Implementasi Wireless Sensor Network Sebagai Media Komunikasi Data Pada Sistem Monitoring Jarak Jauh
Kata Kunci:
Kata Kunci: Wireless Sensor Network, Monitoring jarak jauh, Delay, Packet Loss, Throughput.Abstrak
Penelitian ini berfokus pada berfokus pada implementasi Wireless Sensor Network (WSN) sebagai media komunikasi menjadi solusi teknologi yang semakin relevan untuk pemantauan jarak jauh karena mampu mengirimkan data real-time tanpa infrastruktur kabel, terutama pada area sulit dijangkau atau berbahaya bagi manusia. Penelitian ini bertujuan menguji performa WSN sebagai media komunikasi data dalam sistem monitoring jarak jauh dengan menilai kualitas transmisi dan efisiensi konsumsi daya pada berbagai kondisi lingkungan. Penelitian ini merupakan studi kuantitatif eksperimental dengan pengujian pada tiga skenario lingkungan berbeda (terbuka, semi-terhalang, dan tertutup beton) selama periode pengiriman data berkala. Parameter yang diukur mencakup delay, packet loss, throughput, akurasi sensor, dan konsumsi daya node. Penelitian menunjukkan bahwa lingkungan sangat memengaruhi performa jaringan, dimana area terbuka menghasilkan delay rata-rata 210 ms, semi-terhalang 287 ms, dan tertutup beton 403 ms, sedangkan packet loss tertinggi terjadi pada area tertutup sebesar 6.4%. Throughput tertinggi tercatat pada area terbuka yaitu 0.245 Mbps. Node relay mengonsumsi daya 46 mAh per jam, lebih tinggi dibanding node biasa. WSN terbukti efektif sebagai media komunikasi data monitoring jarak jauh untuk pengiriman paket kecil meski kinerjanya dipengaruhi kondisi fisik lingkungan. Penelitian lanjutan disarankan mengevaluasi optimasi routing dan sumber energi berbasis terbarukan untuk memperpanjang umur operasional node.
Unduhan
Referensi
REFERENSI
[1] F. P. E. Putra, R. A. Mustafida, and A. Nahriyah, “Perancangan Jaringan Nirkabel Berbasis Mesh untuk Menun-jang Aplikasi Smart City,” 2025, researchgate.net. doi: 10.55606/jitek.v5i1.5934.
[2] F. Prasetyo, E. Putra, F. Muslim, N. Hasanah, R. Paradina, and R. Alim, “Jurnal Sistim Informasi dan Teknologi Analisis Komparasi Protokol Websocket dan MQTT Dalam Proses Push Notification,” vol. 5, pp. 63–72, 2024, doi: 10.60083/jsisfotek.v5i4.325.
[3] F. P. E. Putra, D. E. Arissandi, A. Rofiqi, and M. F. Hidayat, “Pemanfaatan Mikrotik Dalam Manajemen Bandwidth Pada Jaringan Sekolah,” 2025, researchgate.net. doi: 10.31294/evolusi.v7i2.5843.
[4] W. Yang et al., “Precise Wireless Charging in Complicated Environments,” IEEE/ACM Trans. Netw., vol. 32, no. 6, pp. 4944–4959, 2024, doi: 10.1109/TNET.2024.3441113.
[5] J. Xu and P. Shang, “Spectral efficiency and secrecy enhancing scheme for IRS-aided SWIPT systems,” Discov. Appl. Sci., vol. 7, no. 1, 2025, doi: 10.1007/s42452-024-06453-5.
[6] S. Fu, Y. Wang, X. Feng, B. Di, and C. Chunguo, “Reconfigurable Intelligent Surface Assisted Non-Orthogonal Multiple Access Network Based on Machine Learning Approaches,” IEEE Netw., vol. 38, no. 2, pp. 272–279, 2024, doi: 10.1109/MNET.004.2300271.
[7] O. Okporokpo, F. Olajide, N. Ajienka, and X. Ma, “Detection of DDoS Cyberattack Using a Hybrid Trust-Based Technique for Smart Home Networks,” Int. J. Adv. Comput. Sci. Appl., vol. 16, no. 1, pp. 32–41, 2025, doi: 10.14569/IJACSA.2025.0160103.
[8] F. P. E. Putra, N. D. Saputri, F. Rosi, and R. Loati, “Optimalisasi Infrastruktur Cloud Networking melalui Inte-grasi SDN, NFV, dan Multi-Cloud,” 2025, researchgate.net. doi: 10.55606/jitek.v5i1.6099.
