Sistem Pemantauan Kualitas Udara Berbasis IoT untuk Peternakan Kambing
DOI:
https://doi.org/10.30595/jrre.v8i1.30550Keywords:
Gas amonia, Gas metana, Mikrokontroler, Peternakan kambing, Internet of ThingsAbstract
Penelitian ini bertujuan untuk mengembangkan sistem pemantauan kadar gas amonia (NH3) dan metana (CH4) pada peternakan kambing berbasis IoT (Internet of Things). Sistem ini menggunakan sensor gas MQ-135 untuk mendeteksi kadar amonia, sensor MQ-4 untuk mendeteksi kadar metana dan panel surya sebagai sumber energi. Data yang diperoleh dari sensor kemudian diolah oleh mikrokontroler ESP-32 dan ditampilkan secara real-time melalui aplikasi IoT Firebase. Hasil penelitian menunjukkan bahwa sistem ini dapat memantau kadar gas amonia dan metana secara akurat dan efektif. Sistem ini juga dapat memberikan notifikasi jika kadar gas melebihi batas normal, sehingga dapat membantu peternak dalam mengelola kesehatan dan keselamatan hewan ternak serta mengurangi dampak lingkungan. Berdasarakan sampel hasil pengukuran, rata-rata kadar gas amonia terukur sebesara 11,105 ppm dan gas metana sebesara 0,386 ppm. Kelebihan sistem ini adalah dapat memantau kondisi kandang secara real-time, sehingga dapat meningkatkan efisiensi dan keselamatan operasional peternakan. Sistem ini juga dapat diintegrasikan dengan sistem lainnya untuk meningkatkan kemampuan monitoring dan controlling.
References
[1] Rusdiana, S, dan A Maesya, (2017), “Pertumbuhan ekonomi dan kebutuhan pangan di Indonesia”.
Agriekonomika, Vol. 6, No. 1, Hal. 12–25.
[2] Octaviano, A., Sofiana, S., Agustino, D. O., dan Rosyani, P., (2022), “Pemantauan Kualitas Udara Berbasis Internet Of Things”, KLIK: Kajian Ilmiah Informatika dan Komputer, Vol. 3, No. 2, ISSN 2723-3898., Hal. 147-156.
[3] Hasanuddin, M. dan Herdianto, (2023), “Sistem Monitoring dan Deteksi Dini Pencemaran Udara Berbasis Internet of Things (IOT)”, Journal of Computer System and Informatics (JoSYC), Vol. 4, No. 4, ISSN 2714-8912 (media online), ISSN 2714-7150 (media cetak), Hal. 976-984.
[4] Susatyono, J. D. dan Fitrianto, Y, (2021), “Sistem Monitoring Kualitas Udara dan Otomatisasi Pemberian Pakan Ayam Berbasis IoT”, KREA-TIF: JURNAL TEKNIK INFORMATIKA, Vol. 9, No. 2, p-ISSN: 2338-2910, e-ISSN:2658-5836, pp. 1 – 10.
[5] Anisha, L., Bala, D. B., Sabitha, S., and Beby, M. L. A., (2024), “Smart IoT System for Gas Monitoring and Environmental Control in Poultry Farms”, Irish Interdisciplinary Journal of Science & Research (IIJSR), Vol. 8, No. 2, pp. 102-112.
[6] Tan, Y.S., Tan, S.Z., Chew, L. W., and Tan, Y. X., (2024), “IoT-based Smart Farming System”, International Journal of Emerging Multidisciplinaries: Computer Science and Artificial Intelligence. IJEMD-CSAI, Vol. 3, No. 1, pp. 1 –14.
[7] Idofitraramdhan, Bustami, M. I. dan Riyadi, W., (2023), “Perancangan Smart System Ternak Ayam berbasis IoT mengunakan Arduino UNO”, Jurnal Informatika Dan Rekayasa Komputer (JAKAKOM). Vol. 3, No. 1, ISSN 2808-5469 (media cetak), ISSN 2808-5000 (media online).
[8] Dankan, G. V., Sandeep, P. M., Ramesha, M., Jayashree, M. K. and Ansuman, S., (2021), “Smart Agriculture and Smart Farming using IoT Technology”, Journal of Physics: Conference Series. 2089 (2021) 012038, doi:10.1088/1742-6596/2089/1/012038.
