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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control ILKOM Jurnal Ilmiah Jurnal Sistem Cerdas JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JMECS (Journal of Measurements, Electronics, Communications, and Systems) Teknika Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo) Algoritme Jurnal Mahasiswa Teknik Informatika Paradigma Internet of Things and Artificial Intelligence Journal eProceedings of Engineering
Satyawan, Arief Suryadi
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Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Other

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Realsense Depth Camera Untuk Pengukuran Jarak Pada Mobil Autonom Roda Tiga Marchellyn, Ferryn; Suratman, Fiky Y; Satyawan, Arief Suryadi
eProceedings of Engineering Vol. 11 No. 5 (2024): Oktober 2024
Publisher : eProceedings of Engineering

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Abstract

Abstrak — Penggunaan kamera kedalaman menjadi krusialdalam teknologi kendaraan otonom untuk mengukur jarak objekdi sekitar kendaraan. Intel RealSense Depth Camera menjadisolusi unggul berkat teknologi sensor stereo yang memberikaninformasi kedalaman akurat. Penelitian ini mengeksplorasikemampuan kamera RealSense dalam mengukur jarak padamobil otonom beroda tiga, fokus pada evaluasi akurasi dalamberbagai kondisi operasional seperti kecepatan kendaraan, jarakobjek, dan pencahayaan.Metode menggunakan Depth Camera Intel RealSense D435iuntuk mendeteksi objek dalam jarak kurang dari 8 meter denganalgoritma Non-Max Suppression yang mengurangi tumpangtindih kotak pembatas dan memilih deteksi objek dengan nilaiconfidence score tertinggi. Implementasi melibatkanpenghubungan Depth Camera Intel RealSense D415i ke laptopuntuk pengolahan data jarak. Pengujian membandingkan hasilpengukuran kamera dengan meteran di area jalan sepanjang 8meter x 1.1 meter.Hasil menunjukkan variasi selisih antara jarak kamera danjarak sesungguhnya, dengan persentase kesalahan dihitungmenggunakan rumus. Kamera RealSense menunjukkan akurasiyang cukup baik, meskipun terdapat perbedaan yang disebabkanoleh toleransi pengukuran dan algoritma. Penelitian inimemberikan wawasan untuk pengembangan teknologi kamerakedalaman dalam kendaraan otonom masa depan, denganmempertimbangkan faktor- faktor yang mempengaruhi akurasipengukuran. Kata Kunci: kendaraan otonom, kamera kedalaman, RealSense,pengukuran jarak, akurasi, Non-Max Suppression, sensor stereo.
Efficient Image Transmission for Autonomous Systems Using Residual Dense Feature Networks Over LoRa Networks Praptawilaga, Muhamad Fadly Rizqy; Suranegara, Galura Muhammad; Satyawan, Arief Suryadi
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 1 (2025): March 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v27i1.7584

Abstract

Autonomous systems face challenges in transmitting high-quality images over bandwidth-constrained networks like LoRa, which operates at data rates of 0.3–50 kbps. This study proposes the Residual Dense Feature Network (RDF Net), a super-resolution model designed to optimize image transmission within the constraints of LoRa networks. By leveraging Contrast-Aware Channel Attention (CCA), Enhanced Spatial Attention (ESA), Blueprint Separable Convolution (BSConv), and a progressive approach, RDF Net achieves 20x upscaling, enabling low-resolution images (40x40 pixels) to be reconstructed into high-resolution outputs (800x800 pixels) on a central server. Experimental evaluations demonstrate that Model-4, combining CCA and ESA, delivers state-of-the-art perceptual quality and structural fidelity, while Model-3, using ESA, offers a computationally efficient alternative for resource-constrained scenarios. Simulations of LoRa’s bandwidth limitations reveal that transmitting a single 40x40 image requires approximately 0.208–0.56 seconds at a data rate of 50 kbps. While this demonstrates the feasibility of near real-time communication, the trade-off between latency and visual fidelity remains a critical consideration, particularly for latency-sensitive applications. These findings underscore RDF Net’s potential to address the challenges of high-quality visual communication in bandwidth-constrained environments, paving the way for enhanced autonomous system applications. Further optimization, including adaptive compression strategies, and testing on actual LoRa hardware are recommended to validate its performance in real-world scenarios and explore its applicability to diverse autonomous systems.
Optimasi Sistem Deteksi Jalur pada Miniatur Kendaraan Otonom dengan menggunakan Algoritma Hough Transform berbasis Computer Vision Awalya, Silmi; Suratman , Fiky Y.; Satyawan, Arief Suryadi
eProceedings of Engineering Vol. 12 No. 5 (2025): Oktober 2025
Publisher : eProceedings of Engineering

