Rancang Bangun Sistem Informasi Smart Farming Berbasis Web Untuk Monitoring Kondisi Tanaman Hidroponik Menggunakan IoT dan Algoritma Decision Tree

Abstract

Hydroponic farming has emerged as an innovative solution to address land scarcity and food security challenges in urban areas. However, maintaining optimal nutrient concentrations and environmental conditions in hydroponic systems requires continuous monitoring and precise decision-making. This study aims to design and build a web-based smart farming information system for monitoring hydroponic plant conditions using IoT sensors and Decision Tree algorithm. The system integrates pH sensors, TDS (Total Dissolved Solids) sensors, and temperature sensors connected to a microcontroller for real-time data collection. The Decision Tree algorithm is employed to classify plant conditions into three categories: healthy, nutrient-deficient, and critical. The system was developed using the Waterfall methodology, consisting of requirements analysis, system design, implementation, testing, and maintenance. Data were collected through laboratory experiments with samhong mustard (Brassica sinensis L.) over a 30-day growth period. Testing was conducted using Black Box Testing and User Acceptance Testing (UAT) with 30 respondents. The results show that the Decision Tree algorithm achieves 94.5% accuracy in classifying plant conditions, the system successfully reduces nutrient monitoring time by 70%, and achieves a user satisfaction score of 4.38 (very good category). This study concludes that the integration of IoT and Decision Tree in a web-based information system is effective for hydroponic monitoring and can be implemented for precision agriculture.