Septian, Fillah (2025) Rancang Bangun Sistem Prediksi Waktu Penyiraman Tanaman Cabai Berbasis Iot Menggunakan Metode Moving Average. Undergraduate thesis, Politeknik Negeri Jember.
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Abstract
This study develops a predictive system for chili plant watering time based on the Internet of Things (IoT) using the Moving Average method. The primary issue in chili cultivation is suboptimal irrigation, either due to water deficiency or excess, which can affect plant growth and productivity. The developed system utilizes a soil moisture sensor connected to an ESP32 microcontroller to collect real-time moisture data. This data is then processed using the Moving Average method to predict the optimal watering time. The system is also equipped with monitoring and watering control features via a web-based interface, allowing users to set soil moisture thresholds and choose between automatic or manual watering modes. The test results indicate that this prediction system provides highly accurate watering recommendations. Additionally, the Moving Average method has proven effective in identifying soil moisture patterns and improving water use efficiency in chili cultivation.
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