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All Journal Dinamik Jurnal Masyarakat Informatika Jurnal Sains dan Teknologi Semantik Techno.Com: Jurnal Teknologi Informasi JAIS (Journal of Applied Intelligent System) Proceeding SENDI_U Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Abdimasku : Jurnal Pengabdian Masyarakat Journal of Soft Computing Exploration Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Community: Jurnal Pengabdian Pada Masyarakat Seminar Nasional Teknologi dan Multidisiplin Ilmu Jurnal Informatika Polinema (JIP) Transformasi Masyarakat : Jurnal Inovasi Sosial dan Pengabdian Scientific Journal of Informatics Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial Pelayanan Unggulan: Jurnal Pengabdian Masyarakat Terapan Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK)
Cahaya Jatmoko
Universitas Dian Nuswantoro
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Physics Public Health Social Sciences Other

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Journal : Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control

 1 
Comparative Study of Classification of Eye Disease Types Using DenseNet and EfficientNetB3 Jatmoko, Cahaya; Lestiawan, Heru; Agustina, Feri; Erawan, Lalang
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 9, No. 3, August 2024
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v9i3.1931

Abstract

The purpose of this research is to build a classification model that can perform the eye disease identification process so that the diagnosis of eye disease can be known and medical action can be taken as early as possible. This research used a dataset which has a total of 4217 eye image data and had 4 main classes namely cataract, diabetic retinopathy, glaucoma, and normal. With the data distribution of 1038 cataract images, 1098 diabetic retinopathy images, 1007 glaucoma images, and 1074 normal images, which of this data will be divided with a data percentage scheme of 50:10:40, 60:10:30, and 70:10:20, to see the results of which dataset division can produce optimal accuracy. In this study, the classification process will use 2 CNN transfer learning architectures, namely DenseNet, and efficientnetb3, which are both trained using the ImagiNet dataset. The results obtained after completing the testing process on the model built using the DenseNet architecture get optimal accuracy when using data division as much as 60:10:30, which is 78.59% while using the efficientnetb3 architecture optimal accuracy results when using the data division of 70:10:20, which is 95.66%. In research on the classification that had previously been done, it is very rare to find a classification process for eye disease types, therefore, in this study, the classification process will be carried out and provide an overview of the eye disease classification process with the CNN transfer learning method with more optimal accuracy results.
A Hybrid Encryption using Advanced Encryption Standard and Arnold Scrambling for 3D Color Images Sari, Wellia Shinta; Astuti, Erna Zuni; Jatmoko, Cahaya
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 1, February 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i1.2058

Abstract

Digital security ensuring the confidentiality and integrity of visual data remains a paramount challenge. The escalating sophistication of cyber threats necessitates robust encryption methods to safeguard sensitive information from unauthorized access and manipulation. Despite the development of various encryption techniques, inherent vulnerabilities exist within conventional methods that can be exploited by attackers. Therefore, this research aims to investigate the effectiveness of the combined approach of Arnold Scrambling and Advanced Encryption Standard (AES) in mitigating these vulnerabilities and providing a more secure solution. The primary goal of this research is to enhance the security of digital images by mitigating vulnerabilities associated with conventional encryption methods. Arnold Scrambling introduces chaotic mapping to disperse pixel values, while Advanced Encryption Standard (AES) provides robust cryptographic strength through its substitution-permutation network. By combining these methods in an ensemble fashion, the encryption process achieves heightened resilience against various cryptographic attacks. The proposed methodology was evaluated by using standard metrics including Unified Average Changing Intensity (UACI), Number of Pixels Change Rate (NPCR), and entropy analysis. Results indicate consistent performance across multiple test images, namely: Lena, Mandrill, Cameraman, and Plane with Unified Average Changing Intensity (UACI) averaging 33.6% and Number of Pixels Change Rate (NPCR) nearing 99.8%. Entropy values approached maximum, affirming the efficacy of the encryption in generating highly randomized outputs.
Improved Chaotic Image Encryption on Grayscale Colorspace Using Elliptic Curves and 3D Lorenz System Sinaga, Daurat; Jatmoko, Cahaya; Astuti, Erna Zuni; Rachmawanto, Eko Hari; Abdussalam, Abdussalam; Pramudya, Elkaf Rahmawan; Shidik, Guruh Fajar; Andono, Pulung Nurtantio; Doheir, Mohamed
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 3, August 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i3.2251

