Computational Support in Academic Peer Review: An Artificial Intelligence Perspective

Riswahyuni Widhawati; Suryari Purnama; Herman Purwoko Putro; Lumi Gantari; Shakeel Rahagi

doi:10.34306/ajri.v6i1.1106

Authors

Riswahyuni Widhawati Universitas Ichsan Satya
Suryari Purnama Universitas Esa Unggul
Herman Purwoko Putro Universitas Ichsan Satya
Lumi Gantari ADI Journal Incorporation
Shakeel Rahagi Eesp Incorporation

DOI:

https://doi.org/10.34306/ajri.v6i1.1106

Keywords:

Academic Peer Review, Artificial Intelligence, Peer Review Efficiency, Machine Learning Algorithms, Big Data Modeling

Abstract

Academic Peer Review is a critical step in the scientific publication process, ensuring the quality and reliability of research work. In this context, this research explores how Artificial Intelligence (AI) can provide valuable computational support in the academic peer review process. This study outlines a perspective that investigates how AI technology can be leveraged to enhance the efficiency, speed, and accuracy of academic peer review. We investigate various methods and tools that can be utilized to support peer review, including the application of machine learning algorithms to identify weaknesses and strengths in manuscripts, as well as the utilization of big data modeling to identify significant research trends. The findings of this research have the potential to pave the way for significant improvements in the academic peer review process, ultimately enhancing the quality of scientific publications and expediting scientific discoveries.

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