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All Journal Prosiding Semnastek Journal of Electrical Technology UMY Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Multitek Indonesia : Jurnal Ilmiah Jurnal Pengabdian Masyarakat Teknik Journal of Intelligent Computing and Health Informatics (JICHI) Society: Jurnal Pengabdian Masyarakat
Jumail, Jumail
Department Of Informatics Engineering, Universitas Muhammadiyah Jakarta
Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Public Health Social Sciences

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From Zero to AI: Educational Initiatives Through Webinars and Workshops on Developing Machine Learning Models Using TensorFlow Hafizh Umar Haq; Mirza Sutrisno; Popy Meilina; Yana Adharani; Nurvelly Rosanti; Jumail; Kevin Arya Dandy; Muhammad Imam Najib; Anggi Rahmadillah; Miftahul Jannah; Rully Mujiastuti
Society : Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2026): Maret
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/3qq71h51

Abstract

The development of Artificial Intelligence (AI) and Machine Learning (ML) requires improved technological literacy and a basic understanding of practical applications. This study aims to introduce the concepts of AI and ML through the implementation of simple machine learning models using TensorFlow. The methods used include material delivery, model implementation practice, and evaluation through pre-tests, post-tests, and feedback questionnaires. The evaluation results show an increase in participants' understanding, marked by an increase in the average score from 76.76 on the pre-test to 80.91 on the post-test, or an increase of 5.41%. In addition, the feedback results showed a very high level of satisfaction, with 96% of participants giving positive ratings. This shows that the TensorFlow-based learning approach is effective in improving basic understanding and skills related to AI and ML.
Co-Authors Adharani, Yana Andri Kuspurnama Anggi Rahmadillah Eka Budhy Prasetya Eka Budhy Prasetya Hafizh Umar Haq Haris Isyanto Irfan Purnawan Purnawan Kevin Arya Dandy Miftahul Jannah Mirza Sutrisno Muhaemin Muhaemin Muhammad Imam Najib Muhammad Kheamal Nofian Firmansyah Nurvelly Rosanti, Nurvelly Popy Meilina Rahayu Rahayu Retnani Latifah Rudiatin, Endang Rully Mujiastuti Sitti Nurbaya Ambo