WIJAYAKUSUMA, PRIMA (2025) PERANCANGAN ALAT TERRAGROW : INTEGRATED PLATFORM FOR REAL-TIME PLANT MONITORING AND AUTOMATED WATERING SYSTEM WITH IOT AND FUZZY SUGENO ALGORITHM. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
The development of modern agriculture faces challenges related to land efficiency, time management, and increasingly complex plant nutrition needs. To address this, this research introduces TerraGrow, a smart farming platform based on Internet of Things (IoT) technology that supports automatic irrigation and realtime environmental monitoring. TerraGrow integrates Soil Moisture, air Humidity, air Temperature, and pH sensors managed by a NodeMCU ESP32 microcontroller. The system also uses the Fuzzy Sugeno algorithm for automated decision-making, with the Blynk IoT app as a cloud-based monitoring and control platform. The applied methodology combines a rule-based system with Fuzzy Sugeno control. The rule-based method is used to read soil moisture based on soil conductivity values, while the Fuzzy Sugeno algorithm is employed to activate the irrigation system based on data from soil moisture, temperature, and humidity sensors. Sensor data is processed and transmitted via IoT protocols, with the Blynk application providing a real-time monitoring interface. The system can receive notifications and access land status through mobile devices. Testing results indicate that the system is well-designed and delivers effective outcomes in accordance with the principles of resistive physics and ADC optimization using a rule-based method. The sensors are designed to operate according to specifications, and the Fuzzy Sugeno algorithm effectively optimizes soil moisture within the range of 60-80%. With the real-time monitoring features of the Blynk IoT platform, the research involving the design of the TerraGrow tool not only enhances agricultural productivity but also optimizes water resource usage and minimizes the risk of crop failure. Keywords : Smart Farming, Internet of Things, Fuzzy Sugeno, Wireless Sensor Networks, Soil Moisture Sensor Perkembangan sektor pertanian modern menghadapi tantangan efisiensi lahan, manajemen waktu, dan kebutuhan nutrisi tanaman yang semakin kompleks. Untuk mengatasi hal ini, penelitian ini merancang sebuah alat yang bernama TerraGrow, sebuah platform smart farming berbasis teknologi Internet of Things (IoT) yang mendukung otomatisasi irigasi dan pemantauan lingkungan secara realtime. TerraGrow mengintegrasikan sensor kelembapan tanah, kelembapan udara, suhu udara, dan pH yang dikelola oleh mikrokontroler NodeMCU ESP32. Sistem ini juga menggunakan algoritma Fuzzy Sugeno untuk pengambilan keputusan otomatis, dengan aplikasi Blynk IoT sebagai platform pemantauan dan kontrol berbasis cloud. Metode yang diterapkan menggabungkan sistem berbasis aturan dengan pengendalian algoritma Fuzzy Sugeno. Metode berbasis aturan digunakan untuk membaca kelembapan tanah dengan berdasarkan nilai konduktivitas tanah, sementara algoritma Fuzzy Sugeno digunakan untuk mengaktifkan sistem irigasi berdasarkan data sensor kelembapan tanah, suhu, dan kelembapan udara. Data sensor diproses dan dikirim melalui protokol IoT, dengan aplikasi Blynk menyediakan antarmuka pemantauan real-time. Sistem ini dapat menerima notifikasi dan mengakses status lahan melalui perangkat seluler. Hasil pengujian menunjukkan bahwa sistem ini berhasil dirancang dan memberikan hasil yang baik sesuai dengan konsep fisis resistif dan pengoptimalisasian ADC dengan metode rule-based. Sensor yang dirancang bekerja sesuai dengan spesifikasinya, dan algoritma Fuzzy Sugeno dapat mengoptimalkan kelembapan tanah pada rentang 60-80% secara efektif. Dengan fitur pemantauan real-time dari platform IoT Blynk, penelitian yang berisi perancangan alat TerraGrow ini tidak hanya meningkatkan produktivitas pertanian, tetapi juga mengoptimalkan penggunaan sumber daya air dan meminimalisir risiko gagal panen. Kata Kunci : Pertanian Cerdas, Internet of Things, Fuzzy Sugeno, Wireless Sensor Networks, Sensor Kelembapan Tanah
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