PERANCANGAN ALAT PENDETEKSI SUHU DAN POTENSIAL HIDROGEN PADA KOLAM BUDIDAYA DENGAN ALAT UKUR BERBASIS INTERNET OF THINGS - Anas Noor Firdaus; Arif Baswantara; Dhimas Susito; Yuni Ari Wibowo (Program Studi Ilmu Perikanan, Fakultas Ilmu dan Teknologi Hayati, Universitas Teknologi Sumbawa, 2024)
Traditional freshwater aquaculture is widely practiced in the community, both on a small and medium scale, in situ and ex situ, using earthen or concrete ponds as well as other supporting media. Generally, the water quality parameters that need to be maintained in freshwater aquaculture are temperature, hydrogen potential (pH), and dissolved oxygen. However, if the pond has sufficient circulation, temperature and pH become the minimum parameters that need to be checked and adjusted at certain times. The design of the detection device is tailored to the needs of the pond, where the detection device will be equipped with two sensors: a temperature sensor and a pH sensor. The sensors of this detection device will display data in the form of measurement results and send it in real-time, which will be stored in a data logger using the Internet of Things (IoT) system. Calibration needs to be performed on the device for measurement accuracy by displaying the average error and its standard deviation. The initial stage is the design of the casing for the land-based device, which is rectangular in shape with dimensions of 160x95x75 mm, and the device that is submerged in water, which is cylindrical with a height of 190 mm and a pipe diameter of 50.8 mm. This is followed by the design of the instrumentation on land, such as Arduino Nano, IoT ESP8266, SD Card, LCD, RTC with a power supply of 7.8 volts stepped down to 5 volts, and also in water, such as Arduino Nano, DS18B20 temperature sensor, and E201C pH sensor, continuing with the calibration and standard deviation calculations, it was found that the temperature had a value of 0.97% and pH 0.96%. The initial accuracy values for temperature and pH using the comparative method were as follows: the average error for the temperature sensor was 3% with an accuracy of 97%, and for the pH sensor, it was 3.55% with an accuracy of 96.45%. Lastly, the data is displayed on an IoT-based website.