Pengembangan Sistem Otomatisasi Pakan Ikan dan Monitoring Kualitas Lingkungan Berbasis IoT dan Machine Learning  untuk Budidaya Ikan Berbasis Web

Muhammad Alfin; Dedy Kiswanto; Muhammad Budi Akbar; Najwa Latifah Hasibuan

doi:10.32672/jnkti.v9i1.160

Authors

Muhammad Alfin Universitas Negeri Medan Author
Dedy Kiswanto State University of Medan Author
Muhammad Budi Akbar State University of Medan Author
Najwa Latifah Hasibuan State University of Medan Author

DOI:

https://doi.org/10.32672/jnkti.v9i1.160

Keywords:

Internet of Things (IoT); Machine Learning; ESP32; Servo Motor; Pakan Otomatis; Budidaya Ikan;

Abstract

Abstrak - Pemberian pakan yang tidak efisien dan kurangnya pemantauan kondisi lingkungan merupakan tantangan utama dalam budidaya ikan tradisional, yang berdampak pada peningkatan biaya operasional dan penurunan produktivitas. Penelitian ini bertujuan untuk merancang dan mengimplementasikan Sistem Otomatisasi Pakan dan Monitoring Kualitas Lingkungan Budidaya Ikan berbasis Internet of Things (IoT) dan Machine Learning (ML) sederhana. Sistem ini menggunakan mikrokontroler ESP32 sebagai pusat kendali untuk membaca data sensor suhu dan menggerakkan servo motor sebagai mekanisme feeder pakan otomatis. Data sensor lingkungan dan parameter ikan (jumlah dan umur) dikirim ke Flask API yang berfungsi sebagai jembatan komunikasi dan pengolah data. Di sisi server, Flask API mengaplikasikan model Regresi Sederhana untuk mengestimasi kebutuhan pakan harian secara adaptif. Hasil estimasi kemudian dikirimkan kembali ke ESP32 untuk eksekusi pemberian pakan. Seluruh proses monitoring dan input parameter dilakukan melalui Dashboard Web berbasis PHP. Hasil pengujian menunjukkan bahwa sistem mampu melakukan pemantauan suhu secara real-time dan melaksanakan mekanisme pemberian pakan secara akurat sesuai hasil perhitungan ML. Integrasi yang efisien antara IoT, API, dan model ML ini diharapkan dapat mengoptimalkan manajemen pakan, mengurangi limbah, dan mendukung praktik akuakultur yang lebih berkelanjutan.

Kata kunci : Internet of Things (IoT); Machine Learning; ESP32; Servo Motor; Pakan Otomatis; Budidaya Ikan;

Abstract - Inefficient feeding practices and the lack of environmental condition monitoring are major challenges in traditional aquaculture, leading to increased operational costs and reduced productivity. This study aims to design and implement an Automated Feeding and Environmental Quality Monitoring System for fish cultivation based on the Internet of Things (IoT) and simple Machine Learning (ML). The system uses an ESP32 microcontroller as the central controller to read temperature sensor data and operate a servo motor as the automatic feeding mechanism. Environmental sensor data and fish parameters (quantity and age) are transmitted to a Flask API, which functions as a communication bridge and data processor. On the server side, the Flask API applies a Simple Regression model to estimate daily feed requirements adaptively. The estimation results are then sent back to the ESP32 for feed dispensing execution. All monitoring processes and parameter inputs are conducted through a PHP-based web dashboard. Experimental results show that the system is capable of performing real-time temperature monitoring and executing accurate feeding mechanisms according to the ML calculations. The efficient integration of IoT, API, and ML models is expected to optimize feed management, reduce waste, and support more sustainable aquaculture practices.

Keywords: Internet of Things (IoT); Machine Learning; ESP32; Servo Motor; Automatic Feeding; Aquaculture;

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Author Biographies

Muhammad Alfin, Universitas Negeri Medan

Program Studi Ilmu Komputer, Fakultas Matematika Ilmu Pengetahuan Alam
Dedy Kiswanto, State University of Medan

Program Studi Ilmu Komputer, Fakultas Matematika Ilmu Pengetahuan Alam
Muhammad Budi Akbar, State University of Medan

Program Studi Ilmu Komputer, Fakultas Matematika Ilmu Pengetahuan Alam
Najwa Latifah Hasibuan, State University of Medan

Program Studi Ilmu Komputer, Fakultas Matematika Ilmu Pengetahuan Alam

References

[1] Sudibyo, H., Yuniko, F. T., Fadel, A., Lesmana, L. S., and Efendi, R., “Sistem Monitoring Budidaya Perikanan Berbasis IoT Fish Feeder Sebagai Implementasi Smart Farming,” JOISIE (Journal Of Information Systems And Informatics Engineering), vol. 8, no. 2, pp. 236–247, Dec. 2024.

[2] Mohamed, A. A., Ahmed, M. M., Muhammad, N. A., and Ali, A. A., “IOT-based Automatic Fish Feeding System,” in 2024 IEEE 22nd Student Conference on Research and Development (SCORED), 2024, doi: 10.1109/SCOReD64708.2024.10872688.