[9] Syafar, F., Anwar, M. and Ridwansyah, (2021), “Smart Chicken Poultry Farm Using IoT Techniques”, International Journal of New Technology and Research (IJNTR), Volume-7, Issue-10, ISSN: 2454-4116, pp. 40-43, doi:10.31871/IJNTR.7.10.11.
[10] Menduni, G., Andrea Zifarelli, A., Kniazeva, E., Russo, S. D., Ranieri, A. C., Ranieri, E., Patimisco, P., Sampaolo, A., Giglio, M., Manassero, F., Dinuccio, E., Provolo,G., Wu, H., Lei, D., and Spagnolo, V., (2023), “Measurement of methane, nitrous oxide and ammonia in atmosphere with a compact quartz-enhanced photoacoustic sensor”, Sensors and Actuators: B. Chemical, doi:10.1016/j.snb.2022.132953.
[11] Vechi, N. T., Mellqvist, J., Samuelsson, J., Offerle, B., and Scheutz, C., (2022), “Ammonia and methane emissions from dairy concentrated animal feeding operations in California, using mobile optical remote sensing”, Atmospheric Environment, doi:10.1016/j.atmosenv.2022.119448.
[12] Azizah, D. N., Heranurweni, S., and Idris, L. O. M., (2025), “Internet of Things Based Air Quality Monitoring System with Automatic Notification”, MALCOM: Indonesian Journal of Machine Learning and Computer Science, Vol. 5, Iss. 3, ISSN(P): 2797-2313 | ISSN(E): 2775-8575, pp: 776-787.
[13] Banhazi, T. M., (2009), “Uer‐Friendly Air Quality Monitoring System”, Applied Engineering in Agriculture, Vol. 25(2): 281‐290, ISSN 0883-8542.
[14] Janke, D., , Bornwin, M., Coorevits, K., Hempel, S., Overbeke, P. V., Demeyer, P., Rawat, A., Declerck, A., Amon, T., and Amon, B., (2023), “A Low-Cost Wireless Sensor Network for Barn Climate and Emission Monitoring—Intermediate Results”, Atmosphere, doi.:0.3390/atmos14111643.
[15] Gosavi, A., Dhamdhere, A., Gore, A. and Sardar, V. M., (2025), “IoT Based Poisonous Gas Detection, Monitoring and Alert System”, IJIRT (INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN TECHNOLOGY), Vol. 11 Issue 11, ISSN: 2349-6002, pp. 6570-6574.
[16] Al-Faris, M. G., and Elsi, Z. R. S., (2024), “Air Quality Monitoring System Based Internet Of Things”, Brilliance: Research of Artificial Intelligence, Vol. 4, No. 2, E-ISSN: 2807-9035, pp. 669-673.
[17] Kulshrestha, D., Asati, A., Vyas, S., Sharma, S., and Bhadouria, A. S., (2024), “Air Pollution Detection & Monitoring Using Internet of Things (IoT)”, MULTIDISCIPLINARY INNOVATIONS IN TECHNOLOGY AND SCIENCE JOURNAL, Vol. 01, Issue 01, pp. 48-62.
[18] Sakib, M., Sarkar, T., Das, S., Jannat, M., Akter, S, Shahjalal, M., (2024), “Real-Time IoT-Based Toxic Gas Monitoring and Comparative Analysis of Machine Learning Techniques for Air Quality Index Prediction in Dhaka”, 4th Int. Conf. on Innovations in Science, Engineering and Technology (ICISET), DOI: 10.1109/ICISET62123.2024.10939534.
[19] Revanth, M. S, Sanjay, S, Puta, Y. R., Sreeja, B.S., (2021), “Smart IoT Device For Sewage Gas Mooitoring And Alert System”, International Research Journal of Education and Technology, Volume: 02 Issue: 03, ISSN: 2581-7795, pp. 52-57.
[20] Shobana, J., Venkata, S. A., Balamurugan, P., Sivakumar, P., Sankari, V., Eldho, K. J., and Nareshkumar, R., (2025), “Smart Agriculture: Integrating Air Quality Monitoring With Deep Learnig For Process Optimization”, Scalable Computing: Practice and Experience, Volume 26, Issues 3, ISSN 1895-1767, pp. 1005–1016
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