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International Journal of Electronics and Communications Systems
Published by Universitas Islam Negeri Raden Intan Lampung
ISSN : -     EISSN : 27982610     DOI : 10.24042
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electronics and Communications System (IJECS) [e-ISSN: 2798-2610] is a medium communication for researchers, academicians, and practitioners from all over the world that covers issues such as the improvement about design and implementation of electronics devices, circuits, and communication systems including but not limited to: circuit theory, integrated circuits, analog circuits, digital circuits, mixed-signal circuits, electronic components, filters, oscillators, biomedical circuits, neuromorphic circuits, RF circuits, optical communication systems, microwave systems, antenna systems, communications circuits for optical communication, development of physics evaluation instruments, development of physics instructional media, digital signal processing, communication theory and techniques, modulation, source and channel coding, microwave theory and techniques, wave propagation and more.
Arjuna Subject : Ilmu Komputer (semua kategori) - Jaringan Komputer dan Komunikasi
Articles 5 Documents
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Search results for , issue "Vol. 2 No. 2 (2022): International Journal of Electronics and Communications System" : 5 Documents clear
Application of Domain Keys Identified Mail, Sender Policy Framework, Anti-Spam, and Anti-Virus: The Analysis on Mail Servers Marzuki, Khairan; Hanif, Naufal; Hariyadi, I Putu
International Journal of Electronics and Communications Systems Vol. 2 No. 2 (2022): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v2i2.13543

Abstract

Viruses spread through email are often sent by irresponsible parties that aim to infect email users' servers. This background encouraged the author to analyze the application of DKIM, SPF, anti-spam, and anti-virus to avoid spam, viruses, and spoofing activities. The goal is for the server to prevent spam, spoofing, and viruses to ensure the security and convenience of email users and prevent the impact of losses caused by them. The design and analysis of DKIM, SPF, anti-spam, and anti-virus applications use the NDLC methodology. The process includes designing spam, spoofing, and virus filtering systems and performing installation and configuration simulations. The next stage is implementation, during which the previously developed system is tested on the spam filtering system, spoofing, and viruses. The last stage is the monitoring stage, where supervision is conducted on the approach to determine its success level. This study concludes that applying the DKIM protocol can prevent spoofing through private and public key-matching methods for authentication. Meanwhile, the application of the SPF protocol can prevent spoofing by authorizing the IP address of the sending server. Additionally, SpamAssassin, ClamAV and Amavisd-New can prevent spam and viruses from entering by checking email headers, bodies, and attachments.
Comparison Study of Convolutional Neural Network Architecture in Aglaonema Classification Mulyani, Yessi; Septiangraini, Dzihan; Muhammad, Meizano Ardhi; Nama, Gigih Forda
International Journal of Electronics and Communications Systems Vol. 2 No. 2 (2022): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v2i2.13694

Abstract

Convolutional Neural Network (CNN) is very good at classifying images. To measure the best CNN architecture, a study must be done against real-case scenarios. Aglaonema, one of the plants with high similarity, is chosen as a test case to compare CNN architecture. In this study, a classification process was carried out on five classes of Aglaonema imagery by comparing five architectures from the Convolutional Neural Network (CNN) method: LeNet, AlexNet, VGG16, Inception V3, and ResNet50. The total dataset used is 500 image data, with the distribution of training data by 80 percent and test data by 20 percent. The segmentation process is performed using the Grabcut algorithm by separating the foreground and background. To build a model for CNN architecture using Google Colab and Google Drive storage. The results of the tests carried out on five classes of Aglaonema images obtained the best accuracy, precision, and recall results on the Inception V3 architecture with values of 92.8 percent, 93 percent, and 92.8 percent. The CNN architecture has the highest level of accuracy in classifying aglaonema plant types based on images. This study seeks to close research gaps, contribute to the field of research, and serve as a platform for primary prevention research.
Palm Tree Coplanar Vivaldi Antenna Array on the Same Substrate Size: Design and Performance Evaluation Nurhayati, Nurhayati; De Oliveira, Alexandre Manicoba; Yasin, Mohd Najib Bin Mohd; Kurniawan, Dayat
International Journal of Electronics and Communications Systems Vol. 2 No. 2 (2022): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v2i2.14221