[9] F. P. E. Putra, M. Riski, M. S. Yahya, and ..., “Mengenal Teknologi Jaringan Nirkabel Terbaru Teknologi 5G,” J. Sistim Inf. …, 2023, doi: 10.60083/jsisfotek.
[10] F. Prasetyo, E. Putra, F. Iqbal, and N. Muhammad, “Twitter sentiment analysis about economic recession in indonesia,” vol. 7, no. 1, pp. 1–7, 2023, doi: 10.31763/businta.v7i1.592.
[11] V. Kumar et al., “Seamless Wireless Communication Platform for Internet of Things Applications,” IEEE Wirel. Commun., vol. 30, no. 6, pp. 102–110, 2023, doi: 10.1109/MWC.006.2200097.
[12] F. P. E. Putra, M. U. Mansyur, K. Z. Imam, and ..., “Optimalisasi Pengembangan Sistem Informasi Laboratorium Terintegerasi Sistem Akademik Menggunakan Metode Scrumb,” J. …, 2023, doi: 10.30873/ji.v23i2.3749.
[13] N. Soni, M. Kaur, and V. Bhardwaj, “A forensic analysis of AnyDesk Remote Access application by using various forensic tools and techniques,” Forensic Sci. Int. Digit. Investig., vol. 48, 2024, doi: 10.1016/j.fsidi.2024.301695.
[14] M. Anoop, L. W. William Mary, A. J. Wilson, and W. S. Kiran, “Optimized graph transformer with molecule attention network based multi class attack detection framework for enhancing privacy and security in WSN,” Multimed. Tools Appl., vol. 84, no. 15, pp. 14273–14304, 2025, doi: 10.1007/s11042-024-19516-x.
[15] F. P. E. Putra, U. Ubaidi, D. Mayangsari, and ..., “Netvista Public Wireless Network Quality Analysis Using Quality Of Service Parameters,” … Res. Artif. …, 2024, doi: 10.47709/brilliance.v4i1.4388.
[16] W. Chang et al., “Power generation performance of a low frequency hinge beam bistable piezoelectric-electromagnetic composite energy harvester,” Smart Mater. Struct., vol. 34, no. 10, 2025, doi: 10.1088/1361-665X/ae09e1.
[17] H. Lanya, M. Zayyadi, D. R. Anjarani, F. P. E. Putra, and ..., “PEMBERDAYAAN SEKOLAH INKLUSI MELALUI E-MODUL BERJENJANG SEBAGAI PENGEMBANGAN KOMPETENSI GURU DALAM PEMENUHAN ….” doi: 10.37303/peduli.v8i2.681.
[18] F. P. E. Putra, U. Ubaidi, M. A. Huda, and ..., “Computer network management optimization through big data analysis using time series analysis method,” Brill. Res. …, 2024, doi: 10.47709/brilliance.v4i1.4373.
[19] J. Choi, J. Choi, H. Joe, and C. Jung, “Caphammer: Exploiting Capacitor Vulnerability of Energy Harvesting Systems,” IEEE Trans. Comput. Des. Integr. Circuits Syst., vol. 43, no. 11, pp. 3804–3815, 2024, doi: 10.1109/TCAD.2024.3446879.
[20] U. B. Chaudhry and C. I. Phillips, “Smart data harvesting in cache-enabled MANETs: UAVs, future position prediction, and autonomous path planning,” Drone Syst. Appl., vol. 12, no. 1, pp. 1–15, 2024, doi: 10.1139/dsa-2024-0003.
[21] S. Batewela, M. Liyanage, E. Zeydan, M. Ylianttila, and P. Ranaweera, “Security Orchestration in 5G and Beyond Smart Network Technologies,” IEEE Open J. Comput. Soc., vol. 6, pp. 554–573, 2025, doi: 10.1109/OJCS.2025.3563619.
[22] M. Merluzzi et al., “The Hexa-X Project Vision on Artificial Intelligence and Machine Learning-Driven Communication and Computation Co-Design for 6G,” IEEE Access, vol. 11, pp. 65620–65648, 2023, doi: 10.1109/ACCESS.2023.3287939.
[23] S. G. Ghasemi, M. E. Cholette, G. S. Larue, A. Rakotonirainy, and S. Glaser, “Energy Efficient and Safe Control Strategy for Electric Vehicles including Driver Preference,” IEEE Access, vol. 9, pp. 11109–11122, 2021, doi: 10.1109/ACCESS.2021.3050780.
