Perkembangan teknologi mendorong inovasi di berbagai bidang, termasuk pertanian. Internet of Things memungkinkan otomatisasi dan pemantauan real-time untuk meningkatkan efisiensi. Penelitian ini merancang sistem penyiraman otomatis dan monitoring bibit kakao berbasis IoT di PT Pesona Khatulistiwa Nusantara. Sistem ini menggantikan metode manual yang kurang efisien serta meningkatkan akurasi pemantauan kelembapan tanah, suhu udara, dan pH tanah. Penelitian ini menggunakan metode kuantitatif untuk menganalisis data sensor dan memastikan keakuratan sensor. Selain itu, pendekatan eksperimental digunakan dalam desain penelitian untuk mengatur RTC dan mengubah nilai ADC pada sensor. Sistem menggunakan NodeMCU ESP8266 dengan sensor kelembapan tanah, suhu (DHT22) serta sensor pH tanah. Data perolehan hasil sensor akan dikirim pada LCD dan Blynk untuk pemantauan via smartphone. Sistem memiliki tiga mode penyiraman yaitu : otomatis saat kelembapan < 40%, terjadwal dengan RTC (Real Time Clock) dan manual melalui Blynk. Proses Pengujian kalibrasi Sensor menggunakan Soil Survey Instrument sebagai alat perbandingan, dari hasil kalibrasi tesebut Sensor kelembapan tanah mendeteksi 0-30% pada kondisi tanah kering (DRY), 40-70% pada kondisi normal (NOR), dan 80-100% pada kondisi basah (WET+). Sensor DHT22 memiliki akurasi 99,36% dengan tingkat error 6,64%, sedangkan sensor pH tanah memiliki akurasi 89,31% pada kondisi asam (pH 3-4), 94,05% pada kondisi netral (pH 6-7), dan 93,56% pada kondisi basah (pH 9-10), dengan error maksimal 10,68%. Berdasarkan hasil Implementasi sistem yang dilakukan, pengujian dilakukan selama 9 jam (pukul 09:00 - 16:59) dengan pengambilan data setiap 30 menit dan pembacaan sensor setiap 2 detik hasil pengujian sistem rata-rata kelembapan tanah berada pada 65,25%, lalu pada penyiraman mode terjadwal pompa dapat aktif selama 15 detik berdasarkan hasil pengaturan RTC yang dimasukan pada program yaitu pukul 09.00, 12.00, 13.00 dan 16.00. Sensor pH menunjukkan pH normal (7,76) serta suhu udara rata-rata 31,44°C. sistem ini diharapkan dapat membantu petani dalam memantau kondisi kualitas bibit kakao serta pemeliharan berupa penyiraman secara otomatis.
Kata Kunci : Blynk, Internet of Things, Mikrokontroler, NodeMCU, Bibit Kakao.

Technological developments encourage innovation in various fields, including agriculture. The Internet of Things enables automation and monitoring in real time to increase efficiency. This research designed an automatic watering and monitoring system for cocoa seedlings loT at PT Pesona Khatulistiwa Nusantara. This system replaced less efficient manual methods and increased the accuracy of monitoring soil moisture, air temperature, and soil pH. This research used quantitative methods to analyze sensor data and ensure sensor accuracy. In addition, an experimental approach was used in the research design to regulate RTC and change the value of ADC on the sensor. The system applied NodeMCU ESP8266 with a soil moisture sensor, temperature (DHT22) as well as a soil pH sensor. Data obtained from the sensor results were sent to LCD And Blink for monitoring via smartphone. The system had three watering modes, namely: automatic when humidity was < 40%, scheduled with RTC (Real Time Clock), and manual through Blink. Sensor calibration testing process using Soil Survey Instrument as a comparison tool, from the calibration results the soil moisture sensor detected 0-30% in dry soil conditions (DRY), 40-70% under normal conditions (NOR), and 80-100% in wet conditions (WET+). Sensor DHT22 had 99.36% accuracy with a level error of 6.64%, while the soil pH sensor had an accuracy of 89.31% in acidic conditions (pH 3-4), 94.05% in neutral conditions (pH 6-7), and 93.56% in wet conditions (pH 9-10), with error maximum 10.68%. Based on the results of the system implementation, testing was carried out for 9 hours (09:00-16:59) with data collection every 30 minutes and sensor readings every 2 seconds. The system test results averaged soil moisture at 65.25%, then in scheduled watering mode the pump could be active for 15 seconds based on the results of the settings. RTC included in the program are 09.00, 12.00, 13.00 and 16.00. The pH sensor showed a normal pH (7.76) and an average air temperature of 31.44°C. This system is expected to help farmers monitor the condition of the quality of cocoa seeds and maintain them in the form of automatic watering. Keywords: Blink, Internet of Things, microcontroller, Node M, Cocoa Seeds.