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Abstract

Perkembangan kendaraan otonom telah menjadi fokus utama dalam dunia teknologi, khususnya dalam aspek deteksi jalur yang presisi pada kondisi lingkungan dinamis. Penelitian ini bertujuan untuk mengembangkan sistem deteksi jalur pada kendaraan otonom miniatur menggunakan algoritma Hough Transform yang dioptimasi dengan strategi deteksi multi-ruang warna berbasis computer vision. Sistem ini diimplementasikan pada modul Duckiebot DB21J yang dilengkapi dengan kamera IMX219 dan pemrosesan oleh Jetson Nano. Metodologi yang digunakan meliputi studi literatur, perancangan sistem, implementasi perangkat keras dan perangkat lunak, serta pengujian komprehensif pada lima skenario berbeda dalam dua kondisi pencahayaan (305 lux dan 181 lux). Hasil menunjukkan bahwa sistem mampu mendeteksi jalur dengan akurasi 97.14% pada kondisi terang dan 96.40% pada kondisi standar, melampaui target minimal 90% dengan detection rate konsisten 99.26% dan 99.16%. Sistem menunjukkan presisi spasial yang sangat baik dengan kesalahan sudut 0.494°-0.57° dan kesalahan posisi 1.19-1.31 cm, serta waktu pemrosesan rata-rata 213-230 ms. Penelitian ini membuktikan superioritas metode yang dikembangkan dengan peningkatan akurasi 6.40%-12.14% dibanding penelitian sebelumnya yang menggunakan CNN+Hough Transform, Hough+Gaussian Filter, dan SVM Model. Sistem ini berpotensi diterapkan pada platform robotika pendidikan dan penelitian lanjutan dalam otomasi kendaraan. Kata kunci — kendaraan otonom, deteksi jalur, computer vision, Hough Transform, Jetson Nano, Duckiebot
Sistem Deteksi Rambu Lalu Lintas Berbasis Computer Vision Untuk Navigasi Miniatur Kendaraan Otonom Saputra, Adhitya Dwi; Suratman, Fiky Y.; Satyawan, Arief Suryadi
eProceedings of Engineering Vol. 12 No. 5 (2025): Oktober 2025
Publisher : eProceedings of Engineering

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Abstract

Abstrak — Teknologi kendaraan otonom menuntut sistem persepsi visual yang andal, khususnya untuk mendeteksi rambu lalu lintas secara real-time. Penelitian ini mengembangkan sistem deteksi rambu berbasis algoritma YOLOv8 dan diimplementasikan pada prototipe miniatur kendaraan otonom. Dataset sebanyak 1.232 gambar dikumpulkan secara mandiri dan diperluas menjadi 3.696 gambar melalui augmentasi. Model YOLOv8n dilatih selama 87 epoch menggunakan Visual Studio Code. Hasil pelatihan menunjukkan precision dan recall sebesar 91,3% serta mAP@0.5 sebesar 91,3%. Pengujian dilakukan dalam kondisi terang dan gelap, statis maupun dinamis. Hasil menunjukkan tingkat keberhasilan deteksi mencapai 90% dalam kondisi terang dan menurun menjadi 48,9% dalam pencahayaan gelap. Sistem juga berhasil menjalankan aksi robotik dengan akurasi 83,3%. Hasil ini menunjukkan sistem dapat mengenali dan merespons rambu lalu lintas secara real-time secara efektif pada skala miniatur. Kata kunci — sistem deteksi, rambu lalu lintas, yolo, computer vision, kendaraan otonom, traffic sign detection
Enhancing Hazy Image Quality with a Modular CNN Encoder–Decoder KHOLIQ, ANDIKA MUHAMMAD NUR; SATYAWAN, ARIEF SURYADI; HAQIQI, MOKH MIRZA ETNISA; AKBAR, FAJAR RAHMAT; NURROHMAH, IASYA FAIQOH; ADAWIYAH, AULIA; WULANDARI, ESTI FITRIA; SUGIAN, RENDI TRI
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 14, No 1: Published January 2026
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v14i1.69

Abstract

This study develops a modular CNN encoder–decoder framework for single-image dehazing by replacing the conventional bottleneck with interchangeable token-mixing modules such as FNet, Spatial-FNet, MLP-Mixer, and gMLP-style designs. The pipeline integrates adaptive preprocessing (CLAHE and histogram matching), photometric augmentations, and training on a controlled subset of the SOTS dataset. Comprehensive quantitative and qualitative evaluations demonstrate substantial improvements over a baseline CNN, with mean PSNR increasing from approximately 18.4 dB to the 23.0–24.0 dB range and SSIM rising from about 0.75 to roughly 0.89–0.91. However, several variants require careful hyperparameter selection and loss-weight tuning to achieve stable performance. The results offer practical guidance for deployment in real-world vision systems.
Performance analysis of OFDM-IM scheme under STO and CFO Suyoto, Suyoto; Subekti, Agus; Satyawan, Arief Suryadi; Mardiana, Vita Awalia; Armi, Nasrullah; Kurniawan, Dayat
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp3293-3299

