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All Journal Jurnal Teknologi Informasi dan Pendidikan Frontier Management Science (FMS)
Safitri, Yulita Dwi
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Social Sciences

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Prioritizing Success Factors for Start-ups in Indonesia Using the Best Worst Method (BWM): A Decision-Making Approach Safitri, Yulita Dwi; Pebriana, Rina; Suasri, Eni
Frontier Management Science Vol. 1 No. 2 (2024): FMS - April
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/fms.v1i2.326

Abstract

The rapid growth of Indonesia’s start-up ecosystem presents both opportunities and challenges for new ventures striving for sustainability and competitiveness. This study applies the Best Worst Method (BWM) to prioritize key success factors for start-ups in Indonesia, providing a structured framework for decision-making. Six critical factors were evaluated: access to funding, innovation capability, market competition, regulatory environment, talent acquisition, and scalability potential. Through pairwise comparisons, this research identifies access to funding as the most critical factor, while scalability potential is considered the least influential in determining start-up success. The findings offer valuable insights for entrepreneurs, investors, and policy-makers, highlighting areas where targeted support can enhance the growth and sustainability of start-ups. This study contributes to the ongoing discourse on start-up development in emerging economies by providing a decision-making tool to guide strategic priorities within Indonesia’s dynamic entrepreneurial landscape.
Enhancing Business Communication Skills in Vocational Education: A Generative Ai Approach for Personalized Learning Wijayati, Titik; Hayati, Marliza Noor; Safitri, Yulita Dwi
Frontier Management Science Vol. 1 No. 2 (2024): FMS - April
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/fms.v1i2.270

Abstract

In the realm of higher education, there is an increasing emphasis on holistic education approaches that extend beyond academic achievements to encompass various dimensions of student well-being, including social, ethical, spiritual, civic, intellectual, and physical health. This paper explores the growing intersection between student mental health and generative artificial intelligence (AI), examining the potential of AI to enhance holistic education by providing personalized mental health support. The study highlights the eco-holistic model's advocacy for a "whole school" approach, which integrates mental, physical, social, emotional, and environmental aspects to improve student well-being. Additionally, the paper discusses the role of generative AI in addressing student mental health issues, offering innovative solutions such as AI-powered chatbots for real-time support, virtual therapy sessions, and the early identification of at-risk students. Ethical considerations, including privacy, data security, and the need for ongoing research, are also examined. The findings underscore the potential of AI to transform mental health support in higher education, making it more accessible and personalized, thus contributing to the overall well-being and success of students.
Leveraging Artificial Intelligence and Technology for Enhancing Halal Supply Chain Management Ghalih, Muhammad; Chang, Chia Hua; Safitri, Yulita Dwi
Jurnal Teknologi Informasi dan Pendidikan Vol. 18 No. 1 (2025): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v18i1.955

Abstract

Halal Supply Chain Management (HSCM) is transforming the way halal products are certified, tracked, and distributed. However, challenges such as regulatory compliance, technological readiness, cost, and stakeholder trust continue to impact AI adoption in the halal industry. This study employs the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to analyze the causal relationships among key factors influencing AI adoption in halal supply chains. Seven key criteria were identified: Technological Infrastructure, Regulatory Compliance, Cost of Implementation, Data Security & Privacy, Scalability & Adaptability, Stakeholder Readiness, and Consumer Trust & Perception. The findings reveal that Technological Infrastructure is the most influential factor driving AI adoption, impacting Regulatory Compliance, Scalability, and Consumer Trust. Conversely, Consumer Trust & Perception emerged as the most dependent factor, highlighting the importance of transparency in AI-based halal certification. Regulatory Compliance plays a dual role as both a cause and an effect, emphasizing the need for standardized AI-driven halal certification frameworks. The results suggest that investment in AI-driven traceability, blockchain-based halal authentication, and automated compliance verification can significantly improve halal supply chain efficiency and consumer confidence. This study provides valuable insights for policymakers, halal certification bodies, and industry stakeholders by identifying key enablers and barriers to AI adoption. Future research should explore hybrid Multi-Criteria Decision-Making (MCDM) approaches, economic feasibility analyses, and real-world case studies to further validate AI-driven solutions in halal supply chains.
Co-Authors Chang, Chia Hua Eni Suasri Ghalih, Muhammad Hayati, Marliza Noor Rina Pebriana, Rina Wijayati, Titik