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All Journal Journal TEPAT: Teknologi Terapan untuk Pengabdian Masyarakat International Journal of Advances in Data and Information Systems
Sakka, Asriadi
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Public Health

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Welding Skills Improvement Training in Lanne Village, Pangkep Regency Amme, Rudi; Salam, Nasaruddin; Renreng, Ilyas; Tarakka, Rustan; Arma, Lukmanul Hakim; Arsyad, Hairul; Mochtar, Andi Amijoyo; Hayat, Azwar; Sakka, Asriadi
JURNAL TEPAT : Teknologi Terapan untuk Pengabdian Masyarakat Vol 8 No 1 (2025): Community Empowerment through Higher Education Community Service Programs
Publisher : Faculty of Engineering UNHAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25042/jurnal_tepat.v8i1.577

Abstract

The welding method combines two or more pieces of metal by melting the material to be joined. The joining of two or more base metals through melting or without melting the joint area is known as welding technology. Karang Taruna Desa Lanne is a village government program for youth empowerment. Currently, the youth organization has a program that still needs to be improved to increase the productivity of youth organization members. Therefore, the training program to improve welding skills initiated by the Department of Mechanical Engineering, Faculty of Engineering, Hasanuddin University, is expected to positively impact partners. The activity was carried out by providing training material followed by welding practice activities to determine the ability of participants to apply the material provided previously. In addition, the pre-test and post-test questionnaires were given to the participants before and after the training to determine the program's success rate. Based on the quantitative analysis of measurements before training, it was found that 85% did not understand and 15% did not understand how to prepare for welding. After the training, it was found that 65% of the participants understood, 25% understood, and 10% understood very well when preparing for welding. This indicates that the activities carried out have a positive impact on partners.
Automated Oil Palm Health Assessment Using Object-Based Deep Learning and High-Resolution UAV Imagery in Indonesia Pindarwati, Atut; Wijayanto, Arie Wahyu; Karmawan, I Putu Agus; Yeza, Ardhan; Sakka, Asriadi
International Journal of Advances in Data and Information Systems Vol. 6 No. 3 (2025): December 2025 - International Journal of Advances in Data and Information Syste
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i3.1391

Abstract

Indonesia, as the world’s largest crude palm oil (CPO) producer, faces challenges in plantation monitoring due to reliance on manual data collection methods that are time-consuming, costly, and prone to human error. This study proposes an automated approach for assessing oil palm tree health using high-resolution UAV imagery (5–10 cm) and object-based deep learning models. We evaluate five state-of-the-art detectors—YOLOv5s, Faster R-CNN, Mask R-CNN, SSD, and RetinaNet—to classify individual trees into four health categories: Healthy, Moderately Healthy, Needs Improvement, and Urgent Condition. Using a dataset of 14,749 labeled trees from Kendawangan, Indonesia, YOLOv5s achieved the highest performance with a precision of 0.784, recall of 0.752, and mAP of 0.764. Our findings demonstrate the potential of AI-driven monitoring to enhance plantation management through rapid, accurate, and cost-effective health assessments—contributing a scalable solution to support precision agriculture and sustainable CPO production.
Co-Authors Amme, Rudi Hairul Arsyad Hayat, Azwar Ilyas Renreng Karmawan, I Putu Agus Lukmanul Hakim Arma Mochtar, Andi Amijoyo Nasaruddin Salam, Nasaruddin Pindarwati, Atut Rustan Tarakka Yeza, Ardhan