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Pengembangan Keterampilan Siswa Melalui Pelatihan Robotik Untuk Mendukung Agenda Sustainable Development Goals (SDGs) Soni Prayogi; Teguh Aryo Nugroho; Nita Indriani Pertiwi; Wahyu Agung Pramudito; Marza Ikhsan Marzuki; Muhammad Abdillah; Wahyu Kunto Wibowo; Herminarto Nugroho; Teuku Muhammad Roffi; Muhammad Muhammad
I-Com: Indonesian Community Journal Vol 5 No 1 (2025): I-Com: Indonesian Community Journal (Maret 2025)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/icom.v5i1.6486

Abstract

ABSTRACT This Community Service Activity aims to improve students' technical skills in robotics while supporting SDGs, especially quality education and technological innovation. Training includes robotics assembly, programming, and applications, with an interactive approach tailored to the curriculum. The program begins with the identification of partner schools with limited resources, followed by coordination and preparation of training modules. Students learn basic robotics theory including the principles of electronics, mechanics, and programming, as well as the practice of assembling and programming robots in small groups. Internal competitions are held to test students' abilities and motivate them to solve problems creatively. The main challenges include limited facilities and time, overcome by adjusting materials and schedules. Evaluations show significant improvements in student skills, with creative innovations in technology-based solutions to support SDGs. The program has succeeded in generating students' interest in technology, providing a strong foundation for similar programs in the future, and encouraging collaboration between education and industry.
Sinergi Energi Terbarukan dan Pertanian Modern: Penerapan PLTS untuk Meningkatkan Kinerja Usaha Hidroponik di Pagifarm Bogor Soni Prayogi; Teguh Aryo Nugroho; Nita Indriani Pertiwi; Wahyu Agung Pramudito; Marza Ikhsan Marzuki; Muhammad Abdillah; Wahyu Kunto Wibowo; Herminarto Nugroho; Teuku Muhammad Roffi; Muhammad Muhammad
I-Com: Indonesian Community Journal Vol 5 No 2 (2025): I-Com: Indonesian Community Journal (Juni 2025)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/i-com.v5i2.7395

Abstract

Permasalahan ketergantungan energi konvensional dalam usaha hidroponik menghambat produktivitas dan efisiensi operasional, terutama pada wilayah dengan akses listrik terbatas atau tidak stabil. Kegiatan pengabdian masyarakat ini dilaksanakan di Pagifarm Bogor dengan tujuan meningkatkan kinerja usaha hidroponik melalui penerapan Pembangkit Listrik Tenaga Surya (PLTS) berbasis IoT. Metode pelaksanaan meliputi survei kebutuhan energi, perancangan dan instalasi sistem PLTS, serta pelatihan penggunaan dan pemeliharaan kepada mitra. Hasil kegiatan menunjukkan adanya peningkatan efisiensi penggunaan energi, penurunan biaya operasional listrik, serta peningkatan produktivitas tanaman hidroponik. Selain itu, mitra mampu secara mandiri mengelola sistem PLTS yang terpasang. Kesimpulannya, sinergi antara energi terbarukan dan teknologi pertanian modern mampu mendukung ketahanan pangan dan keberlanjutan usaha tani, serta memberikan dampak positif terhadap ekonomi lokal dan lingkungan.
Remaining useful life prognosis of low-speed slew bearing using random vector functional link Wahyu Caesarendra; Dimas Revindra Rahardja; Muhammad Abdillah; Seno Darmanto; Sri Utami Handayani; Wahyu Dwi Lestari; Grzegorz Krolczyk
Mechanical Engineering for Society and Industry Vol 5 No 1 (2025)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/mesi.12965

Abstract

Bearings have a very important role in an industry. However, the cost of maintenance and replacement of bearings are very expensive especially for slew-bearing which operated in a very low speed. If the low-speed slew bearing shutdown suddenly, it will also cause a financial issue to the certain industries with rely on the rotating machines because the entire machine will be shut down and the production will be stop Therefore, monitoring of the low-speed slew bearing condition at all times is necessary to predict the bearing failure. There has been advance monitoring devices and systems related to the vibration condition monitoring for bearing and rotating machines, however, in certain cases those monitoring devices and systems are not sufficient. Machine learning is offered to complement and contribute in this case which aims to determine the prediction and Remaining Useful Life (RUL) of the bearing before the bearing experiences more damage. In this paper, the Random Vector Functional Link (RVFL) is used to predict RUL using low speed slew bearing data from University of Wollongong, Australia. The main evaluation matrix such as RMSE is used as an evaluation of the performance of the model used. According to the prediction results, the best modeling results are obtained using a data ratio of 80:20 and a SELU activation function that produces the best average RMSE value. The prediction value of Remaining Useful Life (RUL) of the bearing is 94.24%.