Abstract

Digital data, especially visual content, faces significant security challenges due to its susceptibility to eavesdropping, manipulation, and theft in the modern digital landscape. One effective solution to address these issues is the use of encryption techniques, such as image encryption algorithms, that ensure the confidentiality, integrity, and authenticity of digital visual content. This study addresses these concerns by introducing an advanced image encryption method that combines Elliptic Curve Cryptography (ECC) with the 3D Lorenz chaotic system to enhance both security and efficiency. The method employs pixel permutation, ECC-based encryption, and diffusion using pseudo-random numbers generated by the Lorenz 3D system. The results show superior performance, with an MSE of 3032 and a PSNR of 8.87 dB, as well as UACI and NPCR values of 33.34% and 99.64%, respectively, indicating strong resilience to pixel intensity changes. During testing, the approach demonstrated robustness, allowing only the correct key to decrypt images accurately, while incorrect or modified keys led to distorted outputs, ensuring encryption reliability. Future work could explore extending the method to color images, optimizing processing for larger datasets, and incorporating additional chaotic systems to further fortify encryption strength.
Optimized Visualization of Digital Image Steganography using Least Significant Bits and AES for Secret Key Encryption Jatmoko, Cahaya; Sinaga, Daurat; Lestiawan, Heru; Astuti, Erna Zuni; Sari, Christy Atika; Shidik, Guruh Fajar; Andono, Pulung Nurtantio; Yaacob, Noorayisahbe Mohd
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 3, August 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i3.2252

Abstract

Data hiding is a technique used to embed secret information into a cover medium, such as an image, audio, or video, with minimal distortion, ensuring that the hidden data remains imperceptible to an observer. The key challenge lies in embedding secret information securely while maintaining the original quality of the host medium. In image-based data hiding, this often means ensuring the hidden data cannot be easily detected or extracted while still preserving the visual integrity of the host image. To overcome this, we propose a combination of AES (Advanced Encryption Standard) encryption and Least Significant Bit (LSB) steganography. AES encryption is used to protect the secret images, while the LSB technique is applied to embed the encrypted images into the host images, ensuring secure data transfer. The dataset includes grayscale 256x256 images, specifically "aerial.jpg," "airplane.jpg," and "boat.jpg" as host images, and "Secret1," "Secret2," and "Secret3" as the encrypted secret images. Evaluation metrics such as Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Unified Average Changing Intensity (UACI), and Number of Pixels Changed Rate (NPCR) were used to assess both the image quality and security of the stego images. The results showed low MSE (0.0012 to 0.0013), high PSNR (58 dB), and consistent UACI and NPCR values, confirming both the preservation of image quality and the effectiveness of encryption for securing the secret data.
Co-Authors Abdussalam Abdussalam, Abdussalam Agus Setiawan Agustina, Feri Akrom, Ahmad Alfany, Fauzan Maulana Alvin Faiz Kurniawan Award Widya Laksana, Deddy Candra Irawan Candra Irawan Christy Atika Sari Danu Hartanto Daurat Sinaga Daurat Sinaga De Rosal Ignatius Moses Setiadi Deddy Award Widya Laksana Doheir, Mohamed Edi Sugiarto Edi Sugiarto Edi Sugiarto Eko Hari Rachmawanto Elkaf Rahmawan Pramudya Erna Zuni Astuti Feri Agustina Feri Agustina Florentina Esti Nilawati Guruh Fajar Shidik Hadi, Heru Pramono Hedriyanto, Novi Heribertus Himawan Heru Lestiawan Heru Lestiawan Ifan Rizqa L. Budi Handoko Laksana, Deddy Award Widya Lalang Erawan Lalang Erawan Marjuni, Aris Noor Ageng Setiyanto, Noor Ageng Nova Rijati Nur Rokhman Nur Rokhman Pulung Nurtantio Andono Saifullah, Zidan Setia Astuti Sinaga, Daurat Sinaga, Daurat Sindhu Rakasiwi Solichul Huda, Solichul suprayogi Suprayogi Suprayogi Suprayogi Suprayogi Suprayogi Suprayogi Wellia Shinta Sari Widya Laksana, Deddi Award Yaacob, Noorayisahbe Mohd