Penerapan Sistem Irigasi Tetes Otomatis Berbasis Sensor Kelembaban Tanah: Upaya Pertanian Presisi pada Tanaman Semangka
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Penelitian ini bertujuan untuk menganalisis penerapan sistem irigasi tetes otomatis berbasis sensor kelembaban tanah dalam mendukung pertanian presisi pada budidaya tanaman semangka. Metode yang digunakan adalah narrative literature review dengan mengkaji berbagai sumber ilmiah yang relevan, meliputi jurnal internasional bereputasi, jurnal nasional terakreditasi, serta prosiding ilmiah. Hasil kajian menunjukkan bahwa sistem irigasi tetes berbasis sensor mampu meningkatkan efisiensi penggunaan air hingga 30–80% dibandingkan metode konvensional, karena proses penyiraman dilakukan secara real-time sesuai kondisi aktual kelembaban tanah. Selain itu, teknologi ini mampu menjaga stabilitas kelembaban tanah sehingga berdampak positif terhadap pertumbuhan tanaman, kualitas buah, serta produktivitas hasil panen. Integrasi teknologi sensor, Internet of Things (IoT), dan sistem otomatisasi juga memberikan kemudahan dalam monitoring dan pengelolaan irigasi secara lebih akurat dan efisien. Namun demikian, kajian ini masih memiliki keterbatasan karena bergantung pada data sekunder serta belum didukung oleh pengujian empiris langsung di lapangan. Di sisi lain, implementasi teknologi ini juga menghadapi kendala seperti biaya investasi awal, kebutuhan infrastruktur, serta keterbatasan kapasitas teknis pengguna. Dengan demikian, meskipun penerapan sistem ini berpotensi menjadi solusi strategis dalam menghadapi keterbatasan sumberdaya air dan mendukung pertanian berkelanjutan berbasis teknologi, diperlukan kajian lanjutan untuk memperkuat validasi dan penerapannya di berbagai kondisi lapangan.
Implementation of an Automatic Drip Irrigation System Based on Soil Moisture Sensors: a Precision Agriculture Effort for Watermelon Plants
Abstract
This article aims to analyze the application of an automatic drip irrigation system based on soil moisture sensors to support precision agriculture in watermelon cultivation. The method used is a narrative literature review by examining various relevant scientific sources, including reputable international journals, accredited national journals, and scientific proceedings. The results of the study indicate that the sensor-based drip irrigation system can increase water use efficiency by 30–80% compared to conventional methods, because the watering process is carried out in real time according to actual soil moisture conditions. In addition, this technology is able to maintain soil moisture stability, thus positively impacting plant growth, fruit quality, and crop productivity. The integration of sensor technology, the Internet of Things (IoT), and automation systems also facilitates more accurate and efficient irrigation monitoring and management. However, this study still has limitations because it relies on secondary data and is not supported by direct empirical testing in the field. Furthermore, the implementation of this technology also faces obstacles such as initial investment costs, infrastructure requirements, and limited user technical capacity. Therefore, although the implementation of this system has the potential to be a strategic solution to address limited water resources and support technology-based sustainable agriculture, further studies are needed to strengthen its validation and application in various field conditions.
Abdelmoneim, A. A., Al Kalaany, C. M., Dragonetti, G., & Derardja, B. (2025). Comparative analysis of soil moisture- and weather-based irrigation scheduling for drip-irrigated lettuce using low-cost Internet of Things capacitive sensors.
Ali, A., Hussain, T., & Zahid, A. (2025). Smart irrigation technologies and prospects for enhancing water use efficiency for sustainable agriculture.
Ardiansyah, H., Shodiq, M., Mahbubillah, M. A., & Agustina, R. (2025). Optimasi durasi pada sistem irigasi tetes dengan sensor kelembaban dan suhu tanah menggunakan logika fuzzy Takagi-Sugeno. Techné: Jurnal Ilmiah Elektroteknika, 24(1), 73–88.
