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Journal : Journal of Computer and Information Systems Ampera

Digital Signature Pada Citra Digital Menggunakan Algoritma Rc6 Studi Kasus: Dokumen Kartu Keluarga Hasril Yusuf; Afriyudi Afriyudi; Hadi Syaputra
Journal of Computer and Information Systems Ampera Vol. 1 No. 1 (2020): Journal of Computer and Information Systems Ampera
Publisher : APTIKOM SUMSEL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalcisa.v1i1.4

Abstract

The confidentiality of a document is an important requirement for the people of this age to protect their privacy from people who have no right to know it. To overcome this, an application that can encrypt document files in the form of digital images is needed so that it is not known by others. . The algorithm that has been developed in this study we use the RC6 algorithm as an algorithm method. The purpose of this system will be to help specifically in the administration section to enter or store documents, find and create reports that will be seen by government installations in an encrypted form, and if needed as information can easily be decrypted again. The development method uses the waterfall model. The analytical tool used is Use case, Activity, Diagram, and Class Diagram. The software used is Dreamweaver and Xampp. This system is built in order to provide convenience in processing document data
Klasifikasi Jenis Burung Lovebird Menggunakan Algoritma Convolutional Neural Network Hadi Syaputra; Edi Supratman; Susan Dian Purnamasari
Journal of Computer and Information Systems Ampera Vol. 3 No. 2 (2022): Journal of Computer and Information Systems Ampera
Publisher : APTIKOM SUMSEL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalcisa.v3i2.195

Abstract

Salah satu algoritma yang digunakan untuk klasifikasi citra digital adalah convolutional neural network, dalam penelitian ini citra burung lovebird yang terdiri dari 8 kelas digunakan sebagai dataset untuk pembelajaran mendalam antara lain Agapornis Cana, Agapornis Taranta, Agapornis Pullaria, Agapornis Roseicollis, Agapornis Lilianae, Agapornis Nigrigenis, Agapornis Personata dan Agapornis Ficheri, total citra yang digunakan 800 citra dengan pembagian training 70% dan testing 30%. Implementasi CNN untuk klasifikasi citra burung lovebird. CNN yang digunakan terdiri dari 2 lapisan konvolusi, 2 lapisan, 1 lapisan flatten layer, 2 lapisan dense, dan 2 lapisan Dropout. Tingkat akurasi yang diperoleh dari model CNN dengan nilai learning rate 0.01 dan jumlah epoch sebanyak 100 mendapatkan nilai akurasi 60,83%.