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All Journal International Journal of Community Service Learning Journal of Robotics, Automation, and Electronics Engineering Journal of Vocational Applied Research and Studies
Ahmad Taufiq Musaddid
Universitas Negeri Yogyakarta
Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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Teacher Competence in the Use of ChatGPT for Developing Learning Media in Vocational High Schools Tri Aji, Purno; Aris Nasuha; Dessy Irmawati; Moh Alif Hidayat Sofyan; Ahmad Taufiq Musaddid
International Journal of Community Service Learning Vol. 8 No. 4 (2024): November
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/ijcsl.v8i4.85397

Abstract

ChatGPT technology opens up great education opportunities, especially in supporting the development of educator competencies needed in the 21st century. However, teacher competency in utilizing Artificial Intelligence (AI) technology is still low. As a result, existing learning media are not optimal in presenting engaging and interactive digital teaching materials according to the needs of students in the era of education 4.0. This community service aims to improve the competence of vocational high school teachers in using ChatGPT and AI applications for the development of learning media. This study involved 60 teachers from various fields. The methods used were lectures, discussions, and direct practice with online assistance. Teachers were trained to create interactive teaching materials using ChatGPT and other AI applications. The data analysis technique used qualitative descriptive analysis. The post-test results showed a significant increase in teacher competency in using AI applications, with an average score above 4 out of 5 in key aspects such as material usefulness and skill development. The activity results showed increased teachers' ability to utilize AI technology to create digital-based learning media, such as learning videos and interactive teaching materials. This activity significantly improves the quality of the learning process in vocational high schools. This training is expected to optimize teachers' digital skills to face challenges in the era of education 4.0.
Adaptive Bounding Box Coordinate Adjustment on License Plate Character Detection Using Machine Learning Ahmad Taufiq Musaddid
Journal of Robotics, Automation, and Electronics Engineering Vol. 2 No. 1 (2024): March 2024
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jraee.v2i1.553

Abstract

Effective law enforcement, including the use of the ANPR (Automatic Number Plate Recognition) system, is essential for reducing the number of road traffic accidents. ANPR involves plate localization, character segmentation, and recognition to build a minimum system. This study aims to improve a character segmentation method using a detection approach to address issues like noisy or modified plates. We propose an adaptive improvement on an established sliding window technique, by integrating a CNN (Convolutional Neural Network) for bounding box coordinate adjustment to handle various plate conditions. The proposed method was tested on 280 license plate images and improved the average IoU (Intersection over Union) from 0.4811 to 0.8980. Hence, the recall and precision of the model could be improved to increase any character recognition performance.
DEVELOPMENT OF TEACHING FACTORY MODEL IN VOCATIONAL HIGHER EDUCATION Purno Tri Aji; Aris Nasuha; Dessy Irmawati; Ahmad Taufiq Musaddid; Moh Alif Hidayat Sofyan; Septian Rahman Hakim
Journal of Vocational Applied Research and Studies Vol. 2 No. 1 (2025)
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jvars.v2i1.1452

Abstract

The increasing demand for skilled workers in the industry encourages vocational higher education institutions to align their curricula with real-world practices. One way to bridge the gap between academic learning and industry needs is through the implementation of the Teaching Factory (TEFA) model. This study presents the development of a comprehensive Teaching Factory model within vocational higher education. The research employed primary data collection methods, including Focus Group Discussions (FGD) and interviews, to explore the insights and experiences of stakeholders involved in the development of TEFA. The results provide a framework for integrating industry requirements and academic competencies to enhance the competitiveness of graduates from vocational education institutions.
CONTRIBUTION OF AI IN IMPROVING FOOD SECURITY: A LITERATURE STUDY Dessy Irmawati; Aris Nasuha; Ahmad Taufiq Musaddid; Purno Tri Aji; Moh Alif Hidayat Sofyan; Septian Rahman Hakim
Journal of Vocational Applied Research and Studies Vol. 2 No. 1 (2025)
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jvars.v2i1.1473

Abstract

Global food security is a major challenge due to population growth, climate change and limited natural resources. Artificial intelligence (AI) technologies offer innovative solutions to address these issues by improving efficiency and productivity in the agricultural sector. This article reviews the contribution of AI in supporting food security through applications such as yield prediction, crop health monitoring, water management, and food waste reduction. Several studies demonstrate the use of AI in precision agriculture, which optimizes resource use through real-time data analysis from IoT sensors, satellite imagery, and drones. Innovations such as AI-based automated irrigation systems and smart farming apps help farmers manage water use more efficiently, especially in areas at risk of drought. In addition, the application of AI in vertical farming enables precise environmental control, increasing productivity in urban areas with limited land. The study also highlights the role of AI in reducing reliance on chemical pesticides through early detection systems that enable timely intervention. Despite the potential, the adoption of AI technology in agriculture still faces challenges such as initial investment costs and training needs for farmers. Collaboration between the government, private sector, and research institutions is essential to ensure effective and sustainable implementation of AI in agriculture, so that global food security can be achieved
Co-Authors Aris Nasuha Dessy Irmawati Moh Alif Hidayat Sofyan Purno Tri Aji Septian Rahman Hakim