Pelatihan Koding Kecerdasan Artifisial untuk Peningkatan Kompetensi Guru - Yusuf Ramadhan; Reza Ade Putra; Ilka Zufria; M. Fakhriza; Puji Sari Ramadhan; Rita Novita Sari; Lailan Sofinah Harahap; Suhardi Suhardi; Oktopanda Oktopanda (Al-Khidmah Jurnal Pengabdian Masyarakat, 2026)
The development of artificial intelligence (AI) in education requires teachers to possess digital literacy and adapt to learning technology. However, there is still a competency gap among teachers in understanding basic AI and coding concepts, particularly in educational institutions that have not yet optimally utilized digital technology. Therefore, this community service activity was carried out with the aim of improving teachers' understanding and basic skills in artificial intelligence coding as a support for innovative learning. The community service method used was participatory and applied, implemented through preparation, implementation, and evaluation stages. The training activity involved 50 teachers and was conducted in the form of interactive lectures, discussions, and simple practical exercises related to coding and the use of AI in learning. Throughout the activity, a process evaluation was conducted through observation of participant participation, active participation in discussions, ability to participate in coding exercises, and completion of assigned tasks. This evaluation aimed to ensure that participants understood the material and actively participated in the training. Indicators of success at this stage were demonstrated by a minimum of 85% of participants completing the activity to completion and a minimum of 80% of participants completing the basic coding exercises and using the AI ​​tools provided during the training. After all the material was delivered, a final evaluation was conducted through a post-test, simple AI-based project assignments, and participant satisfaction questionnaires. The final evaluation was used to measure teacher competency improvement after participating in the training. The success of the program was demonstrated by an average post-test score increase of at least 30% compared to the pre-test results. In addition, at least 75% of participants were able to create simple AI-based projects or code according to the training material, and at least 80% of participants were able to integrate the use of AI technology into their learning designs. These findings confirm that artificial intelligence coding training is a strategic step in improving teacher competency and supporting technology-based learning transformation in educational environments.