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Adopsi Generator Kunci Euler Number dan Pembangkit Kunci Blum Blum Shub untuk Meningkatkan Confidentiality Level pada Extended Vigenere Ardhianto, Eka; Redjeki, Rara Sriartati; Supriyanto, Edy; Murti, Hari; Wahyudi, Eko Nur
Infotek: Jurnal Informatika dan Teknologi Vol. 7 No. 1 (2024): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v7i1.21512

Abstract

Algoritma Vigenere merupakan model algoritma enkripsi yang masih dikembangkan dalam bidang keamanan informasi saat ini. Salah satu aspek yang dianggap penting dalam bidang keamanan informasi adalah kerahasiaan. Masalah pencapaian kerahasiaan pesan atau informasi yang tinggi sangat penting dalam bidang keamanan informasi. Extended Vigenere dikenal sebagai evolusi dari Vigenere yang menerapkan lebih banyak set karakter. Salah satu pengembangan algoritma Vigenere adalah dengan memodifikasi generator kunci yang digunakan. Eksperimen ini bertujuan untuk menguji pengaruh kerahasiaan informasi pada penggunaan generator kunci Blum Blum Shub (BBS) dan nomor Euler yang diterapkan pada Extended Vigenere. Metode pembangkitan kunci BBS dan nomor Euler digunakan secara berurutan. Sebagai metrik pengukuran, perhitungan entropi dari keluaran Extended Vigenere digunakan. Hasil yang diperoleh berupa peningkatan kerahasiaan informasi yang signifikan dengan nilai entropy achievement lebih dari 79% dari entropy optimum.
Pendekatan Holistik Dalam Penciptaan Logo Produk Melalui Integrasi Socio-Technical Systems dan Design Thinking Retnowati, Retnowati; Anjarsari, Vici Tiara; Wahyudi, Eko Nur; Mukti, Artin Bayu; Hardiyanti, Widhian
Jurnal Pendidikan Indonesia Vol. 6 No. 1 (2025): Jurnal Pendidikan Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/japendi.v6i1.1568

Abstract

Penelitian ini mengintegrasikan pendekatan Socio-Technical Systems (STS) dan Design Thinking untuk menciptakan logo produk minuman herbal yang holistik dan sesuai dengan kebutuhan pengguna. Proses desain dimulai dengan tahap Empathize untuk memahami preferensi visual, nilai-nilai konsumen, dan kebutuhan informasi tentang produk alami. Tahap berikutnya melibatkan pengembangan konsep kreatif melalui brainstorming di tahap Ideate, diikuti dengan pembuatan prototipe yang diuji dalam berbagai media pada tahap Prototype. Pengujian logo dilakukan menggunakan System Usability Scale (SUS) untuk mengukur kegunaan dan kepuasan pengguna terhadap logo yang dihasilkan. Hasil penelitian menunjukkan bahwa integrasi STS dan Design Thinking secara efektif menghasilkan logo yang relevan secara estetika, fungsional, dan diterima oleh audiens target. Pendekatan ini dapat digunakan dalam proyek desain lain yang memerlukan keseimbangan antara elemen sosial dan teknis.
Peningkatan Kapasitas Pendamping UMKM dalam Menjaga Kerahasiaan Data Pribadi Klien pada Komunitas Aurum First Sunrise di Surakarta Jawa Tengah Wahyudi, Eko Nur; Handoko, Widiyanto Tri; Lestariningsih, Endang
Nusantara: Jurnal Pengabdian kepada Masyarakat Vol. 6 No. 1 (2026): Februari: NUSANTARA Jurnal Pengabdian Kepada Masyarakat
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/nusantara.v6i1.7393

Abstract

This community service activity aimed to enhance the security and efficiency of halal certification mentoring services at the Aurum First Sunrise community in Surakarta. The main challenge faced by the partner was the risk of sensitive SME data leakage such as ID cards, recipes, and supply chain information, due to the lack of an adequate document security mechanism. The core solution implemented was Technology Implementation in the form of a Cryptographically-based Document Management Information sistem (utilizing the Light Weight PDAC algorithm) integrated with digital access rights management and user Training. Evaluation demonstrated successful implementation, evidenced by an increase in the average satisfaction of SMEs regarding data security to 97.8%, confirming enhanced trust. Furthermore, digitalization successfully improved the efficiency of the mentoring team, reflected by a satisfaction score of 85.0%. In conclusion, this service successfully transformed the partner into a secure, efficient, and credible mentoring institution, significantly supporting SMEs in accessing halal certification.
Klasifikasi Dokumen Publik Berbasis NLP: Otomatisasi Proses Informasi Menuju Keterbukaan Data yang Adaptif dan Transparan Retnowati Retnowati; Veronica Lusiana; Eko Nur Wahyudi
Jurnal Teknik Informatika dan Teknologi Informasi Vol. 5 No. 2 (2025): Agustus: Jurnal Teknik Informatika dan Teknologi Informasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jutiti.v5i2.5693

Abstract

In the era of public information disclosure, digital documents have become strategic assets in supporting transparent, accountable, and participatory governance. Effective management of these documents is essential to ensure that public information services are responsive and accessible. However, document classification tasks carried out by Public Information and Documentation Officers (PPID) still rely heavily on manual processes, which are time-consuming, inefficient, and prone to human error. To address this challenge, this study aims to develop an intelligent classification model for public documents using Artificial Intelligence (AI) and Natural Language Processing (NLP), integrated within the Data Lifecycle Management (DLM) framework. The proposed solution was designed using the Design Science Research (DSR) methodology and implemented through Agile development practices. Evaluation was conducted in a simulated laboratory environment that mirrors real-world PPID operations.The developed model leverages transformer-based architectures, particularly BERT (Bidirectional Encoder Representations from Transformers), and is compared against traditional algorithms such as Naive Bayes and K-Nearest Neighbors (KNN). Experimental results show that the BERT model achieves superior performance, with an accuracy of 89%, precision of 0.88, recall of 0.89, and F1-score of 0.88. These metrics confirm that Transformer-based models are highly effective for classifying public documents into categories of information accessibility: available at all times, periodic, immediate, and exempted from disclosure.This research highlights the potential of AI-powered classification to streamline public information services, reduce workload, and enhance compliance with information disclosure laws. The findings support national development priorities such as RPJMN 2025 by contributing to digital transformation in the public sector. The study also provides a replicable framework for other government agencies aiming to implement adaptive and transparent document classification systems.