Joko Sunadi
Universitas Putra Indonesia YPTK Padang

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Penerapan Metode Copras dalam Pemilihan Kepala Pengendalian Mutu (Head Of Quality Control) Joko Sunadi; Asriwan Guci; Abrar Tanjung
JOSTECH Journal of Science and Technology Vol 3, No 2: September 2023
Publisher : UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/jostech.v3i2.6885

Abstract

In the selection of the current Head of Quality Control is appointed manually based solely on the information provided in the application and the decisions that have been raised are inaccurate and cause delays causing the assessment not to be completed. In addition, when recruiting the Head of Quality Control manually, there are several things that can cause problems, such as hiring a Head of Quality Control who does not meet the criteria set by the company, carrying out a slow selection process, and others. The methodology used is the Complex Proportional Assessment (COPRAS) method, which is an approach used to collect data and develop systems and applications to assist companies in making decisions based on common problems. The calculation results with COPRAS were obtained from 10 selected employees, the highest UI score of 100 and the lowest of 52.18. Companies can find qualified managers who meet organizational standards by implementing a decision support system based on this COPRAS methodology.
Artificial Intelligence–Based Information Systems to Support Educational Decision-Making Yaslinda Lizar; Joko Sunadi; Aswirman Guci
AT-TA'LIM Vol 32, No 3 (2025)
Publisher : Institut Agama Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/jt.v32i3.904

Abstract

This study explores the potential of artificial intelligence–based information systems in supporting educational processes within higher education institutions in Indonesia. The rapid adoption of digital platforms in academic administration and learning management has increased the need for intelligent systems that can enhance efficiency, transparency, and data-driven decision-making. This research aims to examine how artificial intelligence–based information systems are utilized in educational contexts, particularly in relation to curriculum implementation, academic management, and institutional readiness. A qualitative research design was employed using semi-structured interviews with academic stakeholders, complemented by document analysis. The findings indicate that artificial intelligence–based information systems contribute positively to improving administrative efficiency, supporting systematic curriculum evaluation, and facilitating evidence-based academic decision-making. However, challenges related to system transparency, interpretability, and user readiness were also identified as critical factors influencing system effectiveness. These findings highlight that the successful integration of artificial intelligence in education is not solely determined by technological capability but also by organizational support and human factors. This study contributes to the interdisciplinary integration of information systems and educational research by providing empirical insights into the role of artificial intelligence in higher education. The results offer practical implications for institutions seeking to adopt responsible and effective artificial intelligence–based information systems.