Design Smart Farming in Rice Field for Monitoring Soil Fertility and Pest Rate Using Internet of Things

Authors

Nurdina Widanti , Aditya Alamsyah , Actor Albus , Ahmad Nur Ikhsan , Sri Wiji Lestari , Wike Handini , Sasmito Adi Raharjo

DOI:

10.29303/jppipa.v10i8.8288

Published:

2024-08-25

Issue:

Vol. 10 No. 8 (2024): August: In Press

Keywords:

IoT, Monitoring, Pest, Rice, Soil fertility

Research Articles

Downloads

How to Cite

Widanti, N., Alamsyah, A., Albus, A., Ikhsan, A. N., Lestari, S. W., Handini, W., & Raharjo, S. A. (2024). Design Smart Farming in Rice Field for Monitoring Soil Fertility and Pest Rate Using Internet of Things. Jurnal Penelitian Pendidikan IPA, 10(8), 5782–5788. https://doi.org/10.29303/jppipa.v10i8.8288
Crossref
Scopus
Google Scholar
Europe PMC

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Abstract

Rice fields in Indonesia have a strategic role in providing food for the Indonesian population. The Central Statistics Agency (BPS) noted that domestic rice consumption also continues to increase, 98.35% of households in Indonesia consume rice. There are many influencing factors for production rice such as pest, climate change. The aim to optimize rice production by monitoring soil moisture and soil pH and adding protection features to detect rat pests. This tool was built using an Internet of Things-based system integration method, where the system output can be monitored on the blynk and email applications for the reading history of rat pests if they are caught on camera. The results obtained from the system are Soil moisture sensor readings have a system accuracy of 99% with an error value of 0.01. And the pH sensor reading has an accuracy of 99% with an error of 0.015. The most optimal PIR sensor reading is 1 meter and this data is sent simultaneously with the camera sensor via email. Monitoring data on rice agricultural land by adding rat pest protection features, as well as historical data can be captured wellcan provide a strong basis for the development of more effective and sustainable.

References

Aarthi, R., Sivakumar, D., & Mariappan, V. (2022). Smart Soil Property Analysis Using IoT: A Case Study Implementation in Backyard Gardening. Procedia Computer Science, 218(2022), 2842–2851. https://doi.org/10.1016/j.procs.2023.01.255

Amnerkar, P., Bawane, K., Raut, M., Bargat, D., Damahe, B., & Ande, P. K. A. (2023). an Iot-Based Solution for Insect Monitoring in Agriculture Using Raspberry Pi and Yolo. International Research Journal of Modernization in Engineering Technology and Science, 04, 7364–7369. https://doi.org/10.56726/irjmets36564

Cardoso, B., Silva, C., Costa, J., & Ribeiro, B. (2022). Internet of Things Meets Computer Vision to Make an Intelligent Pest Monitoring Network. Applied Sciences (Switzerland), 12(18). https://doi.org/10.3390/app12189397

CNBC Indonesia. (2023). 98% Warga RI Makan Beras, Harga Mahal-Bikin Miskin Tetap Beli. Retrieved from https://www.cnbcindonesia.com/research/20231014100600-128-480511/98-warga-ri-makan-beras-harga-mahal-bikin-miskin-tetap-beli

Daniel, L. E. P., Mahmudin, A., & Auliasari, K. (2020). Penerapan IoT (Internet of Thing) Terhadap Sistem Pendeteksi Kesuburan Tanah Pada Lahan Perkebunan. JATI (Jurnal Mahasiswa Teknik Informatika), 4(2), 207–213. https://doi.org/10.36040/jati.v4i2.2678

Derpsch, R., Kassam, A., Reicosky, D., Friedrich, T., Calegari, A., Basch, G., Gonzalez-Sanchez, E., & dos Santos, D. R. (2024). Nature’s laws of declining soil productivity and Conservation Agriculture. Soil Security, 14(January 2023), 100127. https://doi.org/10.1016/j.soisec.2024.100127

Dewanto, D., Wantu, H. M., Dwihapsari, Y., Santosa, T. A., & Agustina, I. (2023). Effectiveness of The Internet of Things (IoT)-Based Jigsaw Learning Model on Students’ Creative Thinking Skills: A- Meta-Analysis. Jurnal Penelitian Pendidikan IPA, 9(10), 912–920. https://doi.org/10.29303/jppipa.v9i10.4964

Diharja, R., Fahlevi, M. R., Rahayu, E. S., & Handini, W. (2022). Prototype-Design of Soil Movement Detector Using IoT Hands-on Application. Jurnal Penelitian Pendidikan IPA, 8(4), 2245–2254. https://doi.org/10.29303/jppipa.v8i4.1709

Dinas Pertanian dan Pangan Kabupaten Kulon Progo. (2023). DIPERTAPA - Hama Utama Padi. Retrieved from https://pertanian.kulonprogokab.go.id/detil/1206/hama-utama-padi

DINPPKP. (2023). Memperbaiki Struktur Tanah Yang Rusak Dengan Penggunaan Pupuk Organik. DKKPP Purworejo.

