Design of an Automated Verification to Improve the Efficiency and Optimization of IPR Management - Mei Rismawati; Dwi Soca Baskara (LPPM Universitas Bhinneka Nusantara, 2026)
Copyright is an essential element of innovation in academic and educational environments. However, the current manual verification and management process of Intellectual Property Rights (IPR) is highly inefficient, particularly in institutions such as Universitas Negeri Malang, which face delays and data duplication due to paper-based workflows. To address this issue, this study aims to develop an Automated Copyright Verification System based on Multi-Agent Artificial Intelligence to enhance efficiency and optimize IPR management. The proposed system, developed using a Prototype Model, leverages an agent-based architecture to model IPR verifiers with distinct functions and objectives. These agents are supported by Vision Language Models (VLM) and Natural Language Processing (NLP). Its key features include ID card data compliance checks and automated text recognition using VLM. The implementation of this system is expected to reduce staff workload, accelerate responses, and ensure data accuracy in IPR management, supporting a sustainable innovation ecosystem.