ICE-045 Artificial Intelegence in Education Peer-Reviewed

Evidence-Based Model Selection in Machine Learning: A Junction-Level Traffic Case Study for AI and Data Science Education

Rachmad Kurniawan • Mohammad Zubair • Syahrun Fathan Hidayah ^✉* • Andi Hendra ^✉* • amar • Andi Rusdin • Mohammad Yazdi

Universitas Tadulako

✉* Corresponding Author(s): Syahrun Fathan Hidayah (syahrunfathanhidayah@untad.ac.id), Andi Hendra (andi.hendra@eng.untad.ac.id)

DOI / Persistent URI: https://doi.org/10.31219/ice.2026.ice-045

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Current Manuscript Status: 2. Abstract Accepted (Needs Full Paper) 10 November 2026, 08:05

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"Background & Problem: Applied case studies are widely used to teach machine learning, yet learners often adopt complex ensemble models by default without evidence that the added co..."

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Keywords:

stacking ensemble model selection traffic prediction artificial intelligence in education data science education

How to Cite (APA 7th Edition)

APA 7th Edition

Rachmad Kurniawan. (2026). Evidence-Based Model Selection in Machine Learning: A Junction-Level Traffic Case Study for AI and Data Science Education. Proceedings of the International Conference on Education (ICE 2026), Vol. 4, No. 1, pp. 1-10. https://doi.org/10.31219/ice.2026.ice-045

This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0).

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ICE-045

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Publication Metadata

Issue: Vol. 4 No. 1 (2026)
Conference Tracks & Scope: Artificial Intelegence in Education
Date Received: 20 Oct 2026
Date Published: 10 Nov 2026
Workflow Stage: Abstract Accepted (Needs Full Paper)

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