Fang, L. (2020). Research on Plant Diseases and Insect Pests Monitoring Technology under the Background of Internet of Things Technology. 2020 International Wireless Communications and Mobile Computing, IWCMC 2020, 1999–2001. https://doi.org/10.1109/IWCMC48107.2020.9148255

Firmansyah, D., Muhrozim, N. R., Sidabutar, J. P. A., Amalia, N. A., & Alvian Dwi Sanjaya. (2023). Penerapan Teknologi Tepat Guna “Alat Pendeteksi Kesuburan Tanah” di Desa Balonggebang. Perigel: Jurnal Penyuluhan Masyarakat Indonesia, 2(2), 75–81. https://doi.org/10.56444/perigel.v2i2.905

Ghosh, D., Anand, A., Gautam, S. S., & Vidyarthi, A. (2022). Soil Fertility Monitoring with Internet of Underground Things: A Survey. IEEE Micro, 42(1), 8–16. https://doi.org/10.1109/MM.2021.3121496

Immanuel, J. M., Ibrahim, I., Rahmadewi, R., & Saragih, Y. (2024). IoT-based Facelook and Fingerprint Safe Security System. Jurnal Penelitian Pendidikan IPA, 10(2), 500–505. https://doi.org/10.29303/jppipa.v10i2.6832

Indra, A. T., Harmadi, H., & Marzuki, M. (2023). Prototype of Forest and Land Fire Monitoring and Detection System Using IoT-Based WSN Technology. Jurnal Penelitian Pendidikan IPA, 9(12), 11837–11845. https://doi.org/10.29303/jppipa.v9i12.5736

Islam, M. R., Oliullah, K., Kabir, M. M., Alom, M., & Mridha, M. F. (2023). Machine learning enabled IoT system for soil nutrients monitoring and crop recommendation. Journal of Agriculture and Food Research, 14(June), 100880. https://doi.org/10.1016/j.jafr.2023.100880

Kementerian Pekerjaan Umum. (2016). Tekonologi Infrastruktur Perdesaan: Sawah Irigasi.

Kumar, V., Sharma, K. V., Kedam, N., Patel, A., Kate, T. R., & Rathnayake, U. (2024). A comprehensive review on smart and sustainable agriculture using IoT technologies. Smart Agricultural Technology, 8(June), 100487. https://doi.org/10.1016/j.atech.2024.100487

Materne, N., & Inoue, M. (2018). IoT monitoring system for early detection of agricultural pests and diseases. Proceedings - 12th SEATUC Symposium, SEATUC 2018. https://doi.org/10.1109/SEATUC.2018.8788860

Mathi, S., Akshaya, R., & Sreejith, K. (2022). An Internet of Things-based Efficient Solution for Smart Farming. Procedia Computer Science, 218(2022), 2806–2819. https://doi.org/10.1016/j.procs.2023.01.252

McCole, M., Bradley, M., McCaul, M., & McCrudden, D. (2023). A low-cost portable system for on-site detection of soil pH and potassium levels using 3D printed sensors. Results in Engineering, 20(November), 101564. https://doi.org/10.1016/j.rineng.2023.101564

Mohanty, S., Pani, S. K., Tripathy, N., Rout, R., Acharya, M., & Raut, P. K. (2024). Prevention of soil erosion, prediction soil NPK and Moisture for protecting structural deformities in Mining area using fog assisted Smart agriculture system. Procedia Computer Science, 235, 2538–2547. https://doi.org/10.1016/j.procs.2024.04.239

Morchid, A., El Alami, R., Raezah, A. A., & Sabbar, Y. (2024). Applications of internet of things (IoT) and sensors technology to increase food security and agricultural Sustainability: Benefits and challenges. Ain Shams Engineering Journal, 15(3). https://doi.org/10.1016/j.asej.2023.102509

Nenotek, P. S., Simamora, A. V, Hahuly, M. V, & Nguru, E. O. St. (2022). Inventory of Pests on Local Potato Plants from Soe in South Central East District, Province of East Nusa Tenggara. Jurnal Penelitian Pendidikan IPA, 8(SpecialIssue), 39–45. https://doi.org/10.29303/jppipa.v8iSpecialIssue.2485

Passias, A., Tsakalos, K.-A., & Rigogiannis, N. (2023). Comparative Study of Camera- and Sensor-Based Traps for Insect Pest Monitoring Applications. AgriFood Electronics (CAFE). https://doi.org/10.1109/CAFE58535.2023.10291672

Putra, B. A., Kharisma, A. P., & Al Huda, F. (2022). Penelitian Akurasi Diagnosa Penyakit Tanaman Padi menggunakan Kamera dengan Metode Klasifikasi Gambar pada Perangkat Bergerak Android. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 6(10), 4686-4692. Retrieved from https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/11654

Rajak, P., Ganguly, A., Adhikary, S., & Bhattacharya, S. (2023). Internet of Things and smart sensors in agriculture: Scopes and challenges. Journal of Agriculture and Food Research, 14(June), 100776. https://doi.org/10.1016/j.jafr.2023.100776