[24] K. Uribe-Murcia, O. G. Ibarra-Manzano, J. A. Andrade Lucio, and Y. S. Shmaliy, “Moving Vehicle Tracking Under Measurement Uncertainties, Multi-Step Random Delays, and Packet Dropouts,” IEEE Access, vol. 11, pp. 52381–52391, 2023, doi: 10.1109/ACCESS.2023.3280858.
[25] A. Israr, Q. Yang, and A. Israr, “Renewable microgeneration cooperation with base station sleeping-mode strategy for energy-efficient operation of 5G infrastructures,” Sustain. Energy, Grids Networks, vol. 38, 2024, doi: 10.1016/j.segan.2024.101358.
[26] G. Kaur and M. Bhattacharya, “Green Fault Tolerant AIoT-Enabled Mobile Sink Data Collection Scheme in Sensor Networks,” IEEE Trans. Veh. Technol., vol. 73, no. 10, pp. 15385–15394, 2024, doi: 10.1109/TVT.2024.3400880.
[27] S. Rezwan and W. Choi, “Priority-Based Joint Resource Allocation with Deep Q-Learning for Heterogeneous NOMA Systems,” IEEE Access, vol. 9, pp. 41468–41481, 2021, doi: 10.1109/ACCESS.2021.3065314.
[28] A. M. Telgote and S. S. Mande, “A power-awareness routing protocol for sustainable low-power wireless networks: FPGA vs. microcontroller implementation,” Int. J. Ad Hoc Ubiquitous Comput., vol. 48, no. 2, pp. 75–93, 2025, doi: 10.1504/IJAHUC.2025.143974.
[29] J. S. More, V. V Sarbhukan, and R. Lokare, “Reinforcement Learning-Based AI-Powered Adaptive Routing Protocols for Urban VANETs,” Int. J. Comput. Networks Appl., vol. 12, no. 4, pp. 538–553, 2025, doi: 10.22247/ijcna/2025/33.
[30] N. Ruzibaeva et al., “Application of Wireless Sensors in the Design of Smart Learning of the English Language Utilizing Zigbee Network Technology,” J. Wirel. Mob. Networks, Ubiquitous Comput. Dependable Appl., vol. 15, no. 3, pp. 125–135, 2024, doi: 10.58346/JOWUA.2024.I3.009.
[31] V. L. Tran, S. Bouro, M. T. Nguyen, and F. Ferrerò, “A Novel Localization Technique in LoRa-Based Low-Power Relay Using Machine Learning,” IEEE Internet Things J., vol. 12, no. 1, pp. 297–308, 2025, doi: 10.1109/JIOT.2024.3459874.
[32] A. N. Padmasali, J. Lokesh, and S. G. Kini, “An Experimental Investigation on the Role of LEDs on the Lifetime Performance of Consumer LED Luminaires,” IEEE Access, vol. 10, pp. 131765–131771, 2022, doi: 10.1109/ACCESS.2022.3230474.
[33] B. B. Komecoglu and B. Yilmaz, “Event Graph-Based News Clustering: The Role of Named Entity-Centered Subgraphs,” IEEE Access, vol. 12, pp. 105613–105632, 2024, doi: 10.1109/ACCESS.2024.3435343.
[34] F. Fernando Jurado-Lasso, J. F. Jurado, and X. Fafoutis, “LEACH-RLC: Enhancing IoT Data Transmission With Optimized Clustering and Reinforcement Learning,” IEEE Internet Things J., vol. 12, no. 13, pp. 23462–23478, 2025, doi: 10.1109/JIOT.2025.3552126.
[35] R. K. Jain, A. Mukherjee, P. Karmakar, A. Banerjee, H. Akbarov, and S. Hasanov, “Experimental performance of soil monitoring system using IoT technique for automatic drip irrigation,” Int. J. Commun. Syst., vol. 36, no. 18, 2023, doi: 10.1002/dac.5617.
[36] Z. Wang, N. Dong, J. Sun, W. Knottenbelt, and Y. Guo, “ZkFL :Zero-Knowledge Proof-Based Gradient Aggregation for Federated Learning,” IEEE Trans. Big Data, vol. 11, no. 2, pp. 447–460, 2025, doi: 10.1109/TBDATA.2024.3403370.
