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All Journal Jurnal Technopreneur (JTech) Journal of Intelligent Decision Support System (IDSS)
Riyadi, Fajar Sugeng
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Agriculture, Biological Sciences & Forestry Computer Science & IT Energy Mechanical Engineering Other

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ANALISIS KEAMANAN DAN PRIVASI DATA PADA LAYANAN CLOUD COMPUTING DENGAN MENGGUNAKAN TEKNIK KRIPTOGRAFI Riyadi, Fajar Sugeng; syefudin, Syefudin; gunawan, Gunawan; Murtopo, Aang Alim
Jurnal Technopreneur (JTech) Vol 11 No 2 (2023): JURNAL TECHNOPRENEUR (November)
Publisher : UPPM Politeknik Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30869/jtech.v11i2.1241

Abstract

Dunia teknologi tidak akan menjadi bahan perdebatan publik di negara Indonesia, dan pemerintah bekerja keras untuk meningkatkan kualitas dan nilai warisan yang menyandang nama tersebut. Artikel ini mengeksplorasi bagaimana layanan cloud, bahkan proyek sektor publik, dapat diamankan sehingga dapat diakses dari mana saja. Metode penelitian yang digunakan dalam penulisan ini meliputi pengumpulan data, studi kasus, tinjauan literatur, dan penelitian teoritis untuk mengumpulkan data guna mendukung penelitian dan menemukan bahan penelitian yang serupa untuk mendukung penelitian dan tinjauan. Keamanan data atau keamanan data adalah yang paling penting dalam layanan cloud, keamanan data pengguna mudah rusak di cloud dan tidak ada undang-undang untuk mengontrol pemadaman listrik. Kemungkinan pelanggaran data dan privasi dapat dihilangkan jika semua tindakan untuk meningkatkan keamanan data digunakan. Langkah-langkah keamanan yang diberikan adalah menyelesaikan proses sertifikasi, meningkatkan privasi dan kerahasiaan, serta membuat cloud computing dapat diandalkan dalam hal privasi. Kata kunci - komputasi awan, komputasi awan, pembelajaran, keamanan, perlindungan, keamanan data, otentikasi pengguna, enkripsi data, dan lapisan soket aman.
Application of computer vision for face recognition using viola jones algorithm method Riyadi, Fajar Sugeng; Gunawan, Gunawan; Arif, Zaenul
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 1 (2024): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v7i1.204

Abstract

This research aims to develop a facial recognition system using computer vision technology by applying the Viola-Jones algorithm method. The main focus of this research is to improve accuracy and efficiency in face identification under various lighting conditions and face orientations. The Viola-Jones algorithm, known for its real-time object detection, was chosen for its efficiency in quickly identifying critical facial features. Through testing of various face datasets, the results showed that the system developed was able to recognize faces with a high level of accuracy, even in conditions of non-optimal lighting and various facial poses. The novelty of this research lies in the optimization of the parameters of the Viola-Jones algorithm to improve facial recognition performance, as well as its application in challenging dynamic environments. These findings make a significant contribution to the field of computer vision and facial recognition, offering more effective and efficient solutions for security and surveillance applications, as well as interactive applications that require fast and accurate facial identification.
Co-Authors Aang Alim Murtopo Arif, Zaenul Gunawan Gunawan Syefudin, Syefudin