Precision Aquaculture Integration with IoT Multi-Parameter Water Quality Sensor for Tambak Udang Farmers in Cirebon Coastal Area

Abstract

Shrimp aquaculture in the coastal tambak areas of Cirebon, West Java, faces persistent challenges related to fluctuating water quality driven by tidal dynamics and estuarine pollution, which frequently result in mass shrimp mortality events that devastate smallholder farmers' livelihoods. This study aimed to design, implement, and evaluate a low-cost IoT multi-parameter water quality monitoring system for vanamei shrimp (Litopenaeus vannamei) tambak farmers in Kecamatan Losari and Gebang, Cirebon. A mixed-methods research design was employed, integrating experimental hardware development, quantitative sensor validation, and qualitative usability assessment through a 30-day field deployment across five active pond units. The system utilized a NodeMCU ESP32 microcontroller integrated with pH, dissolved oxygen (DO), temperature (DS18B20), salinity, and turbidity sensors, transmitting real-time data via WiFi and LoRa to Firebase and ThingsBoard cloud platforms, accessible through an Android mobile application. Results demonstrated strong sensor accuracy across all parameters, pH (MAE ±0.20), DO (MAE ±0.27 mg/L), and temperature (MAE ±0.09°C), with system uptime of 94.7% and mean alert notification latency below five seconds. Farmer usability evaluation yielded a System Usability Scale (SUS) composite score of 78.4 (Grade B=Good). No mass mortality events occurred during the trial period, providing preliminary evidence of tangible aquaculture outcome improvement. The study concludes that affordable, participatory-designed IoT monitoring systems can effectively bridge the technology-adoption gap in smallholder coastal aquaculture, with recommendations for LoRa-primary connectivity, wet-season validation trials, and AI-driven predictive alert integration in future iterations.