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Journal of Computer Science Advancements
Published by Yayasan Adra Karima Hubbi
ISSN : 30263379     EISSN : 3024899X     DOI : https://doi.org/10.70177/jsca
Core Subject : Science,
Computer Science & IT
Journal of Computer Science Advancements is an international peer-reviewed journal dedicated to interchange for the results of high quality research in all aspect of science, engineering and information technology. The journal publishes state-of-art papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the advancement of science and technology, the Journal of Computer Science Advancements follows the open access policy that allows the published articles freely available online without any subscription.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 86 Documents
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Quality of Service Management Solution Becomes a Software-Defined Network Challenge Syamsu, Muhajir; Jixiong, Cai; Jie, Lie
Journal of Computer Science Advancements Vol. 1 No. 4 (2023)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v1i4.582

Abstract

The use of Software-Defined Networking (SDN) has created a huge leap in the management of computer networks. SDN offers flexibility and the ability to dynamically manage networks, but along with its advantages, it also brings significant challenges in managing quality of service (QoS). QoS is critical to maintaining performance and user experience in increasingly complex and distributed network environments. The research method uses Solution Development to address a quality of service (QoS) management challenge and solution in Software Defined Networking with the approach of designing and developing practical solutions to address QoS management issues and challenges in SDN environments. Control Separation and Data Plane are centralized network control at the SDN controller, while the data plane reside in the networks hardware, both capable of maintaining QoS and a challenges in SDN with a computer network approach that separates the control layer from the data layer, enabling more flexible and centralized network management. Research conclusions related to SDN Software Defined Networking quality of service management problems and solutions, focusing on the problem of separating management and data levels. The separations of control and data plane concept in SDN has great potential to improve flexibility, scalability and more efficient network management.
The Quality of Operational Performance of STIE Indonesia Banking School Student Organization with Remotely Operationally (Study on STIE Indonesia Banking School Student Organization in the 2020/2021 Period) Argakoesoemah, Mohamad Ramadhan; Nugraha, Rifqi Alif; Christinadhi, Dhea Ananda; ylvia, Donna
Journal of Computer Science Advancements Vol. 1 No. 4 (2023)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v1i4.594

Abstract

This study is focused on identifying the influence of communication, organizational culture and work-from-home on performance to study in student organizations of STIE Indonesia Banking School in the 2020/2021 period. The questionnaire was distributed to 99 respondents and data were analyzed through SmartPLS version 3.3.3. The results of this study indicate that 1) There is a positive influence between Communication and Performance; 2) There is a positive influence between Organizational Culture and Performance; 3) There is no influence between Work from Home and Performance; 4) There is a positive influence between Organizational Culture and Communication; 5) There is a positive influence between Work from Home and Organizational Culture.
Anxiety Description of Social Workers in Assisting Children in Conflict with the Law Yazid, M. Hikmal
Journal of Computer Science Advancements Vol. 1 No. 4 (2023)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v1i4.606

Abstract

Anxiety, a pervasive emotion in the realm of social work, takes center stage in the experiences of professionals dedicated to assisting children entangled in the legal system. This study undertakes a comprehensive exploration of the nuanced landscape of anxiety among social workers, delving into the background, aims, scope, methodology, and key findings. Against the backdrop of escalating rates of youth involvement in criminal activities, the study aims to unravel the psychological dimensions of social workers tasked with the rehabilitation and support of juvenile offenders. Utilizing a mixed-methods approach, the research investigates the correlation between case severity, institutional support, coping mechanisms, and the anxiety levels experienced by social workers. The findings not only reveal varying degrees of anxiety but also underscore the significant influence of organizational support and coping strategies. This study contributes valuable insights for practitioners, policymakers, and educators, emphasizing the need for tailored interventions to support the well-being of social workers engaged in this emotionally demanding field. As social work continues to intersect with the legal complexities surrounding juvenile justice, a nuanced understanding of anxiety becomes imperative for fostering effective and sustainable interventions.
Development of a Delphi Based Ultrasonic Testing Expert System Dwi Cahyono, Bagus
Journal of Computer Science Advancements Vol. 1 No. 4 (2023)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v1i4.614

