— Based on the prior study, some shrimp ponds went bankrupt due to pond water quality monitoring is still not good. Many shrimps get sick and die for water quality monitoring still relies on laboratory checks and is rarely done because of financial problems. The purpose of this study is to develop a monitoring system of shrimp pond water quality especially for vannamei shrimp using an Internet of Things (IoT)-based device with a data logging method. The system role is to monitor the water condition, record sensor data, and provide water quality status of shrimp ponds based on water movement, turbidity of water, and water temperature. The data logger device uses a microcontroller named NodeMCU ESP8266 and two sensors namely the LDR sensor and the water temperature sensor dallas 18b20. The devices are connected to the internet and send all water quality monitoring data to Google's database service called Firebase. The results of the water quality monitoring can be accessed through an Android-based monitoring application that is built using Flutter framework which contains information. Keywords— Flutter Android; Internet of Things; Monitoring System; Water Quality
Berdasarkan pengalaman peneliti, banyak pengusaha budi daya tambak udang di Indonesia mengalami bangkrut, hal tersebut disebabkan karena biaya yang besar untuk satu kali cek laboratorium sehingga budi daya tambak udang mengalami gagal panen dikarenakan banyak udang yang terserang penyakit dan mati. Pada penelitian ini dibuat sebuah alat pemantauan kualitas air dari tambak udang vannamei menggunakan metode data logging berdasarkan nilai suhu air dan algoritma k-nearest neighbors untuk memprediksi kesehatan udang dan kondisi air tambak udang dari pergerakan air. Perangkat data logger menggunakan mikrokontroler NodeMCU ESP8266, sensor LDR, dan sensor suhu air Dallas DS18B20, kemudian data logger terhubung ke layanan basis data milik Google yaitu Firebase realtime database untuk menyimpan data pemantauan kualitas air. Terdapat layanan web services yang di hosting pada layanan website milik Heroku untuk menjalankan algoritma k-nearest neighbors menggunakan perintah httprequest dari aplikasi Android yang dibangun menggunakan framework Flutter. Aplikasi Flutter Android berisi widget monitoring, detail monitoring dan prediksi dengan tingkat akurasi yang diberikan sebesar 99.9 % untuk kesehatan udang serta 97.5 % untuk kondisi air.
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