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All Journal International Journal of Advances in Intelligent Informatics Budimas : Jurnal Pengabdian Masyarakat Jurnal Teknimedia: Teknologi Informasi dan Multimedia SENTRI: Jurnal Riset Ilmiah ORAHUA : Jurnal Pengabdian Kepada Masyarakat
Thomas Brian
Politeknik Perkapalan Negeri Surabaya
Religion Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Iron welding spot segmentation using Nested UNet (UNet++) enhanced with diverse convolutional modules Thomas Brian; Oskar Natan; Yohanes Yohanie Fridelin Panduman; Anggarjuna Puncak Pujiputra
International Journal of Advances in Intelligent Informatics Vol 12, No 2 (2026): May 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v12i2.2250

Abstract

Welding inspection plays an essential role in manufacturing industries to ensure the integrity and quality of weld joints. However, the prevalent manual inspection procedures are inherently subjective, prone to bias, and result in inconsistent quality assessments. Therefore, there is a strong need for an automated, intelligent system capable of objectively detecting welding spots. To address this, we propose an advanced segmentation model based on deep learning and computer vision techniques, specifically utilizing a Nested UNet (UNet++) architecture enhanced by extensive architectural modifications and comprehensive hyperparameter tuning. To further optimize segmentation performance, we systematically compare various convolutional blocks integrated into the bottleneck of the network architecture. Our experimental evaluation demonstrates that employing a VGG convolutional block at the bottleneck of Nested UNet achieves the highest performance, reaching an Intersection over Union (IoU) score of 76.18% and a validation loss of 0.1713 on our collected dataset. This research advances automated welding inspection by demonstrating that an enhanced Nested UNet with an optimized VGG bottleneck significantly improves weld spot segmentation accuracy. The proposed framework provides a robust benchmark for future studies on intelligent industrial visual inspection and deep learning-based quality assurance.
SISTEM DETEKSI KERUSAKAN PANEL PLTS APUNG DI EMBUNG SIDOBANDUNG BERBASIS CONVOLUTIONAL NEURAL NETWORK DENGAN VISUALISASI AUGMENTED REALITY Thomas Brian; Immanuel Freddy Augustino; Parman Parman; Muhamad Sukarno
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.364

Abstract

This study aims to develop an Augmented Reality (AR) application integrated with a Convolutional Neural Network (CNN) as an interactive system for detecting damage in floating solar power plant (PLTS) panels at Embung Sidobandung in order to maintain the efficiency of the photovoltaic energy system. Conventional manual inspection methods are considered inefficient and prone to errors due to human factors. Therefore, a deep learning approach is employed to automatically and interactively detect and classify solar panel damage. AR technology is utilized to display panel condition information directly through a mobile device camera, enabling real-time damage monitoring. The dataset consists of 615 solar panel images, including 472 images of physical damage and 143 images of electrical damage. Experimental results show that the system is capable of classifying solar panel damage types in real time, achieving a precision of 93.48%, recall of 89.58%, and an F1-score of 91.49% for physical damage, and a precision of 70.59%, recall of 80.00%, and an F1-score of 75.00% for electrical damage, with an overall accuracy of 87.30%. Although the developed application provides interactive and informative visualization, varying lighting conditions in aquatic environments and differences in image acquisition angles remain challenges that affect system accuracy. Overall, the integration of CNN and AR has the potential to serve as an effective and efficient solution for developing damage detection systems for floating solar power plant (PLTS) panels.
Mengenal Dunia Maritim dengan Beraneka Warna Sekarsari Wibowo; Friska Intan Sukarno; Indri Ika Widyastuti; Alief Nur Aisyi Maulidhia; Thomas Brian
ORAHUA : Jurnal Pengabdian Kepada Masyarakat Vol. 2 No. 02 (2025): Januari
Publisher : Faatuatua Media Karya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70404/orahua.v2i02.128

Abstract

Kegiatan Pengenalan Dunia Maritim Melalui Aneka Warna bertujuan untuk meningkatkan pengetahuan dan kreativitas anak-anak di tingkat pendidikan usia dini. Program ini dirancang secara interaktif dengan melibatkan aktivitas pengenalan dengan media gambar dan vidio serta aktivitas mewarnai yang berfokus pada objekobjek dunia maritim, kapal, ikan dan terumbu karang. Kegiatan ini dibagi menjadi beberapa tahap, yaitu perencanaan, pelaksanaan, serta monitoring dan evaluasi. Hasil kegatan menunjukkan peningkatan pengetahuan, dan kreativitas siswa PAUD Sepuluh Nopember tentang dunia maritim. Siswa yang sebelumnya memiliki pengetahuan terbatas tentang laut sekarang dapat memahami laut sebagai sarana transportasi dan habitat makhluk hidup, mengenal berbagai transportasi dan biota laut. Program ini juga menumbuhkan kreativitas siswa melalui kegiatan mewarnai. Ketertarikan dan partisipasi siswa dalam rangkaian kegiatan menunjukkan bahwa program ini efektif dan menarik bagi anak-anak usia dini
Desain dan Simulasi Sistem Pembangkit Listrik Tenaga Bayu Skala Kecil Untuk Penerangan di Perahu Nelayan Parman Parman; Rahmat Basya Shahrys Tsany; Dicki Nizar Zulfika; Thomas Brian
SENTRI: Jurnal Riset Ilmiah Vol. 4 No. 11 (2025): SENTRI : Jurnal Riset Ilmiah, November 2025
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/sentri.v4i11.4888