[37] W. Zhang, R. Shang, Z. Li, R. Sun, and J. Du, “Personalized Web Page Ranking Based Graph Convolutional Network for Community Detection in Attribute Networks,” IEEE Access, vol. 11, pp. 84270–84282, 2023, doi: 10.1109/ACCESS.2023.3303210.
[38] G. Dosymbetova et al., “Neural Network-Based Active Cooling System With IoT Monitoring and Control for LCPV Silicon Solar Cells,” IEEE Access, vol. 11, pp. 52585–52602, 2023, doi: 10.1109/ACCESS.2023.3280265.
[39] J. Song, X. Liao, and J. Qiao, “A Graph Convolutional Network-Based Method for Congested Link Identification,” Appl. Sci., vol. 14, no. 20, 2024, doi: 10.3390/app14209164.
[40] T. Maiwald et al., “A Review of Integrated Systems and Components for 6G Wireless Communication in the D-Band,” Proc. IEEE, vol. 111, no. 3, pp. 220–256, 2023, doi: 10.1109/JPROC.2023.3240127.
[41] J. Debadarshini, M. H. Manish Kausik, and S. Saha, “Structure-Adaptive Many-to-Many Data-Sharing for Internet-of-Things,” IEEE Trans. Netw. Serv. Manag., vol. 21, no. 3, pp. 2596–2607, 2024, doi: 10.1109/TNSM.2024.3376371.
[42] S. Aanjankumar et al., “Enhanced Consumer Healthcare Data Protection Through AI-Driven TinyML and Privacy-Preserving Techniques,” IEEE Access, vol. 13, pp. 97428–97440, 2025, doi: 10.1109/ACCESS.2025.3573076.
[43] F. P. E. Putra, D. T. Agustina, T. S. K. Khotimah, and T. Ramadhanty, “Analisis Kinerja Jaringan 5G dalam Meningkatkan Konektivi-tas Internet of Things (IoT),” 2025, researchgate.net. doi: 10.55606/jitek.v5i1.5836.
[44] M. Hashemi, S. Mohammadi, and T. E. Carlson, “TOP: A Combined Logical and Physical Obfuscation Method for Securing Networks-on-Chip Against Reverse Engineering Attacks,” IEEE Access, vol. 13, pp. 133438–133456, 2025, doi: 10.1109/ACCESS.2025.3590967.
[45] M. Kinnas, J. Violos, N. I. Karapiperis, and I. Kompatsiaris, “Selecting Images With Entropy for Frugal Knowledge Distillation,” IEEE Access, vol. 13, pp. 28189–28203, 2025, doi: 10.1109/ACCESS.2025.3540384.
[46] J. J. Pyrhon̈en et al., “Design of a High-Specific-Power Traction Motor: Innovations and Strategies for Superior Performance,” IEEE Access, vol. 13, pp. 125659–125675, 2025, doi: 10.1109/ACCESS.2025.3589939.
[47] P. Spadaccino, D. Garlisi, A. Franceschi, I. Tinnirello, and F. Cuomo, “Accelerating Network Resource Allocation in LoRaWAN via Distributed Big Data Computing,” IEEE Access, vol. 12, pp. 141237–141250, 2024, doi: 10.1109/ACCESS.2024.3465634.
[48] R. Noormohammadi, A. Khaleghi, and I. Balasingham, “Analog Backscatter Video Transmission for Wireless Capsule Endoscope,” IEEE Access, vol. 11, pp. 18542–18550, 2023, doi: 10.1109/ACCESS.2023.3248019.
[49] G. Cretu, I. Stamatescu, and G. Stamatescu, “Modeling and Prediction of Occupancy in Buildings Based on Sensor Data Using Deep Learning Methods,” IEEE Access, vol. 12, pp. 102994–103003, 2024, doi: 10.1109/ACCESS.2024.3432584.
[50] D. Seo, K. Nam, and K. Jung, “RL-MAB-Based Resource Allocation for Efficient Bandwidth Utilization in Industrial IoT Networks,” IEEE Access, vol. 13, pp. 83394–83407, 2025, doi: 10.1109/ACCESS.2025.3560855.
[51] S. Khan et al., “Hybrid computing framework security in dynamic offloading for IoT-enabled smart home system,” PeerJ Comput. Sci., vol. 10, 2024, doi: 10.7717/PEERJ-CS.2211.
Diterbitkan
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2026 Mohammad Faruq, Ahmad Hamdani (Penulis)

Artikel ini berlisensi Creative Commons Attribution 4.0 International License.








