<![CDATA[Agriculture is a sector that supports food security. Currently, agriculture faces serious challenges due to climate change, land limitations, and low technology adoption. This study aims to develop an Internet of Things (IoT)-based smart farming system integrated with artificial intelligence and run through edge computing. The prototype system is designed to collect real-time data on crop growth environments using pH, TDS, temperature, humidity, and water level sensors. The data is then processed locally using the Random Forest Regressor algorithm to determine optimal environmental conditions. Test results show that the model has very high accuracy in predicting humidity (R² = 0.99; RMSE = 0.65) and temperature (R² = 0.99; RMSE = 0.17), although there are still discrepancies in extreme conditions. The integration of IoT, AI, and edge computing has proven to improve energy efficiency, accelerate response times, and provide adaptive and affordable solutions in support of sustainable urban agriculture productivity.Keywords: Artificial Intelligence; Random Forest Regressor; IoT; Edge Computing AbstrakPertanian merupakan sektor yang mendukung ketahanan pangan, saat ini pertanian menghadapi tantangan serius akibat perubahan iklim, keterbatasan lahan, dan rendahnya adopsi teknologi. Penelitian ini bertujuan mengembangkan sistem pertanian cerdas berbasis Internet of Things (IoT) yang terintegrasi dengan kecerdasan buatan dan dijalankan melalui komputasi tepi. Prototipe sistem dirancang untuk mengumpulkan data lingkungan pertumbuhan tanaman secara real-time menggunakan sensor pH, TDS, suhu, kelembaban, dan tinggi permukaan air. Data kemudian diproses secara lokal menggunakan algoritma Random Forest Regressor untuk menentukan kondisi lingkungan optimal. Hasil pengujian menunjukkan model memiliki akurasi sangat tinggi pada prediksi kelembaban (R² = 0,99; RMSE = 0,65) dan suhu (R² = 0,99; RMSE = 0,17), meskipun masih terdapat selisih pada kondisi ekstrem. Integrasi IoT, AI, dan edge computing terbukti mampu meningkatkan efisiensi energi, mempercepat respons, serta memberikan solusi adaptif dan terjangkau dalam mendukung produktivitas pertanian perkotaan berkelanjutan. ]]>
