Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal G-Tech : Jurnal Teknologi Terapan Indonesian Community Journal
Wahyu Kunto Wibowo
Universitas Pertamina, Indonesia
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Environmental Science Public Health Social Sciences Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
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.
Intelligent Energy Prediction in Smart Manufacturing Using Deep Learning Techniques Soni Prayogi; Wahyu kunto Wibowo
G-Tech: Jurnal Teknologi Terapan Vol 10 No 3 (2026): G-Tech, Vol. 10 No. 3 July 2026
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v10i3.10725

Abstract

The transition toward smart manufacturing requires advanced energy management strategies that leverage artificial intelligence to improve operational efficiency and sustainability. This study proposes a novel deep learning framework based on a Long Short-Term Memory (LSTM) network for analyzing and predicting energy consumption in smart manufacturing environments using real-time data acquired from Internet of Things (IoT)-enabled industrial sensors. Unlike previous studies that primarily focus on offline energy forecasting or static datasets, the proposed approach integrates temporal energy consumption patterns from heterogeneous sensor streams to support predictive energy management and dynamic load optimization. The collected data were preprocessed through normalization and feature engineering before being trained and evaluated using the LSTM model. Experimental results demonstrate that the proposed model achieves a Mean Absolute Error (MAE) of 0.84 kWh, a Root Mean Square Error (RMSE) of 2.13 kWh, and a coefficient of determination (R²) of 0.987, indicating high prediction accuracy. Furthermore, the predictive framework enables an estimated energy consumption reduction of 14.8% through proactive load scheduling. These findings demonstrate that integrating LSTM-based deep learning with IoT sensor networks provides an effective solution for intelligent energy forecasting, improves manufacturing efficiency, and contributes to sustainable industrial development.
Co-Authors Herminarto Nugroho Marza Ikhsan Marzuki Muhammad Abdillah Muhammad Muhammad Nita Indriani Pertiwi Prayogi, Soni Teguh Aryo Nugroho Teuku Muhammad Roffi Wahyu Agung Pramudito