Evaluasi Akurasi Sensor Ultrasonik dan Latensi Notifikasi Blynk pada Prototipe Sistem Pemantauan Banjir Berbasis IoT
DOI:
https://doi.org/10.58344/locus.v5i7.5921Keywords:
Internet of Things, Pemantauan banjir, HC-SR04, Latency, Akurasi sensorAbstract
Keterlambatan penyampaian informasi mengenai peningkatan muka air dapat memperbesar risiko kerusakan serta mengurangi efektivitas tindakan mitigasi banjir. Kondisi tersebut mendorong kebutuhan terhadap sistem pemantauan yang mampu melakukan pengukuran dan distribusi informasi secara cepat serta berkesinambungan. Penelitian ini bertujuan mengevaluasi performa sistem pemantauan banjir berbasis Internet of Things (IoT) dengan memanfaatkan sensor ultrasonik HC-SR04, NodeMCU ESP8266, dan platform Blynk melalui pendekatan evaluasi terpadu antara akurasi pengukuran dan performa komunikasi data. Pengujian dilakukan pada tiga variasi level air, yaitu 5 cm, 10 cm, dan 15 cm dengan sepuluh kali pengulangan pada setiap level pengukuran. Evaluasi akurasi sensor dianalisis menggunakan Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), standar deviasi, dan coefficient of variation (CV), sedangkan performa komunikasi dianalisis berdasarkan mean latency, p95 latency, standar deviasi, dan confidence interval 95% pada kondisi RSSI kuat dan RSSI sedang. Hasil eksperimen menunjukkan bahwa sistem mampu mempertahankan performa pengukuran yang stabil dengan nilai MAE sebesar 0.029–0.039 cm dan nilai MAPE di bawah 1%. Pada pengujian komunikasi, rata-rata latency tercatat sebesar 0.968 detik pada kondisi RSSI kuat dan 1.925 detik pada kondisi RSSI sedang. Temuan tersebut menunjukkan bahwa kualitas jaringan memberikan pengaruh langsung terhadap kestabilan komunikasi pada sistem IoT berbasis cloud. Kontribusi penelitian ini terletak pada penyusunan kerangka evaluasi empiris yang mengintegrasikan analisis akurasi sensor dan latency komunikasi dalam satu skenario pengujian sistem pemantauan banjir berbasis IoT berbiaya rendah. Secara keseluruhan, sistem yang dikembangkan menunjukkan performa yang memadai untuk kebutuhan monitoring level air secara real-time pada skala prototipe.
References
Alhartomi, M. A., Salh, A., Audah, L., Alzahrani, S., Alzahmi, A., Altimania, M. R., Alotaibi, A., Alsulami, R., & Al-Hartomy, O. (2023). Sustainable resource allocation and reduce latency based on federated-learning-enabled digital twin in IoT devices. Sensors, 23(16), 7262.
AlZubi, A. A., & Galyna, K. (2023). Artificial intelligence and Internet of Things for sustainable farming and smart agriculture. IEEE Access, 11, 78686–78692. https://doi.org/10.1109/ACCESS.2023.3298215
Arante, H. R. C., Sybingco, E., Roque, M. A., Ambata, L., Chua, A., & Gutierrez, A. N. (2025). Development of a secured IoT-based flood monitoring and forecasting system using genetic-algorithm-based neuro-fuzzy network. Sensors, 25(13), 3885. https://doi.org/10.3390/s25133885
Biswas, J., Haid, M., Bhalerao, A., Engelhardt, S., & Lemke, S. (2025). WaDA – Water diplomacy automation: Using blockchain, AI, and environment IoT for water management and climate action. Journal of Sensors and Sensor Systems, 14, 187–196. https://doi.org/10.5194/jsss-14-187-2025
Borankulova, G., Altybayev, G., Tungatarova, A., Yeraliyeva, B., Dulatbayeva, S., Murzakhmetov, A., & Bekbolatov, S. (2025). Development of real-time water-level monitoring system for agriculture. Sensors, 25(17), 5564. https://doi.org/10.3390/s25175564
Bresnahan, P., Briggs, E., Davis, B., Rodriguez, A. R., Edwards, L., Peach, C., Renner, N., Helling, H., & Merrifield, M. (2023). A low-cost, DIY ultrasonic water level sensor for education, citizen science, and research. Oceanography, 36(1), 51–58. https://www.jstor.org/stable/27200038
Chen, S.-L., Chou, H.-S., Huang, C.-H., Chen, C.-Y., Li, L.-Y., Huang, C.-H., Chen, Y.-Y., Tang, J.-H., Chang, W.-H., & Huang, J.-S. (2023). An intelligent water monitoring IoT system for ecological environment and smart cities. Sensors, 23(20), 8540. https://doi.org/10.3390/s23208540
Choosumrong, S., Piyathamrongchai, K., Hataitara, R., Soteyome, U., Konkong, N., Chalongsuppunyoo, R., Raghavan, V., & Nemoto, T. (2025). Development of an IoT-based flood monitoring system integrated with GIS for lowland agricultural areas. Sensors, 25(17), 5477. https://doi.org/10.3390/s25175477
