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All Journal Jurnal Elkasista SinarFe7
Gunawan, Ardiansyah
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Materials Science & Nanotechnology

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Journal : SinarFe7

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PENERAPAN ARSITEKTUR JST DALAM DEEP LEARNING UNTUK MENINGKATKAN AKURASI KLASIFIKASI GAMBAR DENGAN AUTOENCODER: Bahasa Indonesia Hudaya, Citra; Gunawan, Ardiansyah; Wijaya Tri, Bintar
SinarFe7 Vol. 7 No. 1 (2025): SinarFe7-7 2025
Publisher : FORTEI Regional VII Jawa Timur

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Abstract - The development of artificial intelligence technology, particularly deep learning, has made significant contributions to digital image processing across various fields such as medicine, security, and manufacturing industries. This study aims to implement the autoencoder method within an Artificial Neural Network (ANN) architecture to optimally enhance image classification accuracy. The autoencoder is employed as an unsupervised learning technique to extract essential and relevant features from input images before passing them to the classification layer. The training process was carried out using a carefully curated image dataset, and the model was evaluated to measure classification performance based on accuracy, precision, and recall. The experimental results show that integrating an autoencoder into the ANN architecture can improve feature extraction efficiency, reduce noise, and deliver more accurate and consistent classification results compared to conventional approaches. This research demonstrates that the autoencoder can serve as a vital component in modern deep learning-based classification systems.
Sistem Deteksi Musuh Berbasis ESP32 dan mmWave C4001 untuk Pos Dengar Gunawan, Ardiansyah; Ramdhani Hidayat, Bayu; Ahmad Zen, Elit; Maulana, Irfan
SinarFe7 Vol. 7 No. 1 (2025): SinarFe7-7 2025
Publisher : FORTEI Regional VII Jawa Timur

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Keamanan dan efektivitas dalam mendeteksi keberadaan musuh di wilayah operasi sangat krusial bagi keberhasilan misi militer. Penelitian ini merancang dan mengimplementasikan sistem deteksi musuh berbasis mikrokontroler ESP32 yang terintegrasi dengan sensor mmWave C4001 dan modul komunikasi nirkabel HC-12, sebagai alternatif portabel pengganti pos dengar konvensional di Basis Operasi Depan (BOD). Sistem ini mendeteksi pergerakan manusia secara real-time melalui gelombang mikro berfrekuensi tinggi yang mampu mengenali keberadaan tanpa kontak fisik. Modul HC-12 berfungsi mengirimkan data deteksi secara nirkabel ke pos penerima pada jarak jauh. Metodologi penelitian mencakup perancangan perangkat keras dan perangkat lunak, pengujian fungsi sensor, serta pengukuran jangkauan komunikasi. Hasil pengujian menunjukkan bahwa sistem mampu mendeteksi keberadaan manusia hingga 6 meter dengan akurasi tinggi, serta mengirimkan data ke penerima secara stabil hingga 100 meter tanpa halangan, dengan konsumsi daya rendah. Temuan ini memperlihatkan potensi sistem sebagai solusi deteksi otomatis di BOD, dengan arah pengembangan pada integrasi jaringan deteksi berbasis mesh untuk memperluas cakupan area
Co-Authors Ahmad Zen, Elit Hidayat, Bayu Ramdhani Hudaya, Citra Irfan Maulana, Irfan Jeki Saputra Ramdhani Hidayat, Bayu Wijaya Tri, Bintar