Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Journal of Novel Engineering Science and Technology Bincang Sains dan Teknologi Journal of Organizational and Human Resource Development Strategies
Areche, Franklin Ore
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Mechanical Engineering Transportation

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Latest Trends in Visual Manipulation and Navigation in Robotics Miftahul Amri, Muhammad; Areche, Franklin Ore; Ratnakar Naik, Amar
Journal of Novel Engineering Science and Technology Vol. 2 No. 01 (2023): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v2i01.253

Abstract

In recent decades, the term Robot has become more and more popular. A robot can be defined as a machine that is specifically built to complete certain tasks to help human-being. In order to successfully accomplish its task, the robot needs to receive input data and process it. Then, the processed data is used for manipulator-actions decision-making. The input data can vary from sound, temperature, vibration, touch, vision, etc. Among those input data, vision is arguably one of the most challenging data. This is because vision often needs detailed and complicated preprocessing before it can be used. In addition, vision data size is relatively larger compared to the other type of input data, making it more challenging to process considering the computational resources. In this paper, current research and future development trend of robotic vision were reviewed and discussed. Further, challenges and potential issues about robot vision, such as safety and privacy concerns, were also discussed.
Artificial Intelligence and Organizational Culture: Navigating Contextual Shifts in Structure, Ethics, and Behavior Areche, Franklin Ore; Ofluoglu, Gokhan
Journal of Organizational and Human Resource Development Strategies Vol. 2 No. 02 (2025): Journal of Organizational and Human Resource Development Strategies
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/ohds.v2i02.1062

Abstract

This article explores the transformative impact of Artificial Intelligence (AI) on organizational culture. With the increasing integration of AI technologies into business operations, organizational dynamics, decision-making structures, and cultural norms are experiencing significant shifts. This qualitative-descriptive study reviews the literature and synthesizes empirical and theoretical perspectives on how AI reshapes organizational culture, focusing on decentralization, transparency, digitalization, and employee-manager relations. The article also highlights the role of deep learning and artificial neural networks as key technological drivers of this cultural evolution. The results underline the need for adaptive organizational models that integrate AI ethically and strategically.
From Data Assets to Value Creation: Competitive Advantage in the AI Age Areche, Franklin Ore; Cansaya, Silvia Hypatia Sarabia; Laura, Daniela
Bincang Sains dan Teknologi Vol. 4 No. 03 (2025): Bincang Sains dan Teknologi
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/bst.v4i03.1890

Abstract

The rapid advancement of Artificial Intelligence (AI) has fundamentally transformed how organizations create and sustain competitive advantage. In contemporary business environments, data is no longer treated merely as a supporting asset but has emerged as a primary source of value creation. This article examines how data-driven approaches, enabled by AI technologies, generate competitive advantage through enhanced decision-making, personalization, and operational efficiency. Using a conceptual research method, this study synthesizes findings from international peer-reviewed journals to analyze the mechanisms through which data becomes economic value. The Results and Discussion section elaborates on three core dimensions: the transformation of data into value generators, the economic characteristics of data in AI-driven markets, and the strategic logic of value creation through data–algorithm–context alignment. The findings indicate that data-driven competitive advantage is contingent not only on data volume but also on data quality, governance, and organizational capability. This article contributes to the growing body of literature on AI-enabled strategy by offering an integrated framework for understanding data as a strategic source of competitive advantage.
Co-Authors Cansaya, Silvia Hypatia Sarabia Laura, Daniela Miftahul Amri, Muhammad Ofluoglu, Gokhan Ratnakar Naik, Amar