Darma Kotama, I. N., Funabiki, N., Kyaw, H. H. S., Pradhana, A. A. S., & Batubulan, K. S. (2025). Accuracy investigation of RAG-based sensor setup assistance in SEMAR IoT platform using generative AI. In Proceedings of the 30th Asia-Pacific Conference on Communications (APCC) (pp. 1–6). IEEE. https://doi.org/10.23919/APCC64555.2025.11279817
Fadilah, R., Ruslan, R., & Imran, A. (2024). Development of Internet of Things (IoT)-based flood early warning tools. Journal of Electrical Engineering and Informatics, 1(2), 45–52. https://doi.org/10.59562/jeeni.v1i2.1508
Guerrero-Ulloa, G., Rodríguez-Domínguez, C., & Hornos, M. J. (2023). Agile methodologies applied to the development of Internet of Things (IoT)-based systems: A review. Sensors, 23(2), 790. https://doi.org/10.3390/s23020790
Hasanah, A. P., Sarif, M. I., & Hafni, H. (2025). Perancangan sistem monitoring level air menggunakan sensor ultrasonik berbasis IoT dengan aplikasi Blynk. Jurnal Informatika dan Teknik Elektro Terapan, 13(2). https://doi.org/10.23960/jitet.v13i2.6485
Iqbal, M., Rosadi, A., & Andana, E. K. (2024). Perancangan sistem IoT untuk deteksi dini banjir berbasis sensor water level menggunakan platform Blynk. Computing Insight: Journal of Computer Science, 4(1), 18–28. https://doi.org/10.30651/comp_insight.v4i1.21762
Islam, S., Klupka, S., Mohammadi, R., Jin, Y.-F., & Xie, M. (2024). Deep learning based IoT system for real-time traffic risk notifications. In Proceedings of the 25th International Symposium on Quality Electronic Design (ISQED) (pp. 1–6). IEEE. https://doi.org/10.1109/ISQED60706.2024.10528772
Khakim, L., & Budihartono, E. (2025). Performance analysis of HC-SR04 and JSN-SRT04T sensors for optimization of microcontroller-based septic tank volume monitoring tools. International Journal of Science, Technology & Management, 6(3), 553–560. https://doi.org/10.46729/ijstm.v6i3.1317
Khan, M. A., Nawaz, T., Khan, U. S., Hamza, A., & Rashid, N. (2023). IoT-based non-intrusive automated driver drowsiness monitoring framework for logistics and public transport applications to enhance road safety. IEEE Access, 11, 14385–14397. https://doi.org/10.1109/ACCESS.2023.3244008
Kusuma, A., Prasita, V. D., & Tambun, R. (2025). IoT-based real-time tide monitoring tool: Design and case study at Kenjeran Beach, Surabaya. Transactions on Maritime Science, 14(1). https://doi.org/10.7225/toms.v14.n01.010
Lengkong, A. G., Salaki, D. T., & Alfonsius, E. (2025). Implementation of an Internet of Things (IoT)-based water level early warning system with Telegram notification. Jurnal Informatika dan Rekayasa Perangkat Lunak, 6(2), 196–207. https://doi.org/10.33365/jatika.v6i2.349
Pereira, T. S. R., de Carvalho, T. P., Mendes, T. A., & Formiga, K. T. M. (2022). Evaluation of water level in flowing channels using ultrasonic sensors. Sustainability, 14(9). https://doi.org/10.3390/su14095512
Ratmini, Y., Atina, V., & Purwanto, E. (2025). Flood monitoring and early-warning system based on the Internet of Things (IoT). Jurnal Ilmiah Teknologi Informasi Asia, 19(1), 1–7. https://doi.org/10.32815/jitika.v19i1.1103
Susila, P., Firdaus, I. N., Chuzairi, M. F., & Rahmawati, D. (2025). Flood early warning system prototype based on ultrasonic sensor and Internet of Things. Jurnal Rekayasa Elektrika, 19(3), 100–106. https://doi.org/10.17529/jre.v19i3.33147
Syamsi, N., Ulfah, M., & Lesmideyarti, D. (2024). Water level monitoring for flood early mitigation based on Internet of Things (IoT). TEPIAN, 5(2), 58–64. https://doi.org/10.51967/tepian.v5i2.2504
Vishwanatha, M., Selvam, K., Saeidi, N., Wiemer, M., & Kuhn, H. (2025). Underwater object detection using capacitive micromachined ultrasonic transducers (CMUTs). Journal of Sensors and Sensor Systems, 14, 285–296. https://doi.org/10.5194/jsss-14-285-2025
Wandi, N. U. A., & Ashari, A. (2025). Monitoring ketinggian air dan curah hujan dalam early warning system bencana banjir berbasis IoT. Indonesian Journal of Electronics and Instrumentation Systems. https://doi.org/10.22146/ijeis.83569
Zhang, H., Zhang, R., & Sun, J. (2025). Developing real-time IoT-based public safety alert and emergency response systems. Scientific Reports, 15(1), Article 29056. https://doi.org/10.1038/s41598-025-13465-7
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Gunawan Prayitno, Aprilia Anes Sarira

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International (CC-BY-SA). that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.




