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All Journal International Journal of Economics Development Research (IJEDR) Jurnal Ilmu Komputer dan Teknologi Informasi
Teguh Pradana
Institut Teknologi dan Bisnis Yadika Pasuruan
Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Integration of Artificial Intelligence In Management Talent For Improving Company Performance: Mediation Employee Engagement Arif Syaifudin; Teguh Pradana; Muhammad Fatkhur Rozi
International Journal of Economics Development Research (IJEDR) Vol. 5 No. 2 (2024): International Journal of Economics Development Research (IJEDR)
Publisher : Yayasan Riset dan Pengembangan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/ijedr.v5i4.6460

Abstract

 Revolution Industry be one of part most important in activities in the company . The number of tasks that are routine done a individual so that matter the can give impact inability a individual do task the because of reach limit maximum physique a human. Intelligence artificial intelligence (AI) provides A offer related with potential transformational For improvement as well as give offer For replace task man in field intellectual , social and also industry In researcher data collection involving 94 leaders company food and beverages in the district area Pasuruan with using primary data. Maintaining talented employees , Support? Culture Organization , Reducing Workload? Employee own influence direct and significant to Company performance , good in a way direct and also through Engagement mediator Employees . Next Engagement Mediator Employee play a role as connector between variable independent and dependent , which indicates that There is influence partial .
Analisis Ancaman Social Engineering Berbasis Agentic AI dan Strategi Mitigasi Menggunakan Pendekatan Zero Trust Teguh Pradana; Nur Amalia Hasma; Handry Eldo; Renita Selviana; Ayuliana Ayuliana
Jurnal Ilmu Komputer dan Teknologi Informasi Vol. 3 No. 2 (2026): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jikti.v3i2.2057

Abstract

The development of Agentic Artificial Intelligence (Agentic AI) presents new challenges in cybersecurity due to its ability to plan, adapt, and act autonomously. This study aims to analyze the threat of social engineering based on Agentic AI and to formulate mitigation strategies using the Zero Trust approach. The research method employs literature review and threat modeling to identify attack vectors, user vulnerabilities, and potential impacts. The analysis shows that Agentic AI can enhance the personalization, scale, speed, and effectiveness of social engineering attacks. This study develops a conceptual framework for mitigating social engineering attacks based on Agentic AI by applying Zero Trust principles as a layered defense approach that places identity, context, and risk at the center of security decision-making.
Co-Authors Arif Syaifudin Ayuliana Ayuliana Handry Eldo Muhammad Fatkhur Rozi Nur Amalia Hasma Renita Selviana