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All Journal Society: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS
Nurbaya Ambo, Sitti
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Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Social Sciences

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Journal : Society: Jurnal Pengabdian Masyarakat

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Educating on the Application of Tensorflow in Artificial Intelligence, Machine Learning and Deep Learning Santoso, Ilham Budi; Aji, Irfan Pandu; Franskusuma, Sutio; Putri, Khansa Aqila; Ardharani, Yana; Mujiastuti, Rully; Nurbaya Ambo, Sitti; Meilina, Popy; Rosanti, Nurvelly; Amri, Nurul
Society : Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2025): Maret
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/jpm.v4i2.547

Abstract

In addition to bringing positive impacts, technological developments also provide new challenges in improving people's technological literacy, especially related to Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). One of the main challenges is the low public understanding of these technologies, which are increasingly relevant in the era of digital transformation. On the other hand, Google developed a library with the name TensorFlow which is widely used for data processing in Artificial Intelligence, Machine Learning, and Deep Learning. Based on this, educational activities were carried out in the form of introducing and training the use of TensorFlow to the general public in the form of webinars and workshops with the theme ‘Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning’. The activity was carried out in two stages, namely webinars for delivering basic material and workshops for hands-on practice. Based on evaluation through a Likert scale questionnaire, the majority of participants stated that they were very satisfied with the quality of the material, presenters, and implementation of activities. The post-test results also showed an increase in participants' understanding of the material, as evidenced by correct answers on topics such as TensorFlow functions, supervised learning, and neural networks. The participation of 52 participants from various institutions shows the success of this activity in achieving its goals.  
Chatbots Made Easy: A Practical Workshop on Generative AI Aullia, Mochammad Rizqi; Fadillah, Muhammad Daffa; Umam, Khoirul; Septiana, Dimas; Rahmawati Gunawan, Alfiana; Nurbaya Ambo, Sitti; Rosanti, Nurvelly; Ardhani, Yana; Jumail, Jumail
Society : Jurnal Pengabdian Masyarakat Vol. 4 No. 3 (2025): Mei
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/jpm.v4i3.548

Abstract

Chatbots powered by Generative AI have become a rapidly evolving technological innovation, enabling users to interact with AI-based systems in a more natural way. However, the implementation of these chatbots still faces many challenges, especially for beginners who lack a deep technical background. This study aims to develop a more accessible and understandable approach for those new to Generative AI. Through webinars and workshops, participants were introduced to the fundamentals of language models, the use of tools such as Google Colab, as well as various challenges and opportunities in AI chatbot development. Some of the main obstacles encountered included complex materials, limited access to data and computational resources, and varying levels of understanding among participants. Nevertheless, these activities provided beginners with the opportunity to grasp the basics of Generative AI and even develop their own chatbots. With a more practical and inclusive approach, this study contributes to introducing Generative AI-based chatbot technology to a broader audience. Evaluation results showed positive feedback from 77 participants from diverse backgrounds, with 51.9% stating they were very satisfied, 37.7% satisfied, and 10.4% neutral. Additionally, Pre-Test and Post-Test results indicated an improvement in participants' understanding of building simple chatbots. This initiative successfully provided a strong foundation for beginners to enter the field of Artificial Intelligence, particularly Generative AI
Co-Authors Abyan Shidqi, Muhammad Adharani, Yana Afkarinah, Afni Izzah Aji, Irfan Pandu Akhdan, Nabil Alghifari, Abdul Hafizd Alifsyah Ramadhan, Rafi Novranza Amanullah, Muhammad Faiz Amili, Fadel Amri, Nurul Anjani, Meisya Putri Apriliano, Yova Rezky Ardhani, Yana Ardharani, Yana Arista Putri, Syahda Aullia, Mochammad Rizqi Cholis Arethusa, Muhammad Dwi Duta Mahardewantoro Dzakiyuddin Rohman, Hilmi Fachrudin, Tedy Fadhlurokhman, Rafi Fadillah, Muhammad Daffa Fauzan Azima Franskusuma, Sutio Gimnastiar, Nazar Ginawan, Najla Maharani Dewi Tiawa Guritno, Deden Habibie, Muhammad Fadhil Hasan, Nur Fatima Haykal Andana, Muhammad Hendra Hendra Ihsan, Awang Ikhsan Adi Prayogo Ikhsan Fitriansyah Ilyasa, Fahri Jumail, Jumail Khoirrosyid, Haida Khoirul Umam Maulana, Fikri Naufal Maulana, Mirza Memanda, Freddy Muhammad Adri Farqan Muhammad Arif muhammad rizky, muhammad Muhammad Zikri Nurvelly Rosanti Nurvelly Rosanti, Nurvelly Pebriano Nurba, Putra Poppy Meilina Popy Meilina Prasetio, Iqlal Wira Priadi, Aryaguna Fadlurrahman Putri, Khansa Aqila Qaedi Setiawan, Muhammad Thirafi Qardhawi, Nadif Yusuf Rahmawati Gunawan, Alfiana Rifqi Baihaqi Sabhan Risanty, Rita Dewi Rosanty, Nurvelly Rozy, Farhan Rully Mujiastuti Santoso, Ilham Budi Saputra, Audyka Saputri, Octaviani Septiana, Dimas Sulthan, Athilla Sutrisno, Mirza Syuja Ardyansyach Taufik Hidayat Zahran, Fikry Muhammad