Background of study: The evolution of cloud computing has transformed server management, yet many management interfaces remain web-based and are not optimized for mobile devices. aaPanel, a popular server control panel, also faces this challenge of providing a mobile-friendly monitoring experience.

Aims and scope of paper: This research aims to design and build a mobile application named "aaPanel Mobile" to efficiently monitor vital server statistics on Android devices, addressing the gap in mobile accessibility for aaPanel users.

Methods: The software development follows the Waterfall model, covering requirements, design, development, testing, deployment, and maintenance. The application was built using Expo React Native, integrates with the aaPanel API for data retrieval, and its functionality was verified through black-box testing.

Result: Testing results confirmed that all primary functionalities were successfully implemented. The application correctly displayed resource usage statistics, provided real-time data updates, and listed websites as expected.

Conclusion: The "aaPanel Mobile" application has met its design and functional objectives, proving to be a viable tool ready for use in a production environment to help administrators monitor servers from anywhere.

Background of Study: Big data visualization and visual analytics are essential in social media analysis because they help process large and complex data into more understandable information. With this technique, we can identify patterns, trends, and relationships in social media data, such as user interactions and social influences, that are difficult to analyze without visualization tools. This allows for faster, more accurate, and in-depth analysis, and helps with data-driven decision-making in a variety of areas.

Aims and Scope of Paper:  The purpose of this paper is to review the literature related to big data visualization and visual analytics in the context of social media, using bibliometric analysis methods to identify current trends, techniques used, and important tools.

Methods: This study used a bibliometric design to analyze the literature in the Scopus database with three main keyword combinations: "Big Data Visualization" AND "Social Media Analysis", "Visual Analytics" AND "Bibliometric Analysis", as well as "Data Visualization" AND "Social Media Analytics". The literature analyzed consisted of journals published between 2015 and 2025.  After data collection, filtering is carried out using OpenRefine to eliminate bias and duplication, ensure the accuracy and validity of the data, resulting in objective insights into trends in data visualization and social media analytics.

Results: A summary of key findings on the most widely used techniques and tools in big data visualization on social media.

Conclusion: Closing on the contribution of bibliometric analysis in understanding the development of big data visualization in social media research.