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PERANCANGAN DAN PENGEMBANGAN SISTEM DETEKSI MUSUH NIRKABEL MENGGUNAKAN ESP32, SENSOR MMWAVE C4001, DAN MODUL HC-12 SEBAGAI PENGGANTI POSISI PENDENGAR DI BASIS OPERASI MAJU (FOBS) Gunawan, Ardiansyah; Hidayat, Bayu Ramdhani; Saputra, Jeki
Jurnal Elkasista Vol 5 No 2 (2024): Jurnal Elkasista
Publisher : Pustaka Poltekad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54317/elka.v5i2.686

Abstract

: Security and effectiveness in detecting enemy presence in operational areas are critical to the success of military missions. This research designs and develops an enemy detection system based on the ESP32 microcontroller integrated with the mmWave C4001 sensor and the HC-12 wireless communication module, as an alternative to conventional listening posts in Forward Operating Bases (FOBs). The system is designed to detect human movement in real-time using high-frequency microwave signals capable of detecting presence without direct physical contact. The HC-12 module is used to wirelessly transmit detection data to a remote receiving post. The methodology includes hardware and software design, sensor function testing, and communication range measurement. Test results show that the system is capable of detecting human presence at a distance of up to 6 meters with high accuracy and transmitting data stably up to 100 meters in unobstructed conditions. The system also has low power consumption, making it suitable for field deployment. The conclusion of this research is that the designed system is effective as a portable and automated alternative to traditional listening posts. Future development is suggested to focus on expanding the system into a mesh-based detection network with multiple nodes to cover a wider area around the Forward Operating Base (FOB). Keywords: ESP32, mmWave C4001, HC-12, enemy detection, listening post, wireless system
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

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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Abstract

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