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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. 3 No. 2 (2023): International Journal of Electronics and Communications System" : 5 Documents clear
Design and Construction of an Automation Tool for Feeding Pokdakan Pesawaran Fish Saputra, Ricco Herdiyan; Hendrawan, Eko
International Journal of Electronics and Communications Systems Vol. 3 No. 2 (2023): 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.v3i2.19750

Abstract

This study focuses on developing an automated feeding tool for fish farming in Pesawaran, a region known for its aquaculture potential. Aquaculture, crucial for global food needs, requires efficient and sustainable management, especially in feeding, a critical factor in fish growth and health. Traditional manual feeding methods are time-consuming and prone to errors, affecting fish productivity and growth. The research aimed to enhance feed management efficiency, minimize feeding errors, and improve the sustainability and productivity of fish farming in Pesawaran. The initial phase involved analyzing the needs of fish farmers, environmental factors, and fish species. The design of the automation tool emphasized ergonomics, reliability, and ease of use. The Rapid Application Development (RAD) method was employed, focusing on quick and iterative development. This method was applied at the Pokdakan Pemuda Tani RPL in Negeri Sakti Village, Gedong Tataan District, Pesawaran Regency, from July to November 2023. The application of RAD in designing the Pokdakan Pesawaran fish-feeding automation tool yielded positive outcomes. The fast, responsive development process, which actively involved users, led to a practical solution well-received by the fish farming community. This research demonstrates the value of RAD principles in providing practical, locally relevant solutions and guiding the development of adaptive, user-oriented aquaculture technology.
Analyzing Airline Services and Communication Systems by Designing Machine Learning Model to Predict Passenger Satisfaction Iskandar, Rodzan; Anies, Okta Reni Azrina Rasyid; Iskandar, Rusydi; Kesuma, Mezan el-Khaeri; Konecki, Mario
International Journal of Electronics and Communications Systems Vol. 3 No. 2 (2023): 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.v3i2.19782

Abstract

This research explores the methods of assessing airline passenger satisfaction through surveys and analyzing factors that are strongly linked to whether a passenger is satisfied or dissatisfied. The aim is also to investigate if it is possible to predict passenger satisfaction levels. The dataset used in this study comes from a Kaggle dataset titled "Airline Passenger Satisfaction," which includes 223,690 records with 23 measurement variables and 1 response variable. It identifies three key factors critical to airline service improvement: delays, online boarding, and class. Airlines can enhance their service offerings by focusing on these areas as air travel activities pick up. Specifically, online boarding is highlighted as a significant factor in reducing the need for manual check-ins and waiting in queues, thereby providing a faster and more efficient process. Furthermore, the study's analysis of categorical data and its correlation with satisfaction levels yields important insights into customer preferences within the airline industry. The differentiation between loyal and disloyal customers, as visualized in the study, shows that many loyal customers are dissatisfied. This points to the fact that loyal customers, despite their overall satisfaction, have faced varying levels of service quality.
Analysis and Implementation of Comparison Between Podman and Docker in Container Management Husain, Husain; Marzuki, Khairan; lauw, Christopher Michael; Azhar Mardedi, Lalu Zazuli
International Journal of Electronics and Communications Systems Vol. 3 No. 2 (2023): 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.v3i2.19860

Abstract

The increasing use of the internet makes the implementation process more accessible, but the problem is that it is difficult to manage network management, with the emergence of container technologies such as Docker and Podman as efficient application management solutions. This research compares Docker and Podman regarding container management using the Network Development Life Cycle (NDLC) methodology. This study evaluates three parameters: accessing the Fedora project registry, handling images or ISOs, and user access in containers. The results show that Podman performs better regarding registry access, is slightly faster with images, and offers faster user creation. Overall, the study concludes that Podman is superior, demonstrating compatibility with Docker and proving its efficacy in container management.
Development of Lampung Script Characters Recognition Model using TensorFlow Muhammad, Meizano Ardhi; Martinus, Martinus; Nurhartanto, Adhi; Mulyani, Yessi; Djausal, Gita Paramita; Achmad, Deni; Ferbangkara, Sony
International Journal of Electronics and Communications Systems Vol. 3 No. 2 (2023): 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.v3i2.19878

Abstract

In the face of cultural erosion, particularly the dwindling proficiency in deciphering Lampung characters, this research pioneers an innovative approach to cultural preservation. The Lampung character recognition model was developed using TensorFlow, a robust computer vision and machine learning framework. Convolutional Neural Networks (CNN) are integrated to enhance the image processing capabilities. The research employs the Design Science Research methodology, emphasizing problem identification, solution objectives, design and development, demonstration, evaluation, and communication. The dataset, comprising 3900 instances, is meticulously collected and features diverse Lampung script writing. Through preprocessing and classification, the model undergoes training with an 80:10:10 split for training, validation, and test data. The architecture includes CNN layers with ReLu activation functions, and transfer learning is employed using the MobileNet V2 network model. Demonstrating commendable performance, the model achieves an accuracy spectrum of 0.652 to 0.998. The research not only underscores the viability of the TensorFlow model but also establishes a foundation for future explorations in preserving Lampung cultural heritage. This intersection of advanced machine learning and cultural preservation signifies a promising synergy, ensuring the enduring legacy of Lampung characters amid societal and technological transformations.
Analysis of Google Stock Prices from 2020 to 2023 using the GARCH Method Athaulloh, M Farhan; Mubarok, Husni Na’fa; Sharov, Sergii; Hati, Berliyana Kesuma; Muthoharoh, Luluk; Alvionita, Mika
International Journal of Electronics and Communications Systems Vol. 3 No. 2 (2023): 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.v3i2.20899

Abstract

This research focuses on Google's share price movements, considering their significant impact on the financial market, using Google's share price data from 2020 to 2023. The aim is to analyze error variance and forecast and provide valuable information to stockbrokers and investors. The ARMA model has shortcomings in dealing with volatility, so the GARCH model is used to overcome it. Research methods include financial data analysis, preprocessing, and modeling with GARCH. The rolling forecast method describes changes in price patterns over time. Evaluation using MAPE validates the prediction accuracy of the ARIMA model. The best model chosen with the most negligible AIC value criteria was the ARIMA(3,0,2)GARCH(1,1) model. The forecasting results show accurate stock price predictions with an average MAPE value of 20.7 percent. This research provides an essential basis for brokers and investors in making investment decisions based on a deep understanding of the dynamics of Google's share price movements in the above time frame.

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