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All Journal Aptisi Transactions on Management International Transactions on Artificial Intelligence (ITALIC)
Ferdiansyah, Januri
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Library & Information Science

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Integrating Artificial Intelligence for Autonomous Navigation in Robotics Costa, Pedro; Ferdiansyah, Januri; Ariessanti, Hani Dewi
International Transactions on Artificial Intelligence Vol. 3 No. 1 (2024): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v3i1.657

Abstract

This research examines the integration of Artificial Intelligence (AI) in enhancing autonomous navigation systems within robotics, focusing on developing adaptive machine learning algorithms for high-dimensional data processing. The primary objective is to advance AI-based navigation systems that outperform traditional methods in terms of accuracy, obstacle avoidance, and efficiency. By leveraging deep learning for intricate visual perception and reinforcement learning for agile decision-making and path optimization, the study achieves a substantial increase in navigation precision and obstacle detection in both simulated and real-world settings. The findings reveal that these AI-driven systems surpass conventional rule-based systems and exhibit superior adaptability in dynamic and unstructured environments. Future efforts will concentrate on refining these algorithms to enhance environmental recognition and extend AI applications to more complex robotic operations. This research supports Sustainable Development Goals (SDGs) by promoting innovative infrastructure (SDG 9) and fostering industry innovation and infrastructure development, which are vital for sustainable economic growth and environmental protection.
Leveraging Artificial Intelligence for Competitive Advantage in SMEs An Empirical Analysiss Ferdiansyah, Januri; Abudaqa, Anas; Lansonia, April
APTISI Transactions on Management (ATM) Vol 9 No 2 (2025): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v9i2.2472

Abstract

Small and Medium Enterprises (SMEs) face significant challenges in a com- petitive market. Artificial Intelligence (AI) has emerged as a critical tool for enhancing business operations, yet the specific impact of AI on the competi- tive advantage of SMEs remains underexplored. This study aims to investigate how AI adoption influences the competitive advantage of SMEs, focusing on key performance indicators such as cost efficiency, market share, customer retention, and innovation. The study adopts a quantitative research approach using Par- tial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS software. Data was collected from 200 SMEs across various industries that have implemented AI technologies. A survey was conducted to assess AI adoption and its impact on competitive advantage. The results indicate that AI adoption positively affects all four dimensions of competitive advantage. The strongest impact was observed on cost efficiency, followed by customer retention, inno- vation, and market share. The relationships between AI adoption and competi- tive advantage were statistically significant. AI adoption provides SMEs with a powerful means to enhance competitiveness by improving operational effi- ciency, customer loyalty, and innovation. Policymakers should support SMEs in overcoming adoption barriers to fully realize these benefits.
Co-Authors Abudaqa, Anas Costa, Pedro Hani Dewi Ariessanti Lansonia, April