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All Journal JURNAL INTEGRASI JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Teknologi dan Riset Terapan (JATRA) Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam J-ENSITEC (Journal of Engineering and Sustainable Technology) Journal of Applied Mechanical Technology (JAMET)
Dzulfiqar, Mohamad Alif
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Aerospace Engineering Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Other

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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

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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 Ari Wibowo Ariyanto, Nugroho Pratomo Aryeni, Illa Baharudin, Budi Batubara, Ninda Hardina Budiana, Budiana Budiman Budiman Butar, Hendra Butar Cahyo Budi Nugroho Darmoyono, Aditya Gautama Dija, Nur Rafia Diono, Diono Fajrin, Aulia Futra, Asrizal Deri Fyona, Annisa Gemala, Mega Gusnam, Mu'thiana Hasnira Hasnira, Hasnira Heni Pujiastuti Hermawan, Muhammad Ghandy Razzaki Husen Iradhat, Achmad Yudha Irmansyah Lubis, Ahmadi Juangsa Putra, Lalu Giat Kamarudin Kamarudin Leksonowati, Nur Fitria Pujo Leo Van Gunawan Lubis, Ahmadi Irmansyah Mahdaliza, Rahmi Manurung, Meilani Mandhalena Maulidiah, Hana Mutialif Mufariz, Mufti Fathonah Mulyadi Mulyadi Nova, Muhammad Andi Nurul Fadhilah Nurul Laili Arifin, Nurul Laili Oktani, Dessy Pamungkas, Nurman Pujo, Nur Fitri Purba, Adi Syahputra Puspita, Roza Rahman Hakim Reynaldi, Muhammad Ryan Rossbandrio, Wowo Saputra, Ihsan Siregar, James Sriyanto Sriyanto Stefani, Windy SUSI LESTARI Wicaksono, Muhammad Jaka Wimbang Zaimah, Zaimah