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All Journal JIKO (Jurnal Informatika dan Komputer) Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer
Bagus Kusuma
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Computer Science & IT

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Analisis Komposit Epoxy HGM Carbon Fiber dan Epoxy HGM Sisal Woven sebagai Material Rompi Anti Peluru Bagus Kusuma; Elza Ully Tiara Tampubolon; Sovian Aritonang
Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer Vol. 3 No. 1 (2025): Februari: Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mars.v3i1.693

Abstract

This research examines the potential of Epoxy-HGM-Carbon Fibre and Epoxy HGM Sical Woven Fibre composites as alternative materials for bulletproof vests. These two materials were chosen because they have similar ballistic protection capabilities to kevlar but with lighter weight and more economical cost. Using the finite element method, this study simulates the resistance of each composite to the penetration and impact energy of projectiles in accordance with the NIJ 0101.06 standard to protect users from ballistic threats. The simulation results show that the Epoxy-HGM-S Sisal Woven Fibre specimen at an optimum thickness of 30 mm as well as Epoxy-HGM-Carbon Fibre at a thickness of 18 to 30 mm are able to meet the penetration, Back Face Signature (BFS), and residual kinetic energy criteria that comply with the safe limits for users. This research makes an important contribution to the identification of alternative materials that not only improve user comfort and mobility, but also maintain ballistic protection effectiveness for military and security applications, especially for personnel who need protection against ballistic projectiles.
Studi Komparasi Bahan Barium Ferrite Magnet Dan Pani/Fe₃O₄, Sebagai Radar Absorbing Material (RAM) Elza Ully Tiara Tampubolon; Bagus Kusuma; Sovian Aritonang
Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer Vol. 3 No. 1 (2025): Februari: Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mars.v3i1.717

Abstract

This research examines the effectiveness of Barium Ferrite and PANI/Fe₃O₄ composite as Radar Absorbing Material (RAM) to reduce radar detection. Barium Ferrite has high absorption at high frequencies as well as good thermal stability, making it suitable for applications under extreme and long-term conditions. In contrast, PANI/Fe₃O₄ composites exhibit high flexibility, the ability to absorb waves over a wider frequency range, as well as light weight, ideal for requirements with lightweight materials, such as aircraft. The analysis shows that the selection of RAM depends on the application requirements regarding frequency range and thermal stability. This study recommends the development of composite materials that combine the advantages of both materials as well as field tests to ensure optimal performance in stealth applications.
KLASIFIKASI JENIS PENYAKIT PADA TANAMAN PADI MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK Bagus Kusuma; Teguh Iman Hermanto; Candra Dewi Lestari
JURNAL INFORMATIKA DAN KOMPUTER Vol 9, No 1 (2025): Februari 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiko.v9i1.1395

Abstract

Padi adalah tanaman pangan utama di Indonesia dan memiliki peran vital dalam perekonomian serta kehidupan sehari-hari masyarakat. Namun, produksi padi saat ini mengalami penurunan akibat serangan hama dan penyakit. Deteksi dini dan klasifikasi penyakit padi yang akurat sangat penting untuk mengurangi dampak negatif ini. Pada penelitian ini dilakukannpembangunan dan pelatihan model Convolutional Neural Network (CNN) untuk mengenali kondisi kesehatan tanaman padi. Model dilatih dengan dataset citra daun padi dan dioptimasi dengan parameter terbaik yaitu 30 epoch, batch size 45, dan optimizer Lion. Hasil pengujian menunjukkan akurasi 75% untuk data uji dengan loss 59%, dan akurasi 76% untuk data latih dengan loss 61%. Model ini juga berhasil diimplementasikan dalam aplikasi mobile berbasis Android. Penelitian ini diharapkan dapat berkontribusi pada sektor pertanian Indonesia dengan menyediakan alat deteksi penyakit padi yang lebih efisien dan efektif.
Co-Authors Bagus Kusuma Wijaya Candra Dewi Lestari Elza Ully Tiara Tampubolon Sovian Aritonang Teguh Iman Hermanto Wayan Eny Mariani