Abstract

A person who has the expertise to operate ultrasonic testing in the field of ultrasonic called experts. Currently very difficult to obtain an ultrasonic expert in an industry. For the expert knowledge of ultrasonic testing is adopted in the computer system. This system called Expert System Type of Disability Determination Using Ultrasonic Welding The Delphi Program. This expert system is used to determine the classification of weld defects in determining the acceptance / rejection of defective welds. In the expert system can also be used to determine the type of weld defects based on defect indications obtained. In addition to the expert system there is an explanation of ultrasonic, calibration procedures and procedures for ultrasonic inspection. In the expert system is the input data that shows an ultrasonic flaw manually entered into the computer. In building an expert system software to use Delphi 7 and Inno Compiler Set Up the installer. Expert systems can be used by people who are just learning the ultrasonic as a tool to determine the acceptance / rejection of defective welds. The results showed that the Expert System Determining the type of defect indications welding able to identify all the defective welds of the inspection. Acceptance of material is observed in accordance with AWS D1.1 acceptance
Utilization of Hotspot Network Bandwidth Management at SMK Muhammadiyah Parkan Rahmah, Zihan Fauziah; Wathoni, Mahbubul; Efendi, Yasin
Journal of Computer Science Advancements Vol. 1 No. 5 (2023)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v1i5.619

Abstract

Mikrotik is a routing activity using Wireless Local Area Network (W-LAN) technology. Mikrotik is an operating system and software used to function a computer as a router. The model used in this study refers to the PPDIOO type development model with 6 stages, namely Prepare, Plan, Design, Implement, Operate, and Optimize. Validity tests and effectiveness tests include the product being able to run optimally and successfully improving the quality of existing network bandwidth. Data collection instruments used interviews and observation. Data collection was carried out in November 2022 at Muhammadiyah Parakan Vocational School. The results of the material expert validity test were 92%, the media expert validity test was 80%, the teacher response effectiveness test was 80% and the student effectiveness test was 88%
Fuzzy C-Means and K-Means Methods Comparison for the Detection of Diabetes Subarja, Roy Efendi; Hendrik, Billy
Journal of Computer Science Advancements Vol. 1 No. 5 (2023)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v1i5.620

Abstract

The necessity for precise and effective disease detection techniques has increased due to the rising incidence of diabetes. The main objective of this study is to assess how well the fuzzy C-Means and K-Means clustering algorithms detect diabetes. Based on pertinent medical data, the study attempts to examine how well these two clustering approaches identify cases of diabetes. For testing, a dataset with a variety of health and diagnostic indicator variables was used. Metrics including sensitivity, specificity, accuracy, and F1-score were used to evaluate the detection performance of the Fuzzy C-Means and K-Means algorithms that were used to cluster the dataset. Based on several evaluation criteria, the results show that both clustering approaches have promising potential for diabetes identification. However, their performance varies. This study sheds light on the advantages and disadvantages of clustering algorithms and advances our understanding of their suitability for diabetes identification. Improved diagnosis precision and early diabetes management intervention could result from more optimization and validation of these algorithms
Implementation of Neural Key Generation Algorithm For IoT Devices Guitouni, Zied; Zairi, Aya; Zrigui, Mounir
Journal of Computer Science Advancements Vol. 1 No. 5 (2023)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v1i5.637

