Enhancing University Students’ Image Processing Skills through Hybrid Google Colab Training on Image Histogram Analysis
DOI:
https://doi.org/10.62712/juribmas.v5i2.1721Keywords:
Google Colab, Hybrid Training, Image Histogram, Image Processing, PythonAbstract
University students generally understand basic digital image concepts but rarely practise image processing computationally. This community service activity aimed to improve students’ image processing skills through hybrid training based on Google Colab and Python, focusing on image histogram analysis. The training was held on 26 September 2026 in a computer laboratory and involved 20 students of Information Technology Program (8 on-site, 12 online). The activity comprised needs identification, demonstration, hands-on practice with a shared Colab notebook, histogram analysis, evaluation, and follow-up. Outcomes were measured using a pre-test and post-test, a practical task rubric, and a response questionnaire. The mean score increased from 85 to 95 (10 points; 11.8%). Eighteen of 20 participants (90%) completed the histogram analysis task according to the rubric, comprising all on-site participants and 10 of 12 online participants. The questionnaire score reached 94%. Unstable internet connection was the main constraint and was mitigated through mobile tethering.
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Copyright (c) 2026 Supiyandi Supiyandi, Rahmi Hayati, Febriyansyah Ramadhan, Husni Mubarak, Nuranisah Nuranisah
This work is licensed under a Creative Commons Attribution 4.0 International License.
