Data Visualization Analysis in the Management Information System for Submitting Credit Scores for Education Personnel

Journal Title: International Journal of Social Science And Human Research - Year 2023, Vol 6, Issue 11

Abstract

Education staff have an important role in facilitating the implementation of the tridharma of higher education and are an indicator of educational administration success. This study looks at how data visualization was implemented in the Management Information System for Submitting Credit Scores for Education Personnel. The research is primarily concerned with the Functional Position of Intermediate Expert Computer Staff. The study's goal is to create web-based data visualization tools to enable submitting and assessing credit scores for Intermediate Computer Experts easier, thereby meeting the requirement for efficiency and accuracy in the promotion and position process. This study employs a research and development (R&D) methodology with an iterative prototype approach. The initial step involves a needs analysis, including an in-depth understanding of the Associate Computer Expert promotion process and the associated administrative requirements. Next, a web-based data visualization prototype was designed, which included an intuitive user interface, database integration, and a credit number calculation algorithm. The prototype was then implemented and tested on a limited basis in the IPDN environment. The proposed system is designed to provide easy access, facilitate data verification, and enable computerized sorting and calculation of credit numbers. The main contribution of this research lies in developing information technology solutions that can increase the transparency and effectiveness of administrative processes in the IPDN environment. It is hoped that the output of this research can provide conceptual and practical contributions to managing the credit figures for educational staff and provide a basis for developing similar systems in other educational institutions.

Authors and Affiliations

Edy Supriyono, Etin Indrayani, Rudi Riki Ramdani, Wirman Syafri

Keywords

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  • EP ID EP724951
  • DOI 10.47191/ijsshr/v6-i12-27
  • Views 69
  • Downloads 0

How To Cite

Edy Supriyono, Etin Indrayani, Rudi Riki Ramdani, Wirman Syafri (2023). Data Visualization Analysis in the Management Information System for Submitting Credit Scores for Education Personnel. International Journal of Social Science And Human Research, 6(11), -. https://www.europub.co.uk/articles/-A-724951