Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal Engineering Science Letter Journal of Educational Technology Innovation and Applications
Franklin Ore Areche
National University of Huancavelica
Computer Science & IT Control & Systems Engineering Education Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Social Sciences Other

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Service Desk in Perspective of Information Technology Infrastructure Library 3rd-Version Dimas Mahardika; Tawar; Saima Ahmed Rahin; Franklin Ore Areche; Ari Fajar Santoso; Ahmad Suryan
Engineering Science Letter Vol. 1 No. 02 (2022): Engineering Science Letter
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (736.746 KB) | DOI: 10.56741/esl.v1i02.142

Abstract

ICT services are an essential element in modern organizations. Understanding the workings of service systems with specific frameworks helps manage services well. One of the services in this management is the Service Desk or Helpdesk. This study aims to explain the Service Desk using the ITIL V.3 framework. The method used is descriptive qualitative using relevant references. The results of this study indicate that ITIL V.3 can be used to describe the management of the Service Desk accurately.
Scoping Review of AI-Enabled Predictive Analytics and Decision Support in Agricultural Education: Current Trends, Tools, and Pedagogical Implications Daniela Laura; Nancy V. Quispe Cordova; Franklin Ore Areche
Journal of Educational Technology Innovation and Applications Vol. 2 No. 01 (2026): Journal of Educational Technology Innovation and Applications
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.jetia.001994

Abstract

Artificial Intelligence (AI) and predictive analytics are increasingly reshaping contemporary agricultural systems by enabling data-driven decision support, early pest and disease detection, and optimized crop management. As these technologies become embedded in agricultural practice, agricultural education faces growing pressure to prepare learners with analytical reasoning and decision-making competencies aligned with AI-enabled environments. This scoping review maps peer-reviewed literature published between 2020 and 2025 on AI-enabled predictive analytics, crop advisory systems, and pest and disease detection technologies, with a specific focus on their educational implications. Following PRISMA-ScR guidelines, 18 studies were systematically identified and synthesized through thematic analysis. The results indicate rapid growth in technically oriented AI applications for precision agriculture, contrasted with limited empirical research on curriculum integration and competency-based learning outcomes. While project-based learning, simulations, and decision support tools are frequently proposed as pedagogical strategies, explicit assessment of learners’ analytical and decision-making competencies remains scarce. This review highlights critical gaps between AI innovation and educational research, and underscores the need for interdisciplinary approaches, curriculum redesign, and competency frameworks that support responsible and effective AI use in agricultural education.
Co-Authors Ahmad Suryan Ari Fajar Santoso Daniela Laura Dimas Mahardika Nancy V. Quispe Cordova Saima Ahmed Rahin Tawar