Aswat, A., Hayati, P. K. D., Sutoyo, Warnita, & Kuswandi. (2025). Penampilan morfologi tanaman semangka (Citrullus lanatus Thunb.). Jurnal Agroteknologi Universitas Andalas, 7(1), 57–66. https://doi.org/10.25077/jagur.7.1.57-66.2025
Azahra, M., & Styawati, S. (2024). Drip irrigation technology for watermelon crops with IoT-based solar panels for efficient use of energy resources. IC-ITECHS Journal, 5(1).
Bao, L., Zhang, S., Liang, X., Wang, P., Guo, Y., & Sun, Q. (2023). Intelligent drip fertigation increases water and nutrient use efficiency of watermelon in greenhouse without compromising the yield. Agricultural Water Management, 282, 108278. https://doi.org/10.1016/j.agwat.2023.108278
Bathula, R., Uma Devi, M., Madhavi, A., Kumar, A., Akula, B., & Triveni. (2024). Influence of fertigation levels and drip irrigation on yield and quality of summer watermelon. Journal of Experimental Agriculture International, 46(12), 75–86. https://doi.org/10.9734/jeai/2024/v46i123113
Chanafi, M., Sudarmana, L., & Syahruddin, F. (2023). Rancang bangun sistem penyiraman otomatis menggunakan sensor kelembaban tanah pada tanaman seledri berbasis NodeMCU ESP8266. Teknomatika: Jurnal Informatika dan Komputer, 13(2), 52–62. https://doi.org/10.30989/teknomatika.v13i2.1136
Datta, P., & Behera, B. (2022). Assessment of adaptive capacity and adaptation to climate change in the farming households of Eastern Himalayan foothills of West Bengal, India. Environmental Challenges, 7, 100462. https://doi.org/10.1016/j.envc.2022.100462
Fadillah, S., Siagian, C. P., Afifah, R., Sani, A. Y. H., & Junaidi, J. (2025). Pemanfaatan sensor kelembaban tanah untuk mengendalikan gerbang otomatis pada sistem irigasi cerdas. JULIKOM: Jurnal Ilmu Komputer, 1(2), 89–95.
Food and Agriculture Organization of the United Nations. (2021). Systems at breaking point.
Guo, H., & Li, S. (2024). A review of drip irrigation’s effect on water, carbon fluxes, and [title incomplete].
Hasan, H., Sutjiningtyas, S., Rachmanto, A. D., Supriyadi, S., & Sidik, F. N. (2026a). Penyiraman tanaman otomatis berbasis NodeMCU dan IoT menggunakan sensor kelembapan tanah. Jurnal Sains Informatika Terapan, 8(1), 45–53.
Hasan, H., Sutjiningtyas, S., Rachmanto, A. D., Supriyadi, S., & Sidik, F. N. (2026b). Penyiraman otomatis berbasis sensor kelembapan tanah untuk efisiensi penggunaan air pada tanaman hortikultura. Jurnal Teknologi Pertanian Indonesia, 18(1), 45–56.
Kamagi, D., Rumambi, D. P., & Kalesaran, L. H. (2023). Rancang bangun sistem kontrol otomatis sensor kelembaban tanah pada media tanam polybag. COCOS, 15(2). https://doi.org/10.35791/cocos.v15i2.47511
Kingslin, S., & Vaishnavi, K. (2025). A comprehensive survey on IoT-based smart irrigation in agriculture. International Journal of Research and Scientific Innovation (IJRSI).
Kumar, R., Singh, A., & Patel, N. (2022). Drip irrigation management for improving water use efficiency in horticultural crops. Agricultural Water Management, 261, 107358. https://doi.org/10.1016/j.agwat.2021.107358
L, S., S, J., & P, S. (2024). Nutrient dynamics and moisture distribution under drip irrigation system. [Journal title unavailable], 46(10), 485–493.