Abstract

In this letter, performance analysis of orthogonal frequency division multiplexing with index modulation (OFDM-IM) is presented in term of bit error rate (BERs). The analysis considers its performance under two impairments, symbol time offset (STO) and carrier frequency offset (CFO) in frequency-selective fading channel. As orthogonal multicarrier system, OFDM-IM is subject to both inter-symbol interference (ISI) and inter-carrier interference (ICI) in a frequency-selective fading channel. OFDM-IM is a new multicarrier communication system, where the active subcarriers indices are used to carry additional bits of information. In general, in the previous existing works, OFDM-IM are evaluated only for near-ideal communication scenarios by only incorporating the CFO factor. In this work, the OFDM-IM performance is investigated and compared with conventional OFDM in the presence of two impairments, STO and CFO. Simulation results show that OFDM-IM outperforms the conventional OFDM with the presence of STO and CFO, especially at high SNR areas.
Impact of carrier frequency offset and in-phase and quadrature imbalance on the performance of wireless precoded orthogonal frequency division multiplexing Suyoto, Suyoto; Subekti, Agus; Satyawan, Arief Suryadi; Armi, Nasrullah; Ali Wael, Chaeriah Bin; Nurkahfi, Galih Nugraha
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5153-5163

Abstract

Precoding in orthogonal frequency division multiplexing (OFDM) system proved to reduce the peak-to-average power ratio (PAPR), so that it improves BER. However, from the existing literature, the effect of carrier frequency offset (CFO), in-phase and quadrature (IQ) imbalance on precoded wireless OFDM systems has not been carried out. Therefore, this study evaluated the precoded OFDM (P-OFDM) system performance by considering the impact of CFO and IQ imbalance. P-OFDM performance evaluation is expressed in signal-to-interference noise ratio (SINR) and bit error rates (BER). The communication channels used are the additive white Gaussian noise (AWGN) channel and the frequency-selective Rayleigh fading (FSRF) channel, while the channel equalization process is considered perfect. The results of the analysis and simulation show that P-OFDM is greater affected by the presence of CFO and IQ imbalance than conventional OFDM system. In AWGN channel, P-OFDM experiences different SINR for each subcarrier. This is different from conventional OFDM system, where all SINRs are the same for all subcarriers. In the FSRF channel, both the POFDM system and the OFDM system experience different SINR for each subcarrier, where the SINRs fluctuation in the P-OFDM system is much larger than in the OFDM system.
Co-Authors ADAWIYAH, AULIA Adi, Puput Dani Prasetyo Adiprabowo, Tjahjo Agus Subekti Akbar, Fabian AKBAR, FAJAR RAHMAT Ali, Abdul Latif Aloysius Adya Pramudita Aptadarya, Harwin Arentaka, Fiendo Mahendra Argaloka, Aditya Adni Ariffin, Denden Mohamad Arifyandy, Rachmat Artemysia, Khaulyca Arva Arumjeni Mitayani Aurelia, Felicia Bunga Awalya, Silmi Chaeriah Bin Ali Wael, Chaeriah Bin Christian, Yohanes Wahyu Dayat Kurniawan Fauzan, R. Aldam Dwi Fazri, Nurul Fiky Y. Suratman Firman Galura Muhammad Suranegara Hamdani, Nizar Alam HAQIQI, MOKH MIRZA ETNISA Haqiqi, Mokh. Mirza Etnisa Harahap, Taufiq Hidayat Helfy Susilawati Hidayat, Haryanto Iswarawati, Ni Kadek Emy Jody H, Amadeus Evan KHOLIQ, ANDIKA MUHAMMAD NUR Kitagawa, Akio Laksono, Muhammad Fauzan Anggi Fathul Latukolan, Merlyn Inova Christie Linggi, Rinda Safana Manullang, Yan Ario Eko Panca Marchellyn, Ferryn Mardiana, Vita Awalia Marta Dinata, Mochamad Mardi Muhammad Yassir Mulyana, Tri Munawir Munawir Nasrullah Armi Noviely, Isra Fanliv Nugroho, Agung Nurdiana, Dian Nurkahfi, Galih Nugraha NURROHMAH, IASYA FAIQOH Nurul P., Vethrea D. Gynandra Pangemanan, Agnes Novi Anna Paramita, I Gusti Ayu Putri Surya Prameswari, Aulia Widya Praptawilaga, Muhamad Fadly Rizqy Purwoko Adhi Puspita, Heni Putra, Muhammad Taufik Dwi Putra, Nyoman Triyoga Arika Putri, Riza Ayu RR. Ella Evrita Hestiandari Saharuna, Saharuna Samie, Muhammad Ikbal Saputra, Adhitya Dwi Septiyanti, Riska Yucha Shamie, M. Ikbal Siburian, Sebastian Edward Siswanti, Ike Yuni Siti Helmyati Sopian, Sani Moch Sopian, Sani Moch. Sri Desy Siswanti SUGIAN, RENDI TRI Suratman , Fiky Y. Sutejo, Muhammad Fajar Suyoto Suyoto Utomo, Prio Adjie Wiwik Handayani WULANDARI, ESTI FITRIA Wulandari, Ike Yuni Yuniorrita, Seszy