen Satya Wacana
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Social Sciences Other

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Journal : JOIV : International Journal on Informatics Visualization

 1 
Academic Document Authentication using Elliptic Curve Digital Signature Algorithm and QR Code Theophilus Wellem; Yessica Nataliani; Ade Iriani
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2.872

Abstract

Paper-based documents or printed documents such as recommendation letters, academic transcripts, and diplomas are prone to forgery. Several methods have been used to protect them, such as watermarking, security holograms, or using paper with specific security features. This paper presents a document authentication system that utilizes QR code and ECDSA as the digital signature algorithm to protect this kind of document from counterfeiting. A digital signature is a well-known technique in modern cryptography used for providing data integrity and authentication. The idea proposed herein is to put a QR code in the printed documents where the QR code includes a digital signature. The signature can later be authenticated using the proposed system by uploading the document for authentication or scanning the document's QR code. The proposed system is particularly developed for digital signature generation and verification of students' final project approval documents as the case study. In traditional settings, the approval form is typically signed directly by the student's advisor dan co-advisor using handwritten signatures. However, using the conventional handwritten signature, the signature on the approval form can be falsified. Therefore, a digital signature generation and verification system is implemented herein to avoid handwritten signature falsification. The advisors can use this system to sign the approval form using a digital signature instead of a handwritten one. The signature is stored in a QR code and is generated using ECDSA with SHA-256 as the hash function. The proposed system is evaluated using documents (i.e., approval forms) with genuine and forged QR codes.  The evaluation results showed that the system could verify the authenticity of the approval forms, which contain genuine QR codes. The approval forms that contained forged QR codes were correctly identified.
Multi-Objective k-Nearest Neighbor for Breast Cancer Detection Nataliani, Yessica; Arthur, Christian; Wellem, Theophilus; Hartomo, Kristoko Dwi; Wahab, Nur Haliza Abdul
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2669

Abstract

Early detection of cancer is crucial. This study aims to increase the efficiency of breast cancer detection using the modified k-nearest neighbor (k-NN) algorithm. Since k-NN faces challenges with sensitivity to k values and computational complexity, a modification of k-NN was proposed, namely a multi-objective k-NN model. It was developed to incorporate multi-objective optimization and local density to create a more robust and efficient classification algorithm. The model dynamically determines the k value based on the sample density, optimizing accuracy and efficiency. Breast cancer data were collected from the University of Wisconsin Hospitals, Madison. The experimental results showed that the multi-objective k-NN model outperformed traditional k-NN and k-NN with feedback support. The proposed model achieved an accuracy of 93.7%, with precision values of 93% for the negative cancer class and 94% for the positive cancer class. These results indicate that the multi-objective k-NN model provides superior accuracy and precision in breast cancer detection, demonstrating its potential for clinical applications.
Co-Authors Ade Iriani Adi Setiawan Adriyanto Juliastomo Gundo Agustinus Fritz Wijaya Antika Lorien Anton Hermawan Arthur, Christian Bentar Priyopradono Danang Maulana Ikhsan Daniawan, Benny Daniel D Kameo Danny Manongga Darmawan Utomo Donny Priyadi Edi Suharyadi Erwien Christianto Fauzan, Rafi Ardhan Fra Arsandy Kusuma Sejati Fransiscus Bryan Prasetio Gabriel Gracia Salindeho Henderi . Hendry Hindriyanto Dwi Purnomo Ignatius Agus Supriyono Ikhsan, Danang Maulana Ilham Hizbuloh Imanuel Susanto Indrastanti Ratna Widiasari Irwan Sembiring Ivanna Kristianti Timotius Iwan Setyawan Jonathan Putera Perdana krismiyati krismiyati Kristoko Dwi Hartomo Lasso, Aldi Luis Geraldo Mauboy Maulana, Aldias Henry Muhamad Yusup Pantow, Prayogo Pangestu Piter Wijaya Prakoso, Alvian Dafa Priatna , Wowon Putra, Yeheskiel Mandala Rafi Ardhan Fauzan Rafly Fernanda Rizky Restu Fauzi Roland Tumbelaka Palar Sri Yulianto Joko Prasetyo Suharyadi Sutarto Wijono Tintien Koerniawati Valen Brata Pranaya Wahab, Nur Haliza Abdul Weku, Winsy C.D Yeheskiel Mandala Putra Yessica Nataliani Yonas Juniantiko Putro