[3] Sobri, M. A., and Topiq, S., “Automatic Fish Feed Design and IoT Based Monitoring Using NodeMCU ESP8266 Microcontroller,” Journal Corner of Education, Linguistics, and Literature, vol. 4, no. 001, pp. 503-514, Dec. 2024, doi: 10.54012/jcell.v4i001.426.

[4] Abdikadir, N. M., Abdullah, A. S., Abdullahi, H. O., and Hassan, A. A., “Smart Aquaculture: IoT-Enabled Monitoring and Management of Water Quality for Mahseer Fish Farming,” SSRG International Journal of Electrical and Electronics Engineering, vol. 11, no. 11, pp. 84–92, Nov. 2024.

[5] Patil, A. A., Shaikh, S. F., Todkar, S. J., and Waghmare, P. A., “Automatic Fish Feeding System,” International Journal of Research Publication and Reviews, vol. 6, no. 4, pp. 9954–9957, Apr. 2025.

[6] Silalahi, A. O., Sinambela, A., Panggabean, H. M., and Pardosi, J. T. N., “SMART AUTOMATED FISH FEEDING BASED ON IOT SYSTEM USING LORA TTGO SX1276 AND CAYENNE PLATFORM,” EUREKA: Physics and Engineering, vol. 3, 2023.

[7] Babu, P., Kumar, K. A., Rakesh, N., and Ramana, C., “Development of Automatic Fish Feeding Machine for Integrated Floating Cage Aquageoponic System,” International Journal of Environment and Climate Change, vol. 13, no. 3, pp. 17–25, Feb. 2023, doi: 10.9734/IJECC/2023/v13i31675.

[8] Roy, D., Padhiary, M., Roy, P., and Barbhuiya, J. A., “Artificial Intelligence-Driven Smart Aquaculture: Revolutionizing Sustainability Through Automation and Machine Learning,” LatIA, vol. 2, no. 116, Dec. 2024, doi: 10.62486/latia2024116.

[9] Manoj, M., and Rajan, R., “Precision Aquaculture Using IoT & Machine Learning Techniques,” AGPE The Royal Gondwana Research Journal of History, Science, Economic, Political and Social Science, vol. 2, no. 1, pp. 105–111, Jul. 2021.

[10] Hossam, R., Heakl, A., and Gomaa, W., “Precision Aquaculture: An Integrated Computer Vision and IoT Approach for Optimized Tilapia Feeding,” arXiv Preprint, arXiv:2409.08695v2, Sep. 2024.

[11] Rahayuningtyas, A., Sagita, D., Azizah, I. F., and Furqon, M., “Design and Performance of an Automatic Fish Feeder With an Adjustable Spreader System,” AgricEngInt: CIGR Journal, vol. 25, no. 4, pp. 92–102, Dec. 2023.

[12] Kurniawan, Z., and Tiaharyadini, R., “Predicting Catfish Growth and Feed Efficiency in Using Decision Tree and Support Vector Regression,” Indonesian Journal of Artificial Intelligence and Data Mining (IJAIDM), vol. 8, no. 1, pp. 271–280, Mar. 2025.

[13] D. Kiswanto, F. Ramadhani, N. M. Surbakti, and N. A. Nasution, “Pengembangan dan Implementasi Sistem Deteksi Serangan DDoS Berbasis Algoritma Random Forest,” Bulletin of Information Technology (BIT), vol. 6, no. 3, pp. 247–256, Sep. 2025, doi: 10.47065/bit.v5i2.2203.

[14] Nur, M. R., Rizkysuro, E., Istiqomah, I., Kurniawan, T., Klana Surbakti, S. A., Putra, A. P., Pertama, V. A., Suryawan, A. F. D., Tahajjadan Zhaahir Haq, R., & Setiawan, A., “Sistem Pakan Tertakar Otomatis untuk Budidaya Ikan Nila Merah Berbasis IoT,” Journal of Internet and Software Engineering, vol. 1, no. 4, pp. 1–9, 2024.

[15] Misniati, Samsumar, L. D., & Zaenudin, “Implementasi Smart Feeder Berbasis Internet of Things (IoT) pada Akuarium Ikan,” Journal of Computer Science and Informatics Engineering, vol. 5, no. 1, pp. 13–27, Jan. 2026.

[16] Alfin, M., Kiswanto, D., Akbar, M. B., & Hasibuan, N. L., “Pengembangan Sistem Otomatisasi Pakan Ikan dan Monitoring Kualitas Lingkungan Berbasis IoT dan Machine Learning untuk Budidaya Ikan Berbasis Web,” Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI), vol. 8, no. 3, Jun. 2025.

[17] Chua, R., Kusnandar, & Rafida, V., “Rancang Bangun Sistem Monitoring Ph dan Suhu Air Kolam pada Budidaya Ikan Berbasis Internet Of Things Menggunakan Arduino Uno,” Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI), vol. 8, no. 3, Jun. 2025.

[18] Pane, U. F. S. S., & Andriyani, I., “Sistem Pendeteksi Kualitas Air Pada Budidaya Ikan Air Tawar Berbasis Internet Of Things (IoT),” Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD, vol. 7, no. 1, pp. 84–94, Jan. 2024.