Abstract

This paper aims to describe the performance of the palm tree Coplanar Vivaldi Antenna Array (CVA) that was simulated from 0.25-6.25 GHz in terms of return loss and radiation pattern. Palm Tree Coplanar Vivaldi Antenna is available in four different configurations: single-element, two-element array, four-element array, and an eight-element array. We create a feeding network and radiator patch for two, four, and eight-array antennas. The simulation results demonstrate that the single-element antenna has the best return loss performance and can cover all frequency work from 0.25-6.25 GHz. In contrast, the antenna array can only cover multiband frequency. At 3 GHz, a single-element antenna has a directivity of 8.77 dBi, a sidelobe level of -2.2 dB, and a beamwidth of 63.70. In contrast, an antenna array of 8 elements has a directivity of 15.5 dBi, a sidelobe level of -12.6 dB, and a beamwidth of 80. Using the same substrate size, by configuring the Vivaldi Coplanar antenna to be an array at a frequency of 3 GHz, the 1×8 array antenna has a 6.73dBi improvement in directivity, a 10.4 dB boost in side lobe level, and a 55.70 enhanced in beamwidth performance compared to a single element. According to the simulation findings, the radiation pattern performance of the. Palm Tree CVA is greater than a single element in the same substrate size. Good directivity, SLL, and beamwidth performance make the proposed Palm Tree CVA array suitable for integration in telecommunication, radar, or cognitive radio applications.
Deep Transfer Learning Networks for Brain Tumor Detection: The Effect of MRI Patient Image Augmentation Methods Abdalla, Peshraw Ahmed; Qadir, Abdalbasit Mohammed; Rashid, Omed Jamal; Rawf, Karwan M. Hama; Abdulrahman, Ayub O; Mohammed, Bashdar Abdalrahman
International Journal of Electronics and Communications Systems Vol. 2 No. 2 (2022): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v2i2.14815

Abstract

The exponential growth of deep learning networks has enabled us to handle difficult tasks, even in the complex field of medicine with small datasets. In the sphere of treatment, they are particularly significant. To identify brain tumors, this research examines how three deep learning networks are affected by conventional data augmentation methods, including MobileNetV2, VGG19, and DenseNet201. The findings showed that before and after utilizing approaches, picture augmentation schemes significantly affected the networks. The accuracy of MobileNetV2, which was originally 85.33 percent, was then enhanced to 96.88 percent. The accuracy of VGG19, which was 77.33 percent, was then enhanced to 95.31 percent, and DenseNet201, which was originally 82.66 percent, was then enhanced to 93.75 percent. The models' accuracy percentage engagement change is 13.53 percent, 23.25 percent, and 23.25 percent, respectively. Finally, the conclusion showed that applying data augmentation approaches improves performance, producing models far better than those trained from scratch.
Usability Methodologies and Data Selection: Assessing the Usability techniques on Educational Websites Abdulrahman, Ayub Othman; Hama Rawf, Karwan Mahdi
International Journal of Electronics and Communications Systems Vol. 2 No. 2 (2022): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v2i2.15045

Abstract

The purpose of an educational website is to efficiently provide up-to-date services and resources to students, faculty, and staff. However, the needs of university students are not always prioritized throughout the design phase of websites; instead, technological considerations, organizational concerns, and commercial goals may all drive the process. When it comes to meeting the demands of the target audience, website designers often fall short. At the same time, visitors may encounter a wide variety of usability issues while visiting the sites. Thus, the purpose of this study is to examine the efficacy of different approaches to evaluating the usability of university websites from the viewpoint of their target audiences via user-based testing and questionnaire methods involving actual users. The outcomes, which are based on data from tests conducted in real time, outline the difficulties and advantages associated with each strategy. Both a user-based test and a questionnaire, which are both trustworthy evaluation methodologies, were used in the process of analyzing and evaluating the websites.

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