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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) PROFICIO: Jurnal Pengabdian Masyarakat Journal of Informatics and Communication Technology (JICT) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Journal of Informatics and Communication Technology (JICT) Computer Journal Smatika Jurnal : STIKI Informatika Jurnal
Arif Rahman Hakim
Universitas Telkom
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mathematics Social Sciences Other

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Edukasi Perancangan Rekayasa Perangkat Lunak Bagi Siswa Untuk Menghadapi Tantangan Revolusi Industri 5.0 Agus Suwarno; Antika Zahrotul Kamalia; Arif Rahman Hakim; Pahmi Bagja; Adam Wira Hadi Kusuma
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 1 (2026): Juli 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i1.1439

Abstract

Kegiatan Pengabdian kepada Masyarakat ini bertujuan meningkatkan pemahaman dan keterampilan siswa SMKN 6 Kota Bekasi dalam perancangan Rekayasa Perangkat Lunak untuk menghadapi tantangan Revolusi Industri 5.0. Pelaksanaan kegiatan menggunakan seminar edukatif, diskusi interaktif, studi kasus, praktik perancangan, pendampingan, serta evaluasi pre-test dan post-test. Materi mencakup identifikasi masalah, analisis kebutuhan pengguna, perancangan sistem, desain antarmuka dan basis data, implementasi sederhana, serta pengujian dan evaluasi. Hasil kegiatan menunjukkan peningkatan rata-rata pemahaman siswa dari 45% pada pre-test menjadi 84% pada post-test. Siswa juga mampu menghasilkan rancangan perangkat lunak sederhana yang berorientasi pada kebutuhan pengguna, mudah digunakan, dan memperhatikan etika teknologi. Dengan demikian, kegiatan ini efektif meningkatkan kompetensi dasar perancangan perangkat lunak serta membangun kesiapan siswa menghadapi perkembangan industri digital yang human-centric dan berkelanjutan.
Early detection of vascular streak dieback (VSD) disease in cocoa plants using deep learning Dewi Marini Umi Atmaja; Arif Rahman Hakim; Fadhil Rozi Hendrawan; Komang Diah Devi Pramesty; Naufal Fadhilah Fitrah; Faiz Rochmatullah Widhaputra
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v15i3.pp1087-1096

Abstract

Vascular streak dieback (VSD), caused by Ceratobasidium theobromae, poses a significant threat to cocoa (Theobroma cacao) production, leading to substantial yield losses and plant mortality. Early detection is critical to mitigate disease spread and reduce economic impact. While convolutional neural network (CNN) architectures like VGG-16 and ResNet-50 excel in leaf disease detection, no prior studies address stem-based VSD symptomatology where the disease originates in vascular tissues. This study presents the first CNN specifically developed for cocoa stem VSD detection, achieving 99.16% test accuracy with a lightweight architecture that outperforms VGG16/ResNet50 in both accuracy and mobile inference speed. A novel dataset of 215 cocoa stem images was curated and augmented for robustness. Additional evaluation metrics, including precision, recall, specificity, and F1-score, further confirm the reliability of the model. The model was successfully converted into TensorFlow Lite (TFLite) format, enabling deployment on mobile devices for real-time disease detection. This study highlights the potential of integrating deep learning into mobile and drone-based agricultural systems to support precision farming and early intervention strategies.
Penerapan Metode OWASP IoT Top 10 dalam Analisis Kerentanan Keamanan Perangkat Internet of Things: Studi Kasus Smart Waste Arif Rahman Hakim; Rizki Surya Permana; Demi Adidrana; Hertanto Suryoprayogo; Deny Haryadi
Computer Journal Vol. 4 No. 2 (2026): August
Publisher : Yayasan Pendidikan Mitra Mandiri Aceh (YPMMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58477/cj.v4i2.471

Abstract

This study examines security vulnerabilities in a publicly accessible IoT-based smart waste system using Nmap, Wireshark, and OWASP ZAP to assess network services, packet traffic, and the web application layer. Results were mapped to the OWASP IoT Top 10 (2018). Because the assessment was external black-box testing without exploitation, the mapping is indicative rather than comprehensive. Nmap identified several active TCP ports, although only six open ports were explicitly documented. Wireshark captured 62,591 packets, indicating port-scanning activity and ongoing TCP communication. OWASP ZAP identified 14 web application weaknesses: six medium, five low, and three informational, with no high-risk findings. Four OWASP IoT Top 10 categories (I2, I3, I7, and I9) were supported by direct evidence, while I1 and I5 require further verification and I4, I6, I8, and I10 were outside the testing scope. Key risks involved insecure network services, default settings, and inadequate data protection during transmission and storage.
Co-Authors Adam Wira Hadi Kusuma Adelia Chitra Sazkia Agus Suwarno Alan Abyan Maftuh Antika Zahrotul Kamalia Daniswara Rafi Pandora Dede Rizki Demi Adidrana Deny Haryadi Dewi Marini Umi Atmaja Fadhil Rozi Hendrawan Faiz Rochmatullah Widhaputra Hertanto Suryoprago Hertanto Suryoprayogo Ilham Roni Yansyah Komang Diah Devi Pramesty Muhammad Zidan Alfarizi Muttaqin, Widang Naufal Fadhilah Fitrah Pahmi Bagja Putri Rizkiyah Rizki Surya Permana Suwaryo, Niko Zaidan Mufaddhal Zhawa Kamela