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All Journal JURNAL INTEGRASI JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Teknologi dan Riset Terapan (JATRA) Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat
Nova, Muhammad Andi
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Aerospace Engineering Humanities Computer Science & IT Education Electrical & Electronics Engineering Engineering Mechanical Engineering Other

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Pengaruh Engine Bleed Trip Terhadap Tingkat Kebutuhan Pergantian Komponen Pada Pesawat B737-800 Nova, Muhammad Andi; Iradhat, Achmad Yudha; Siregar, James; Dzulfiqar, Mohamad Alif; Dija, Nur Rafia; Rossbandrio, Wowo
Jurnal Teknologi dan Riset Terapan (JATRA) Vol. 6 No. 1 (2024): Jurnal Teknologi dan Riset Terapan (JATRA) - June 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jatra.v6i1.7795

Abstract

An engine bleed trip is an indication that there is a failure in the engine bleed system in regulating the temperature and pressure of the bleed air. This can affect the work of other systems that rely on the output of the engine bleed system, one of which is the cabin pressure system. The aim of this research is to find out the percentage level of the need for main components in the engine bleed system to be replaced in handling engine bleed trip cases. This research is an ex post-facto comparative research with primary data collection methods sourced from aircraft maintenance databases and interviews. The research results showed that from a total of 52 bleed trip cases that occurred during 17 months, the percentage of main components that needed to be replaced were the 390F thermostat sensor (42.3%), precooler control valve (19.2%), pressure regulating shuttle valve (11 .5%), bleed air regulator (7.7%), and the rest are other components.
Pelatihan Penggunaan Software Autocad sebagai Upaya Peningkatan Kompetensi Siswa SMK Kota Batam Cahyagi, Danang; Restu, Fedia; Yuniarsih, Nidia; Nova, Muhammad Andi; Saputra, Hendra; Satoto, Sapto Wiratno; Mutiarani, Mutiarani; Aryswan, Adhe; Fyona, Annisa; Havwini, Tian; Fadilah, Nurul; Rahman, Kholilur
Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat Vol 24, No 2 (2024): Suluah Bendang: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/sb.05790

Abstract

Kota Batam merupakan daerah dengan julukan kota industri. Sejak setelah bertranformasi menjadi kawasan industri kota Batam memiliki berbagai macam indutri yang dibangun, sehingga terbuka banyak peluang kerja yang tersedia. Salah satu keberlanjutan yang perlu didukung yaitu ketersediaan tenaga kerja terampil yang memiliki kompetensi dibidang keteknikan. Gambar dan penggunaan software CAD menjadi salah satu kompetensi yang perlu dipenuhi oleh masyarakat. Upaya menyediakan tenaga kerja terampil dapat dilihat dari tersedianya sekolah menengah kejuruan. Meskipun demikian, keterbatasan fasilitas praktik menjadi salah satu kendala yang dihadapi sebagian sekolah dalam melaksanakan layanan pendidikannya. Kegiatan Pelatihan Penggunaan Software AutoCAD kepada siswa/i SMK Kota Batam Tahun 2024 kemudian hadir menjadi salah satu solusi untuk dapat membantu sekolah dalam meningkat mutu pendidikan vokasi di Kota Batam. Pelatihan ini didanai secara internal oleh Politeknik Negeri Batam dan telah dilaksanakan di Politeknik Negeri Batam pada 23 – 26 Juli 2024. Adapun mitra peserta pengabdian ini adalah dari siswa dan guru SMK S Aljabar Batam, SMK S Kartini, SMK N 9 Batam. Beberapa luaran yang telah diselesaikan pada kegiatan pengabdian ini adalah terselenggaranya kegiatan dan penyusunan modul pelatihan. pemberitaan pada media masa, HKI modul, poster dan video kegiatan.
Identifikasi Penyebab Terjadinya Landing Gear Indication Tidak Berfungsi Normal pada Pesawat Boeing 737-900 ER Mohamad Alif Dzulfiqar; Nabila Ayu Saputri; Nova, Muhammad Andi; James Siregar; Lalu Giat Juangsa Putra; Nur Rafia Dija; Meilani Mandhalena
JURNAL INTEGRASI Vol. 17 No. 1 (2025): Jurnal Integrasi - April 2025
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v17i1.9510

Abstract

The Boeing 737-900 ER aircraft has a system called landing gear indication which in its application uses a proximity sensor that is useful in providing information about the position of the landing gear. However, this system can experience problems where if the landing gear indication does not function, the pilot cannot obtain information from the instrument that ensures the position of the landing gear. The purpose of this study is to identify problems that often occur in the landing gear indication system on the aircraft. The analysis was carried out using the Root Cause Analysis (RCA) method with the Fishbone Diagram approach. From the identification results, it was found that the main cause was a problem with the proximity switch sensor experiencing corrosion and changes in position which caused the signal reading to be inaccurate. For this reason, it is necessary to replace components and adjust the sensor position so that the system can run properly.
Aircraft Image Classification on a Small-Scale Dataset using MobileNetV2 with Grad-CAM as Explainable AI Lestari, Susi; Dzulfiqar, Mohamad Alif; Lubis, Ahmadi Irmansyah; Nova, Muhammad Andi; Zaimah, Zaimah; Mulyadi, Mulyadi
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10546

Abstract

This study explores aircraft image classification using MobileNetV2 combined with Gradient-weighted Class Activation Mapping (Grad-CAM) for model interpretability. A dataset of 1,500 balanced images—helicopters, propeller aircraft, and jets—was split into training, validation, and testing sets with data augmentation to reduce overfitting. Transfer learning with pre-trained MobileNetV2 achieved an accuracy of 87.56%, with macro-average precision and recall of 85.76% and 87.69%. Grad-CAM visualizations confirmed that correct predictions relied on distinctive features such as rotor blades, propellers, and engines, while misclassifications often stemmed from background distractions or less discriminative areas. These findings demonstrate the potential of lightweight architectures for small-scale datasets and highlight the value of Explainable AI in validating deep learning models. The study provides a practical reference for educational contexts and offers directions for future work with larger datasets.
Co-Authors Adhe Aryswan Cahyagi, Danang Dija, Nur Rafia Dzulfiqar, Mohamad Alif Fyona, Annisa Hendra Saputra Iradhat, Achmad Yudha James Siregar Kholilur Rahman, Kholilur Lalu Giat Juangsa Putra Lubis, Ahmadi Irmansyah Meilani Mandhalena Mohamad Alif Dzulfiqar Mulyadi Mulyadi Nabila Ayu Saputri Nidia Yuniarsih Nur Rafia Dija Nurul Fadilah, Nurul Restu, Fedia Rossbandrio, Wowo Satoto, Sapto Wiratno Siregar, James Sugeng, Santoso SUSI LESTARI Tian Havwini Zaimah, Zaimah