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All Journal Journal Medical Informatics Technology Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Vebiyatama, Andicha
Unknown Affiliation
Computer Science & IT Dentistry Engineering Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Public Health

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Advances in Machine Learning and Deep Learning towards Medical Data Analysis Vebiyatama, Andicha; Ernawati, Muji
Journal Medical Informatics Technology Volume 2 No. 1, March 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i1.32

Abstract

Artificial intelligence uses advanced algorithms such as deep learning and machine learning methods to help doctors make more accurate diagnoses, identify potential health risks, and customize personalized treatment plans for patients. This literature review explores machine learning and deep learning methods applied to medical datasets over the past five years. The paper discusses the advancements, challenges, and future directions in utilizing ML and DL techniques for medical data analysis. It synthesizes recent research findings, highlighting key methodologies, datasets, and outcomes.
Improving DES Robustness for Text Encryption via Blum-Blum-Shub Key Generation Moata, Omega Joel Patria; Vebiyatama, Andicha; Indra, Muhamad
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 2 (2025): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i2.1385

Abstract

The security vulnerabilities of the Data Encryption Standard (DES) require innovative enhancements to ensure data protection against modern threats. This study integrates the Blum-Blum-Shub (BBS) pseudorandom number generator with DES to enhance encryption robustness. By leveraging BBS’s randomness, the proposed method strengthens the 16-round block cipher structure of DES, improving security while maintaining computational efficiency. A Java-based desktop application is developed to implement this approach, ensuring data security without cloud reliance. Feasibility testing confirms successful encryption with an average processing time of 2 seconds, demonstrating both security improvements and practical applicability. Comparative analysis reveals that BBS integration enhances unpredictability, making decryption more challenging. The findings suggest that combining DES with BBS provides a viable solution to DES’s limitations. Future research may explore scalability, adaptation to diverse data types, and further optimizations to enhance encryption strategies against evolving cybersecurity challenges.
Co-Authors Ernawati, Muji Indra, Muhamad Moata, Omega Joel Patria