Leiva Soto, A. (2024). Evaluation of irrigation systems for watermelon production. Agronomy Journal. https://acsess.onlinelibrary.wiley.com/doi/10.1002/agj2.21653
Lestari, S., Ramadhan, T. F., Hardiyanto, A., & Pramono, P. (2025). Sistem irigasi otomatis berbasis sensor kelembaban tanah pada tanaman cabai menggunakan ESP32. Prosiding Seminar Nasional Teknologi Informasi dan Bisnis, 1154–1158. https://doi.org/10.47701/rcryjz73
Li, H., Mei, X., Wang, J., Huang, F., Hao, W., & Li, B. (2021). Drip fertigation significantly increased crop yield, water productivity and nitrogen use efficiency. Agricultural Water Management, 244, 106534. https://doi.org/10.1016/j.agwat.2020.106534
Liang, Z. (2020). Water allocation and integrative management of precision irrigation. Water, 12(11), 3135. https://www.mdpi.com/2073-4441/12/11/3135
Liu, Z. (2025). Optimizing water use efficiency in watermelon. Frontiers in Plant Science. https://www.frontiersin.org/articles/10.3389/fpls.2025.1662575/full
Luo, P., Chen, R., Yang, J., & Javed, T. (2026). Enhancing soil structure and water dynamics through long-term mulched drip irrigation. International Soil and Water Conservation Research, 14(1), 100564. https://doi.org/10.1016/j.iswcr.2025.08.007
Miller, L., & Vellidis, G. (2018). Soil moisture-based irrigation in watermelon. HortTechnology, 28(3), 362. https://journals.ashs.org/view/journals/horttech/28/3/article-p362.xml
Mursalin, S. B., Sunardi, H., & Zulkifli, Z. (2020). Sistem penyiraman tanaman otomatis berbasis sensor kelembaban tanah menggunakan logika fuzzy. Jurnal Ilmiah Informatika Global, 11(1), 47–54. https://doi.org/10.36982/jiig.v11i1.1072
Nanda, A. P., Jeprianto, J., & Mahdi, M. I. (2024). Sistem otomatis penyiraman tanaman berbasis sensor kelembapan tanah untuk peningkatan produktivitas pertanian. Technologia: Jurnal Ilmiah, 15(4), 764–772. https://doi.org/10.31602/tji.v15i4.16300
Neilson, J. A. D., Smith, A. M., Mesina, L., Vivian, R., Smienk, S., & De Koyer, D. (2021). Potato tuber shape phenotyping using RGB imaging. [Journal title unavailable], 1–14.
Pramana, R., Pinandito, A. M., Septiana, T., & Syamsudin, M. S. (2025). Analisis dampak dan tantangan pemanfaatan sensor kelembaban tanah dalam sistem irigasi otomatis berbasis IoT. Qomaruna: Journal of Multidisciplinary Studies, 3(1), 24–31. https://doi.org/10.62048/qjms.v3i1.124
Pratama, A. J., & Mandela, R. (2024). Evaluating the effectiveness of smart irrigation systems in improving agricultural productivity. Agricultural Power Journal, 1(4).
Putra, R. D., & Nugroho, A. (2022). Sistem irigasi otomatis berbasis sensor kelembapan tanah menggunakan mikrokontroler. Jurnal Teknik Informatika dan Sistem Tertanam, 6(2), 101–110.
Rahman, M. M., Islam, M. T., & Hossain, M. A. (2021). IoT-based smart irrigation system for precision agriculture. Computers and Electronics in Agriculture, 180, 105872. https://doi.org/10.1016/j.compag.2020.105872
Rahman, M. N., Sozol, S. S., Hossin, M. S., Rahman, M. M., & Islam, M. R. (2024). Soil characterization of watermelon field through IoT. IOP Conference Series, 1265(1), Article 012034. https://doi.org/10.1088/1755-1315/1265/1/012034
Roziqin, M., Fauzan, A., & Haq, S. Z. N. (2025). Rancang bangun penyiraman tanaman cabe otomatis menggunakan ESP32. Jurnal Informatika dan Teknik Elektro Terapan, 13(3).
