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p-Index From 2021 - 2026
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This Author published in this journals
All Journal Aptisi Transactions on Management International Transactions on Artificial Intelligence (ITALIC) Advance Sustainable Science, Engineering and Technology (ASSET)
Lina Nurjanah
IPB University
Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science

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Human Centered AI Integrating Ethical Psychological and Computational Perspectives for Inclusive Innovation Lina Nurjanah; Roby Syaiful Ubed; Prabawati Nurhabibah; Marta Rodriguez
APTISI Transactions on Management (ATM) Vol 10 No 1 (2026): ATM (APTISI Transactions on Management: January)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v10i1.2572

Abstract

The rapid evolution of Artificial Intelligence (AI) has reshaped social, economic, and cultural landscapes, yet its development often prioritizes technical efficiency over human values. This study proposes the Human-Centered AI Integration Framework, a multidisciplinary model that unites ethical, psychological, and computational perspectives to promote inclusive and responsible AI innovation. Employing a mixed-method and Design Science Research (DSR) approach, data were gathered from literature studies, user surveys, and AI system analyses to identify gaps between ethical principles, user perception, and algorithmic design. The proposed framework consists of three interrelated layers: the Ethical Layer, emphasizing fairness, accountability, and transparency; the Psychological Layer, focusing on trust, empathy, and human experience; and the Computational Layer, ensuring algorithmic integrity through bias mitigation and explainability. Evaluation results from interdisciplinary experts confirm that the model effectively bridges human values with technical implementation, enhancing trust, inclusivity, and transparency across AI systems. This research contributes to the growing discourse on responsible AI by providing a holistic foundation for designing systems that are not only intelligent and efficient but also empathetic, equitable, and aligned with human well-being.
Design of an Entrepreneurial Competency Development Model to Improve Creative Industry Business Performance Lina Nurjanah; Elisa Anggraeni; Budi Yulianto; Rizal Syarief
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.2247

Abstract

The creative industry contributes significantly to national economic growth through job creation, exports, and cultural preservation. However, its development is constrained by limited entrepreneurial competencies, education, experience, resources, and business networks. This study aims to design an entrepreneurial competency development model to improve business performance in the creative industry. Using a quantitative approach, data were collected from 259 creative industry entrepreneurs and 15 experts and analysed through PLS-SEM and AHP. The results show that knowledge, skills, entrepreneurial orientation, and social capital positively affect business performance (β = 0.583, t = 9.305, p < 0.001). AHP identifies knowledge as the main factor (0.640), government as the key actor (0.531), and strengthening entrepreneurial character and skills as the primary objective (0.634). The main strategy is developing technology-based training curriculum standards and sustainable mentoring programs (0.506) to enhance competitiveness and sustainability in the creative economy. 
Assessing the Environmental and Economic Effects of Smart Grid Integration Using SEM Richard Evans; Fitra Putri Oganda; Mohamad Agus Setiawan; Lina Nurjanah; Meriyana Sunengsih
International Transactions on Artificial Intelligence Vol. 4 No. 1 (2025): November
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v4i1.934

Abstract

The global shift toward renewable energy has intensified the need for intelligent energy management systems capable of addressing variability in power supply and optimizing system-wide performance. Smart grid technologies have emerged as a key enabler in achieving sustainable, efficient, and data-drivenvenergy distribution. This study employs a quantitative approach using Structural Equation Modeling (SEM) via SmartPLS to analyze data collected from stakeholders involved in renewable energy deployment, utility operations, and smart grid implementation. The model evaluates the relationships between smart grid integration, environmental performance, and economic outcomes. The primary aim of this research is to assess how smart grid adoption influences carbon emission reduction, energy efficiency enhancement, and cost optimization within renewable energy ecosystems. The SEM analysis indicates a statistically significant positive effect of smart grid integration on both environmental and economic indicators. Smart grid implementation improves energy efficiency by more than 30%, while operational cost savings reach up to 25% over extended periods. Carbon emission reduction is identified as a key mediating factor within the model, reinforcing the ecological benefits of smart grid adoption. The findings demonstrate that smart grid technologies contribute substantially to both sustainability and economic resilience in renewable energy management. The study provides actionable insights for energy policymakers, grid operators, and industry practitioners, highlighting the vital role of intelligent, data-driven infrastructures in advancing future global energy systems.
Co-Authors Budi Yulianto Elisa Anggraeni Fitra Putri Oganda Marta Rodriguez Meriyana Sunengsih Mohamad Agus Setiawan Prabawati Nurhabibah Richard Evans Rizal Syarief Roby Syaiful Ubed