Moh Hasbi Assidiqi

Moh. Hasbi Assidiqi

PhD Candidate, Computer Information Systems
Faculty of Computing and Information Technology
King Abdulaziz University, Jeddah, Saudi Arabia

Assistant Professor / Lektor (on study leave)
Diploma of Multimedia Broadcasting Technology
Department of Creative Multimedia Technology
Electronic Engineering Polytechnic Institute of Surabaya

About Me

I’m a computer engineer that became passionate about web development and information system. I love to learn new things and share my knowledge with others.

In pursue of my passion, I’ve participating in many programming challenges including TopCoder. I’ve participating in various tech stack, including angular, react, and recently SolidJS. Open source fills my love of programming. Lots of great source code examples in the open source community that I can learn from.

I also love to program everything that I can which is now becoming a field called Robotic Process Automation. I’m also a tech enthusiast and love to learn about new technologies, including Kafka, Redis, and Grafana. I love software development from planning to deployment, and I’m also a big fan of DevOps. I’m also a big fan of transparent progress as encouraged by Agile and Scrum.

Currently, I’m studying at King Abdulaziz University in Saudi Arabia. I’m a PhD candidate in Computer Information Systems at the Faculty of Computing and Information Technology.

Basically, I’m a tech enthusiast, programming lover, and competitive programmer passionate about building scalable solutions and teaching others. Let’s learn and code together!

Publications

Proceedings papers

  1. M. L. Hidayat, I. Ahmad, M. H. Assidiqi, T. J. S. Khanzada, and M. Meccawy, “Knowledge Discovery and Scientometric Analysis of Conversational Artificial Intelligence (CAI) for Mental Health,” 2025 International Conference on Innovation in Artificial Intelligence and Internet of Things (AIIT), pp. 1–15, May 2025, doi: 10.1109/aiit63112.2025.11082869. [View]
  2. R. Faradisa, Y. M. Akbar, Y. Setiowati, T. Badriyah, and M. H. Assidiqi, “Enhancing Medical Expenditure Prediction Using Machine Learning on Claims Data for Better Healthcare Cost Management,” Proceedings of the International Conference on Applied Science and Technology on Social Science 2025 (iCAST-SS 2025), pp. 473–481, 2025, doi: 10.2991/978-94-6463-938-4_54. [View]
  3. G. R. Putra, H. Rante and M. H. Assidiqi, "Animated Video Using Duik Bassel Rigging Toolset on Tuberculosis Education," 2021 International Electronics Symposium (IES), Surabaya, Indonesia, 2021, pp. 349-355, doi: 10.1109/IES53407.2021.9594031. [View]

Journal papers

  1. M. H. Assidiqi, D. Alghazzawi, S. Alarifi, and L. Cheng, “Conversational Enterprise Management Through Agentic AI: A Five-Pillar Framework for LLM-Driven ERP Systems,” Applied Artificial Intelligence, vol. 40, no. 1, Jul. 2026, doi: 10.1080/08839514.2026.2700868. [View]
  2. M. H. Assidiqi, D. Alghazzawi, S. Alarifi, and L. Cheng, “Knowing when to escalate: Prompt-based uncertainty quantification for selective automation of LLM-based intrusion detection,” Array, vol. 31, p. 101127, Sep. 2026, doi: 10.1016/j.array.2026.101127. [View]
  3. M. H. Assidiqi, D. Alghazzawi, S. Alarifi, and L. Cheng, “Benchmarking Reference-Free LLM Agent Robustness Under Schema, Policy, and Toolset Drift,” IEEE Access, vol. 14, pp. 79662–79672, 2026, doi: 10.1109/access.2026.3696096. [View]