Implementasi Sistem Pengatur Nutrisi AB Mix Berbasis Internet of Things pada Greenhouse

Abstract

Pengaturan nutrisi AB Mix pada sistem hidroponik NFT di greenhouse masih banyak dilakukan secara manual sehingga berpotensi menyebabkan ketidaksesuaian dosis. Penelitian ini bertujuan mengimplementasikan sistem pengatur nutrisi AB Mix berbasis Internet of Things untuk mendukung pemantauan dan pengendalian nutrisi secara otomatis. Metode penelitian meliputi pengembangan perangkat keras, perangkat lunak, dan website. Perangkat keras mengintegrasikan ESP32, sensor TDS, sensor suhu air, relay, pompa peristaltik, RTC, dan LCD. Perangkat lunak dirancang untuk membaca sensor, menjalankan kontrol berdasarkan setpoint, mengatur kerja pompa, serta mengirim data melalui MQTT. Website digunakan untuk pemantauan, pengaturan sistem, riwayat data, manajemen alat, dan kontrol nutrisi. Hasil pengujian menunjukkan sensor TDS memiliki RMSE 8,84 ppm dan MAPE 1,133%, sensor suhu air memiliki RMSE 0,218 °C dan MAPE 0,671%, serta pompa peristaltik memiliki RMSE 0,53 mL dan MAPE 1,117%. Pengujian respons otomatis berhasil 100% dari 10 skenario. Sistem ini mampu membantu pengelolaan nutrisi hidroponik secara lebih terukur dan konsisten.

The adjustment of AB Mix nutrients in NFT hydroponic systems in greenhouses is still largely done manually, which can potentially lead to dosage discrepancies. This study aims to implement an Internet of Things (IoT)-based AB Mix nutrient control system to support automatic nutrient monitoring and control. The research methods include the development of hardware, software, and a website. The hardware integrates an ESP32, a TDS sensor, a water temperature sensor, a relay, a peristaltic pump, an RTC, and an LCD. /T//he software is designed to read sensor data, execute controls based on setpoints, regulate pump operation, and transmit data via MQTT. The website is used for monitoring, system configuration, data history, device management, and nutrient control. Test results show that the TDS sensor has an RMSE of 8.84 ppm and a MAPE of 1.133%, the water temperature sensor has an RMSE of 0.218 °C and a MAPE of 0.671%, and the peristaltic pump has an RMSE of 0.53 mL and a MAPE of 1.117%. Automatic response testing was 100% successful across 10 scenarios. This system is capable of facilitating more precise and consistent management of hydroponic nutrients.