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All Journal TEKNIK INFORMATIKA Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Sriwijaya Journal of Informatics and Applications Jurnal Generic Journal of Applied Data Sciences
Muhammad Qurhanul Rizqie
Informatics Department, Computer Science Faculty, Sriwijaya University
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Journal : Jurnal Generic

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Pengujian Integritas File Operasi Tanda Tangan Digital Menggunakan Kombinasi Hash MD5, RSA dan Skema Qr-Cod Hafiz Mursid; Julian Supardi; M. Qurhanul Rizkie
Generic Vol 14 No 2 (2022): Vol 14, No 2 (2022)
Publisher : Fakultas Ilmu Komputer, Universitas Sriwijaya

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Abstract

Kebijakan WFH pada masa pandemi COVID-19 mengakibatkan berbagai dokumen yang awalnya masih menggunakan sistem manual beralih ke sistem digital termasuk pada pengesahan pada dokumen tersebut. Maka penerapan tanda tangan digital dapat dijadikan alternatif sebagai bukti autentik sebuah dokumen untuk menggantikan tanda tangan konvensional. Penelitian ini bertujuan untuk mengembangkan perangkat lunak guna melakukan pengujian integritas dokumen dengan tanda tangan digital yang dibangun menggunakan fungsi hash MD5 dan algoritma RSA yang kemudian di-generate menjadi Qr-Code pada dokumen yang terdiri dari 1000 kata dengan ekstensi .docx. Dokumen yang akan diuji tersebut diberikan tanda tangan digital dengan perangkat lunak yang dibangun dan selanjutnya dilakukan pengujian integritas dengan melakukan operasi modifikasi terhadap file teks tersebut. Pada penelitian ini telah dibuat perangkat lunak untuk menerapkan skema autentikasi pada sebuah dokumen. Dari hasil penelitian yang dilakukan maka dapat disimpulkan jika fungsi hash MD5 dan algoritma RSA yang digenerate menjadi Qr-Code dapat diimplementasikan dengan baik untuk operasi tanda tangan digital.
Lung X-Ray Segmentation using Quadrant-Based Tracing Method Rizqie, Muhammad Qurhanul; Maolana, Iyus; Supriyanto, Eko
Generic Vol 16 No 1 (2024): Vol 16, No 1 (2024)
Publisher : Fakultas Ilmu Komputer, Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/generic.v16i1.182

Abstract

Chest X-Ray is one of the most popular imaging modalities. Chest X-ray has been a subject of various imaging-related research for years. Among the various research, Lung segmentation is one of the most prominent ones. Nowadays the trend of research in segmentation is moving toward deep learning however traditional segmentation has advantage of requiring less calculation resources thus still has potential to be explored. In this paper an alternative non-deep learning segmentation method using graph-based method to trace border of the Chest X-Ray lung region is proposed. Chest X-Ray image was treated as a graph with coordinate of the pixels as vertex and value of the pixels as edges. First the image was divided into 4 quadrants, then the border of lung region on each quadrant was traced by finding the minimum spanning tree of the graphs on each quadrant, then the pixels recorded as the tree was smoothed and optimized using Savitzky-Golay filter. The results were analyzed using the confusion matrix by comparing the proposed method results with manual segmentation by a radiologist. The proposed method is successfully segment lung area on lateral view of chest X-Ray with an average accuracy of 0.936. Two sample T-test also employed in order to show that there is no significant difference between the proposed method results and manual segmentation by radiologist.
Co-Authors Abdiansah Abdiansah Abdiansah Abdiansah Abdiansah, Abdiansah Ahmad Ghiffari Ananda Haykel Iskandar Deris Stiawan Edi Surya Negara Eko Supriyanto Hadipurnawan Satria Hadipurnawan Satria Hafiz Mursid Iskandar, Ananda Haykel Julian Supardi Latius Hermawan M. Hatta Aldino Ramadhan Maolana, Iyus Meilinda Meilinda Muhammad Fachrurrozi MUHAMMAD FAHMI Muhammad Furqan Nazuli Muhammad Ikhsan Nugraha, Wibisena Primanita, Anggina Ramayanti, Indri Rizma Adlia Syakurah Wibisena Nugraha