Abstract

The utilization of renewable energy in the maritime sector serves as a strategic solution to reduce fishermen's dependence on expensive and environmentally unfriendly fossil fuels. This study develops a mini Wind Power Plant (PLTB) model that can be implemented on fishing boats using a MATLAB Simulink-based simulation approach. The study encompasses turbine aerodynamic design, generator selection, and control system optimization to enhance the efficiency of wind energy conversion into electrical power. Simulation results indicate that at an average wind speed of 7.7 m/s, the designed mini wind turbine is capable of generating 125.8 Watts of mechanical power with a peak torque of 3.44 Nm at a wind speed of 12 m/s. The study also calculates the turbine shaft size at 6 mm, the turbine-side pulley diameter at 70 mm, and the generator-side pulley diameter at 39.63 mm, with a belt drive length of 473.75 mm, based on the generator specifications of 1500 RPM and 81% efficiency. Considering the dynamic maritime environment, the design is evaluated through performance simulations using MATLAB Simulink to ensure power output stability under various wind speed conditions. The analysis demonstrates that the system can maintain wind energy conversion efficiency at optimal wind speeds and has significant potential for small-scale applications.
Workshop Kreatif Mengenal Jenis Kapal Melalui Metode Origami dan Game Edukasi di Panti Asuhan Assalafiah Putri Nur Rahayu; Mustika Kurnia Mayangsari; Teguh Junian Kuswanto; Ekananda Sulistyo Putra; Anggarjuna Puncak Pujiputra; Thomas Brian; Ardhon Rakhmadi
BUDIMAS : JURNAL PENGABDIAN MASYARAKAT Vol. 8 No. 2 (2026): BUDIMAS : Jurnal Pengabdian Masyarakat
Publisher : LPPM ITB AAS Indonesia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/budimas.v8i2.20529

Abstract

Pengenalan dunia maritim dan jenis-jenis kapal sejak dini penting untuk menumbuhkan minat generasi muda, termasuk anak-anak di panti asuhan yang seringkali memiliki keterbatasan akses terhadap media pembelajaran interaktif. Kegiatan pengabdian masyarakat ini bertujuan untuk mengenalkan berbagai jenis kapal kepada anak-anak di Panti Asuhan Assalafiah melalui pendekatan yang menyenangkan dan mudah dipahami. Pelaksanaan kegiatan menggunakan metode workshop kreatif yang intensif dan berorientasi pada hasil nyata (outcome-oriented). Kegiatan diawali dengan penyampaian materi teori secara singkat dan padat, dilanjutkan dengan praktik langsung (hands-on practice) pembuatan origami kapal serta permainan edukasi di bawah bimbingan instruktur. Evaluasi keberhasilan program diukur melalui analisis komparatif nilai rata-rata kuesioner sebelum (pre-test) dan sesudah (post-test). Hasil kegiatan menunjukkan peningkatan pemahaman peserta yang signifikan mengenai jenis-jenis kapal. Anak-anak panti asuhan menunjukkan antusiasme yang tinggi dan mampu menyelesaikan karya origami dengan baik sesuai instruksi. Metode origami dan game edukasi terbukti efektif sebagai media pembelajaran interaktif dalam meningkatkan pengetahuan maritim anak-anak panti asuhan assalafiah. Program ini disarankan untuk terus dilanjutkan dengan variasi materi maritim lainnya.
Co-Authors Alief Nur Aisyi Maulidhia Anggarjuna Puncak Pujiputra Ardhon Rakhmadi Dicki Nizar Zulfika Ekananda Sulistyo Putra Friska Intan Sukarno Immanuel Freddy Augustino Indri Ika Widyastuti Muhamad Sukarno Mustika Kurnia Mayangsari Oskar Natan Parman Parman Putri Nur Rahayu Rahmat Basya Shahrys Tsany Sekarsari Wibowo Teguh Junian Kuswanto Yohanes Yohanie Fridelin Panduman