Saputra, M. J., & Suryono, R. R. (2024). Implementasi teknologi irigasi tetes pada tanaman jagung menggunakan sensor soil moisture. MALCOM: Indonesian Journal of Machine Learning and Computer Science.
Saragih, K. A., & Kurniawan, R. (2025). Sistem penyiraman otomatis berbasis IoT dengan logika fuzzy Sugeno. Jurnal Algoritma, 23(1), 808–819. https://doi.org/10.33364/jurnalalgoritma.v22-1.2327
Seyar, M. H., & Ahamed, T. (2023). Development of an IoT-based precision irrigation system for tomato production. Applied Sciences.
Singh, D., Kumar, P., & Sharma, R. (2023). Smart irrigation systems for sustainable agriculture. Sustainable Computing: Informatics and Systems, 38, 100857. https://doi.org/10.1016/j.suscom.2023.100857
Supria, S., Wahyat, W., & Musri, T. (2025). Sistem distribusi pengairan dan monitoring kelembapan tanah berbasis IoT. Techno.Com, 24(2).
Susanti, L., Wijayanto, B., & Rimartin, G. A. (2025). Penerapan sistem irigasi otomatis berbasis kelembaban tanah pada produksi benih melon. Jurnal Pengabdian Masyarakat dan Riset Pendidikan, 3(4), 1005–1012. https://doi.org/10.31004/jerkin.v3i4.1005
Tace, Y., Tabaa, M., Elfilali, S., & Leghris, C. (2022). Smart irrigation system based on IoT and machine learning. Energy Reports, 8, 1025–1036. https://doi.org/10.1016/j.egyr.2022.07.088
Vaddevolu, U. B. P. (2021). Automatic drip irrigation using soil moisture sensors. Water, 13(14), 1991. https://www.mdpi.com/2073-4441/13/14/1991
Wahyudi, A., Pradana, A. I., & Permatasari, H. (2025). Implementasi sistem irigasi otomatis berbasis IoT untuk pertanian greenhouse. Jurnal Pendidikan dan Teknologi Indonesia, 5(2), 435–446. https://doi.org/10.52436/1.jpti.656
Wang, H., Wang, N., Quan, H., Zhang, F., Fan, J., Feng, H., Cheng, M., Liao, Z., Wang, X., & Xiang, Y. (2022). Yield and water productivity under subsurface drip irrigation. Agricultural Water Management, 269, 107645. https://doi.org/10.1016/j.agwat.2022.107645
Wang, Z., Yu, S., Zhang, H., Lei, L., Liang, C., Chen, L., Su, D., & Li, X. (2023). Deficit mulched drip irrigation improves yield and water use efficiency. Agricultural Water Management, 277, 108103. https://doi.org/10.1016/j.agwat.2022.108103
Widari, L. A. (2025). Dampak teknologi irigasi otomatis terhadap efisiensi ekonomi pertanian. Journal of Economic Studies, 1(2), 107–113.
Xiao, C., Cai, J., Zhang, B., Chang, H., & Wei, Z. (2023). Evaluation of evapotranspiration models. Agricultural Water Management, 278, 108166. https://doi.org/10.1016/j.agwat.2023.108166
Yang, P., Wu, L., Cheng, M., Fan, J., Li, S., Wang, H., & Qian, L. (2023). Review on drip irrigation impact on crop yield and water productivity.
Zhang, Y., et al. (2023). Intelligent drip fertigation increases efficiency of watermelon. Agricultural Water Management. 282: 108278. https://doi.org/10.1016/j.agwat.2023.108278
Zhang, Z. (2021). Precise soil water control improves watermelon productivity. Agricultural Water Management. https://www.sciencedirect.com/science/article/pii/S0378377421004212
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