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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) ELKHA : Jurnal Teknik Elektro Jurnal EECCIS SITEKIN: Jurnal Sains, Teknologi dan Industri ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer JOIV : International Journal on Informatics Visualization JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Multitek Indonesia : Jurnal Ilmiah TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Jurnal Pengabdian Masyarakat Borneo Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) IJITEE (International Journal of Information Technology and Electrical Engineering) Indonesian Journal of Electrical Engineering and Computer Science Elektrika Borneo JESCEE- Journal of Emerging Supply Chain, Clean Energy, and Process Engineering Jurnal INFOTEL Jurnal Elektronika dan Telekomunikasi Jurnal Rekayasa elektrika
Syahfrizal Tahcfulloh
Universitas Borneo Tarakan
Aerospace Engineering Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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Enhanced Angular Resolution in OEST Radar Using Hybrid APES-MUSIC Algorithm RANDI RAMDANSYAH; SYAHFRIZAL TAHCFULLOH; DWI RISKY; NUR SAFARIA; ILHAM TIARA PUTRA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 4: Published November 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i4.369

Abstract

Limited angular resolution in Overlapped Equal Subarray Transmit (OEST) radar poses a critical challenge in detecting closely spaced targets, especially in complex multi-target environments. This paper evaluates super-resolution MUSIC and APES methods to enhance angular resolution in OEST radar systems with 6 subarrays. Performance analysis was conducted under single and multiple target scenarios: one target at 0.5°, two targets at [0°, 0.5°], and three targets at [–0.5°, 0°, 0.5°]. Both methods achieved accurate angle detection for single and dual-target cases. However, in triple-target scenarios, APES demonstrated superior DoA and RCS estimation precision (up to 0.999) despite higher sidelobes, whereas MUSIC showed reduced RCS accuracy but lower sidelobes. The hybrid APES-MUSIC approach produced sharp spectral peaks, near-unity amplitude response, and minimized sidelobe interference, significantly improving estimation accuracy and stability for this radar in dense multi-target settings.
Combined Barker-M-Sequence Coded LFM for High-Performance Subarray-MIMO Radar Applications Akhmad Iqbal; Syahfrizal Tahcfulloh; Antonius Antonius; Rizkyandi Juliannanda; Arya Nurrahmansyah
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 2 (2026): Issues January 2026
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i2.15837

Abstract

Subarray-Multiple-Input Multiple-Output (SMIMO) radar is an advanced technology that integrates the advantages of phased-array and MIMO radars to enhance target detection resolution. A key challenge in SMIMO implementation lies in improving velocity resolution without compromising spectral efficiency, while maintaining accurate target detection capability under high sidelobe levels and inter-channel interference. This study proposes a novel approach—Combined Barker-M-Sequence Coded LFM—in which the LFM signal is phase-modulated using a hybrid code formed by concatenating a Barker sequence (length 11) and an M-sequence (length 7). Simulation results show that the proposed signal achieves a Peak Sidelobe Ratio (PSLR) of −20.83 dB, significantly outperforming LFM-Barker (−8.45 dB) and LFM-M-sequence (−16.3 dB). It also delivers a velocity resolution of 0.95 m/s and a range resolution of 225 m, representing a 38% improvement over standard LFM. Moreover, under SNR = −5 dB, the system achieves a SINR gain of 4.7 dB relative to LFM-M-sequence. This approach enables more efficient waveform utilization in modern radar applications—such as air surveillance, military defense, and autonomous vehicles—particularly in challenging environments characterized by low SNR, multipath propagation, and high clutter.
Adaptive Low-Power LoRa WSN for Real-Time Soil Monitoring in Remote Oil Palm Plantations Tahcfulloh, Syahfrizal; Rattu, Michael Yehezkiel; Wahyuni, Etty; Kusuma, Irawan Wijaya; HM, Irawati; Santoso, Dwi; Arif, Nina Fapari; Fatwa, Nur; Setiawan, Rusdy; Arwan, Arwan
ELKHA Vol. 18 No.1 April 2026
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v18i1.100568

