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Journal of Computer Science Artificial Intelligence and Communications
Published by CV. Raskha Media Group
ISSN : 31093981     EISSN : 31089828     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Earth & Planetary Sciences Engineering
Journal of Computer Science Artificial Intelligence and Communications is a multidisciplinary, peer-reviewed journal dedicated to advancing research in computer science, artificial intelligence (AI), and communication technologies. The journal publishes high-quality original articles, reviews, and case studies that explore the latest innovations, theories, algorithms, and applications shaping the digital world. Focused on the intersection of computational systems, intelligent automation, and seamless communication networks, JOCSAIC aims to foster collaboration and knowledge exchange among researchers, practitioners, and academics working across diverse sectors such as data science, machine learning, telecommunications, and intelligent systems. The journal is a key resource for cutting-edge developments and trends in these transformative fields.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 22 Documents
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Evaluation of the Usability of the Academic Information System Using the System Usability Scale (SUS) Method Rahardian, Rifky Lana; Khodijah, Siti; Rizki, Cindy Atika
Journal of Computer Science, Artificial Intelligence and Communications Vol 2 No 2 (2025): November 2025
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v2i2.62

Abstract

The increasing reliance on digital platforms in higher education necessitates the evaluation of system usability to ensure effective user interaction and satisfaction. This study aims to evaluate the usability of the Academic Information System (AIS) at [University Name] using the System Usability Scale (SUS) method. SUS is a reliable, standardized tool for measuring the usability of interactive systems, providing a quick and quantitative assessment. Data were collected from a sample of 100 students and academic staff who frequently use the AIS for various academic activities, including course registration, grade checking, and academic planning. The results of the SUS analysis yielded an average score of 72.5, indicating that the system falls within the “Good” usability category. However, several usability issues were identified, such as navigation complexity and visual layout inconsistencies, which slightly reduced user satisfaction. These findings highlight the importance of continuous usability testing and user-centered design in the development of academic systems. The study recommends specific design improvements to enhance user experience and system performance. Overall, the SUS method proved effective in identifying usability strengths and weaknesses, offering valuable insights for future system optimization.
Development of an Employee Performance Monitoring Information System Using a Web-Based Interactive Dashboard Prayoga, Abil Alwi; Hasanuddin, Muhammad; Khodijah, Siti; Rizki, Cindy Atika
Journal of Computer Science, Artificial Intelligence and Communications Vol 2 No 2 (2025): November 2025
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v2i2.63

Abstract

This research aims to develop an employee performance monitoring information system that utilizes a web-based interactive dashboard to enhance decision-making and managerial oversight. In many organizations, traditional performance evaluation methods are often time-consuming, static, and lack real-time insight, resulting in inefficiencies in performance tracking. To address these challenges, the proposed system is designed to provide dynamic visualization of key performance indicators (KPIs), attendance records, task completion rates, and other critical metrics through an interactive and user-friendly dashboard interface. The development process follows the Waterfall methodology, encompassing stages of requirements analysis, system design, implementation, testing, and deployment. The system was built using PHP and JavaScript for front-end interactivity, with a MySQL database to manage data storage. The dashboard includes various visual tools such as graphs, charts, and progress bars to facilitate real-time monitoring and performance analysis. Testing results indicate that the system performs effectively, offering accurate and timely information that supports employee evaluation and organizational planning. User feedback also reveals a high level of satisfaction due to the dashboard's ease of use and responsiveness. Overall, the implementation of this web-based performance monitoring system is expected to improve transparency, accountability, and productivity within the organization.

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