Ratnawati, D., & Setiadi, B. R. (2019). Techno-Pest Control Berbasis IoT untuk Proteksi Tanaman Padi. Jurnal Dinamika Vokasional Teknik Mesin, 4(2), 129–133. https://doi.org/10.21831/dinamika.v4i2.27396

Rohmah, R. N., Oktafianto, Y., Nurokhim, Supriyono, H., & Supardi, A. (2024). Pest Control System on Agricultural Land Using Iot Electronic Controller. Journal of Applied Engineering and Technological Science, 5(2), 1011–1019. https://doi.org/10.37385/jaets.v5i2.4592

Rosyidin, Z. U., Argeshwara, D. K., Wibawa, A. P., Handayani, A. N., & Hadi, M. S. (2023). Pemodelan Sistem Deteksi Kadar Unsur Hara Tanah Berdasarkan Nilai NPK Menggunakan Metode Fuzzy Mamdani. Jurnal Sains Dan Informatika, 9(November 2022), 77–88. https://doi.org/10.34128/jsi.v9i1.523

Safiatuddin, S., & Asnawi, R. (2023). Effectiveness of Using Virtual Reality-Based Virtual Laboratories in the Internet of Things Course. Jurnal Penelitian Pendidikan IPA, 9(7), 5062–5070. https://doi.org/10.29303/jppipa.v9i7.4040

Singh, R., Gehlot, A., Vaseem Akram, S., Kumar Thakur, A., Buddhi, D., & Kumar Das, P. (2022). Forest 4.0: Digitalization of forest using the Internet of Things (IoT). Journal of King Saud University - Computer and Information Sciences, 34(8), 5587–5601. https://doi.org/10.1016/j.jksuci.2021.02.009

Siregar, M. T. (2023). Design of Integrated Warehouse Control Tower (WCT) Digitalization by the Internet of Things Architectures. Jurnal Penelitian Pendidikan IPA, 9(6), 4368–4374. https://doi.org/10.29303/jppipa.v9i6.3781

Subeesh, A., & Mehta, C. R. (2021). Automation and digitization of agriculture using artificial intelligence and internet of things. Artificial Intelligence in Agriculture, 5, 278–291. https://doi.org/10.1016/j.aiia.2021.11.004

Sudrajat. (2015). Mengenal Lahan Sawah dan Memahami Multifungsinya Bagi Manusia dan Lingkungan. Gadjah Mada University Press.

Tomczyk, P., Wdowczyk, A., Wiatkowska, B., Szymańska-Pulikowska, A., & Kuriqi, A. (2024). Fertility and quality of arable soils in Poland: spatial–temporal analysis of long-term monitoring. Ecological Indicators, 166(April). https://doi.org/10.1016/j.ecolind.2024.112375

Untoro, M. C., Praseptiawan, M., Ashari, I. F., Yunira, E. N., & Hanifah, R. (2021). Sistem Kontroling Dan Monitoring Hama Padi Berbasis Internet of Thing. Jurnal Karya Abdi, 5(3), 677–682. https://doi.org/10.22437/jkam.v5i3.17298

Wahyudi, B. T., Hidayat, T., Studi, P., Elektro, T., Industri, F. T., & Indonesia, U. I. (2022). Alat Pendeteksi Tingkat Kesuburan Tanah Dengan Pendekatan Pengukuran Parameter Kelistrikan Tanah. Retrieved from https://dspace.uii.ac.id/handle/123456789/40434

Wang, X., Yan, B., Shutes, B., Wang, M., & Zhu, H. (2024). Dynamics and microbial characteristics of nitrogen and carbon in saline-alkali paddy soil under different fertilization. Watershed Ecology and the Environment, 6(June), 95–104. https://doi.org/10.1016/j.wsee.2024.06.002

Wicaksono, M. G. S., Suryani, E., & Hendrawan, R. A. (2021). Increasing productivity of rice plants based on IoT (Internet of Things) to realize Smart Agriculture using System Thinking approach. Procedia Computer Science, 197, 607–616. https://doi.org/10.1016/j.procs.2021.12.179

Author Biographies

Nurdina Widanti, Jayabaya University

Aditya Alamsyah, Jayabaya University

Actor Albus, Jayabaya University

Ahmad Nur Ikhsan, Jayabaya University

Sri Wiji Lestari, Jayabaya University

Wike Handini, Jayabaya University

Sasmito Adi Raharjo, Jayabaya University

License

Copyright (c) 2024 Nurdina Widanti, Aditya Alamsyah, Actor Albus, Ahmad Nur Ikhsan, Sri Wiji Lestari, Wike Handini, Sasmito Adi Raharjo

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with Jurnal Penelitian Pendidikan IPA, agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY License). This license allows authors to use all articles, data sets, graphics, and appendices in data mining applications, search engines, web sites, blogs, and other platforms by providing an appropriate reference. The journal allows the author(s) to hold the copyright without restrictions and will retain publishing rights without restrictions.
  2. 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 acknowledgment of its initial publication in Jurnal Penelitian Pendidikan IPA.
  3. 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 (See The Effect of Open Access).