Abstract

In the realm of Internet of Things (IoT) systems, the generation of cryptographic keys is crucial for ensuring secure data transmission and device authentication. However, traditional methods of generating random keys encounter challenges about security, efficiency, and scalability, particularly when applied to resource-constrained IoT devices. To address these issues, neural networks have emerged as a promising approach due to their ability to learn intricate patterns. Nonetheless, the architecture of neural networks significantly impacts their performance. This paper presents a comprehensive comparative analysis of three commonly employed neural network architectures for generating cryptographic keys on IoT devices. We propose a novel neural network-based algorithm for key generation and implement it using each architecture. The models are trained to generate cryptographic keys of various sizes from random input data. Performance evaluation is conducted based on key metrics such as accuracy, loss, key randomness, and model complexity. Experimental results indicate that the Feedforward Neural Network (FFNN) architecture achieves exceptional accuracy of over 99% and successfully passes all randomness tests, surpassing the alternatives. Convolutional Neural Networks (CNNs) demonstrate subpar performance as they emphasize spatial features that are irrelevant to key generation. Recurrent Neural Networks (RNNs) struggle with the complex long-range dependencies inherent in generating keys
Arduino-based Automatic Fish Feeding Device Prototype Nugraha, Muhammad Iqbal; Cahyono, Bagus Dwi
Journal of Computer Science Advancements Vol. 1 No. 5 (2023)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v1i5.641

Abstract

Consuming fish food is an important part of the process of growing and maintaining fish. In general, fish food is given by conventionally throwing it by hand. However, this is not done at the same time every day. Based on the problems above, the researchers made a prototype of an Arduino-based automatic fish feeding device. The aim of this research is to determine the effectiveness of the automatic fish feeder prototype. In the prototype that the researchers made using several main components such as Arduino Uno as the system or brain of this prototype, servo motor, 20 x 4 LCD, buttons, Real Time Clock (RTC), and several jumper cables. The effectiveness of this tool can be seen from the test results, where the automatic fish feeder prototype succeeded in providing fish food according to a predetermined schedule.
Innovative Educational Game: Designing and Developing Interactive Web-Based Memory Card Games as an Educational Media for Children Helda, Nurul; Sanusi , Sanusi; Suhendra, Rivansyah
Journal of Computer Science Advancements Vol. 1 No. 5 (2023)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v1i5.674

Abstract

In the dynamic landscape of children’s education, innovation plays a pivotal role in shaping engaging and effective learning experiences. This research focuses on the design and development of an interactive web-based memory card game as an innovative educational tool. Grounded in the waterfall method, the development process prioritizes sequential stages to ensure robustness. Performance testing, using PageSpeed Insights, evaluates the game’s speed and efficiency, aiming to enhance user experience. The results, showcased by a remarkable score of 99, affirm the careful consideration given to optimization techniques. This research not only contributes to the broader understanding of game-based learning but also provides concrete insights for developers. The memory card game stands as a testament to the seamless integration of technological innovations into children’s education, promising enduring contributions to the future of learning.  
Impact of Using Big Data Analisys in Increasing Personalization of Learning Rahmawati, Rahmawati; Nursalim, Nursalim; Alfiah, Agry; Hasyim, Andi; Fawait, Aldi Bastiatul
Journal of Computer Science Advancements Vol. 2 No. 2 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i2.906

Abstract

In today’s digital era, big data analytics has become a very relevant topic to improve learning personalisation as it can collect and analyse very large and complex data. Big data analytics can lead to a more efficient learning system by collecting and analysing huge and complex data. In education, big data analytics can be used to understand students’ learning behaviour, their needs and preferences, so that learning and learning outcomes can be improved. This research is conducted with the aim of using big data analytics to improve learning personalisation. It also aims to find out the challenges of using big data analytics to improve learning personalisation. The method used in this research is quantitative method. This method is a way of collecting numerical data that can be tested. Data is collected through the distribution of questionnaires addressed to students. Furthermore, the data that has been collected from the distribution of the questionnaire, will be accessible in Excel format which can then be processed with SPSS. From the research results, it can be seen that the big data analysis has shown that the use of more detailed and accurate data can help teachers find students’ special needs and improve learning effectiveness. As a result, teachers can create learning strategies that are better suited to students’ needs and improve their learning outcomes. From this study, we can conclude that the use of big data analytics in improving personalisation allows teachers to understand better the individual needs and preferences of students, so that more suitable learning plans can be developed and student engagement can be improved.

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