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All Journal Jurnal Masyarakat Informatika Techno.Com: Jurnal Teknologi Informasi JAIS (Journal of Applied Intelligent System) ANDHARUPA Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Abdidas Journal of Soft Computing Exploration Jurnal Citrakara
Laksana, Deddy Award Widya
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Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Journal : Journal of Soft Computing Exploration

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A text security evaluation based on advanced encryption standard algorithm Bima, Aristides; Irawan, Candra; Laksana, Deddy Award Widya; Krismawan, Andi Danang; Isinkaye, Folasade Olubusola
Journal of Soft Computing Exploration Vol. 4 No. 4 (2023): December 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v4i4.274

Abstract

This research approach analysis and examines a number of advanced encryption standard (AES) performance factors, including as encryption and decryption speed, processing resource, consumption, and resilience, to cryptanalysis attacks. The study’s findings demonstrate that AES is successful in providing high-level data security, particularly when used in the CBC (Cipher Block Chaining) operating mode. Performance is dependent on the length of the key that is utilized. Increasing the level of security through the use of longer keys may result in an increase in the amount of time needed for encryption. The experimental results show that the highest results from the data are as follows the length of the encryption time is 0.00005317 seconds, the length of the decryption time is 0.00000882 seconds, the results of BER and CER are 0, the results of entropy are 7.44237, and the results of avalanche influence are 54.86%.
Eye disease classification using deep learning convolutional neural networks Rachmawanto, Eko Hari; Sari, Christy Atika; Krismawan, Andi Danang; Erawan, Lalang; Sari, Wellia Shinta; Laksana, Deddy Award Widya; Adi, Sumarni; Yaacob, Noorayisahbe Mohd
Journal of Soft Computing Exploration Vol. 5 No. 4 (2024): December 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i4.493

Abstract

This study begins with the analysis of the growing challenge of accurately diagnosing eye diseases, which can lead to severe visual impairment if not identified early. To address this issue, we propose a solution using Deep Learning Convolutional Neural Networks (CNNs) enhanced by transfer learning techniques. The dataset utilized in this study comprises 4,217 images of eye diseases, categorized into four classes: Normal (1,074 images), Glaucoma (1,007 images), Cataract (1,038 images), and Diabetic Retinopathy (1,098 images). We implemented a CNN model using TensorFlow to effectively learn and classify these diseases. The evaluation results demonstrate a high accuracy of 95%, with precision and recall rates significantly varying across classes, particularly achieving 100% for Diabetic Retinopathy. These findings highlight the potential of CNNs to improve diagnostic accuracy in ophthalmology, facilitating timely interventions and enhancing patient outcomes. For future research, expanding the dataset to include a wider variety of ocular diseases and employing more sophisticated deep learning techniques could further enhance the model's performance. Integrating this model into clinical practice could significantly aid ophthalmologists in the early detection and management of eye diseases, ultimately improving patient care and reducing the burden of ocular disorders.
Co-Authors Agus Setiawan Ahmad Zainul Fanani Akrom, Ahmad Alfany, Fauzan Maulana Ali, Rabei Raad Arni Ernawati Arry Maulana Syarif, Arry Maulana Bima, Aristides Cahaya Jatmoko Candra Irawan Christy Atika Sari Deny Tri Ardianto Dwi Putri, Puri Kusuma Eko Hari Rachmawanto Hanny Haryanto Heribertus Himawan Isinkaye, Folasade Olubusola Krismawan, Andi Danang Lalang Erawan Liya Umaroh, Liya Mohamad Taufik, Mohamad Nur Rokhman Pratama, Reza Arista Solichul Huda, Solichul Sumarni Adi, Sumarni Syarifudin, Moh Fathih Wellia Shinta Sari Yaacob, Noorayisahbe Mohd