Abstract

Oil palm plantations in remote regions such as Sebatik, North Kalimantan, face significant challenges in sustainable soil management due to limited infrastructure and dynamic peat soil conditions. Conventional monitoring methods lack real-time capability and energy efficiency. To address this, this research proposes a novel adaptive low-power LoRa-based Wireless Sensor Network (WSN) that dynamically adjusts sensing and transmission frequency based on real-time soil parameters—specifically, moisture, temperature, and pH. Unlike fixed-interval systems, the proposed architecture implements edge-based logic on ESP32 nodes to escalate sampling during critical events (e.g., pH ≤ 4.5) and reduce activity during stable periods, optimizing energy use without cloud dependency. The system integrates LoRa SX1278 modules, a RAK2245 gateway, ChirpStack for secure data routing, and OpenRemote for visualization and alerts. Field testing over 7 days in three micro-zones (roadside, plantation center, drainage) demonstrated robust performance with average Packet Delivery Ratios of 97.2%, 82.5%, and 88.3%, respectively, and a communication range of up to 2.8 km. Crucially, the adaptive strategy reduced daily power consumption to 7.8 mAh—58% lower than a fixed 10-minute schedule—extending theoretical battery life from 6–8 months to over 14 months. Sensor accuracy remained high (moisture error: 1.68%; temperature: 3.09%; pH: 1.47 units), enabling timely agronomic interventions such as targeted liming. This work contributes an environment-responsive WSN architecture that balances energy efficiency and event responsiveness, offering a scalable, deployable model for precision agriculture in tropical peripheral regions with acidic soils and intermittent connectivity.
Optimization of Wireless Sensor Network Node Placement in Oil Palm Plantations using Particle Swarm Optimization for Improved Path Loss Prediction Syahfrizal Tahcfulloh; Etty Wahyuni; Dwi Santoso; Tri Noviyansyah
Jurnal Rekayasa Elektrika Vol. 21 No. 4 (2025): Vol. 21, No. 4, December 2025
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i4.756

Abstract

This study proposes a data-driven framework for optimizing Wireless Sensor Network (WSN) node placement in oil palm plantations on Sebatik Island, Indonesia, by integrating site-specific path loss modeling with a modified Particle Swarm Optimization (PSO) algorithm. Field measurements across 120 transmitter-receiver pairs at 433 MHz revealed that conventional log-distance models poorly predict signal attenuation in dense vegetation (R² < 0.35, RMSE > 8 dB), while calibrated quadratic and cubic polynomial models achieved high accuracy (R² up to 0.9857, RMSE as low as 1.12 dB). These empirical models were embedded into the PSO fitness function to optimize spatial deployment of 20 nodes over a 500 m × 800 m area. The optimized layout achieved 94.7% coverage, 98% connectivity, 42% energy savings over random placement, and 95.6% Packet Delivery Ratio (PDR). Validation against independent field data confirmed robust prediction accuracy (RMSE = 4.3 dB), significantly outperforming generic models like ITU-R. This approach demonstrates that vegetation-aware, empirically calibrated modeling combined with metaheuristic optimization substantially enhances WSN performance in tropical agro-forestry environments, offering a scalable solution for smart agriculture in remote, ecologically complex regions.
Co-Authors Abadi, Aji Bijaksana Abdul Muis Prasetia, Abdul Muis Akhmad Iqbal Antonius Antonius Antonius Antonius Arif, Nina Fapari Arwan Arwan Arya Nurrahmansyah Ashar Ashar Budiman, Achmad DWI RISKY Dwi santoso DWI SANTOSO Eka Riskayadi Etty Wahyuni Huda, Abil ILHAM TIARA PUTRA Irawan Wijaya Kusuma, Irawan Wijaya Irawati HM Kristianto Pasepang Mado, Ismit Mizar Ahmad Maulana Muhammad Jeki Muttaqin Hardiwansyah Nur Fatwa, Nur NUR SAFARIA Patria Julianto Petrick Petrick RANDI RAMDANSYAH Rattu, Michael Yehezkiel Rizkyandi Juliannanda Rusdy Setiawan Sabaria, Sabaria Said, Fitriani Sapriansa Sapriansa Sartika, Linda Selviyani, Selviyani Sugeng Riyanto Sultan Mahdi Sumardi . Syamsiar, Syamsiar Tri Noviyansyah Tri Noviyansyah