RANCANG BANGUN SISTEM PEMANTAUAN DAN KONTROL INTENSITAS CAHAYA SERTA PENYIRAMAN TANAMAN OTOMATIS PADA GREENHOUSE BERBASIS INTERNET OF THINGS [DESIGN AND CONSTRUCTION OF A SYSTEM FOR MONITORING AND CONTROLLING LIGHT INTENSITY AND AUTOMATIC WATERING OF PLANTS IN A GREENHOUSE BASED ON THE INTERNET OF THINGS]

Abstract

Agriculture is an important sector in a country's economy, but with the increasing population growth, the challenges in agriculture are becoming increasingly complex. One of the main challenges is maintaining the quality and quantity of plants product. Greenhouses are an effective solution to control the plant growth environment. However, environmental management in conventional greenhouses today requires a lot of labor and high costs. To address this challenge, there is an urgent need to develop an automation system capable of monitoring plant conditions and controlling the light intensity and watering of plants in greenhouse plants. The system uses Internet of Things (IoT) technology with an ESP32 Devkit v1 microcontroller module for automatic and real-time monitoring and control of the plant growth environment. Through the implementation of carbon dioxide (CO₂), light intensity, soil pH, and soil moisture quality monitoring systems along with automatic control of light intensity and watering of plants in greenhouses, it is hoped that agricultural productivity can be increased. Sensor data were taken and read by the microcontroller which is then displayed and sent to 4 platforms, namely Serial Monitor, LCD OLED, website Platform, and Google Sheets. The microcontroller successfully reads the data of the installed sensors and sent in real-time to multiple platforms. These test data provide a concrete picture of the performance of the developed greenhouse plant monitoring and control system. The results of verification to commercial measuring instruments showed that the LDR sensor had an average error of 1.15%, the CO₂ sensor had an error of 0.86%, the soil pH sensor had an error of 3.22%, and the soil moisture sensor had an error of 1.46%. Functional tests show that the system responds to turn on the growlight when the light intensity drops to 500 Lux and turn on the pump when the soil moisture drops below 40% according to the threshold points setting.

Bahasa Indonesia Abstract:

Pertanian adalah sektor penting dalam perekonomian suatu negara, namun dengan pertumbuhan penduduk yang terus meningkat, tantangan dalam pertanian menjadi semakin kompleks. Salah satu tantangan utama adalah menjaga kualitas dan kuantitas hasil tanaman. Greenhouse adalah solusi efektif untuk mengendalikan lingkungan pertumbuhan tanaman. Namun, pengelolaan lingkungan dalam greenhouse konvensional saat ini memerlukan banyak tenaga kerja dan biaya yang tinggi. Untuk mengatasi tantangan ini, ada kebutuhan mendesak untuk mengembangkan sistem otomatis yang mampu memantau kondisi tanaman dan mengontrol intensitas cahaya serta penyiraman tanaman pada greenhouse. Sistem ini menggunakan teknologi Internet of Things (IoT) dengan mikrokontroler ESP32 Devkit v1 untuk pemantauan dan kontrol otomatis realtime pada lingkungan pertumbuhan tanaman. Melalui implementasi sistem pemantauan konsentrasi karbon dioksida (CO₂), intensitas cahaya, pH tanah dan kelembapan tanah serta kontrol otomatis intensitas cahaya dan penyiraman tanaman otomatis, diharapkan produktivitas pertanian dapat ditingkatkan. Data-data sensor diambil dan dibaca oleh mikrokontroler yang kemudian ditampilkan dan dikirimkan ke 4 platform, yaitu Serial Monitor, LCD OLED, platform website, dan Google Spreadsheet. Mikrokontroler berhasil membaca data-data sensor yang terpasang, dan mengirimkan secara realtime pada platform-platform tersebit. Data-data pengujian ini memberikan gambaran konkret tentang kinerja sistem pemantauan dan kontrol tanaman greenhouse yang dikembangkan. Hasil verifikasi terhadap alat ukur komersial menunjukkan sensor LDR mempunyai kesalahan sebesar 1.15%, sensor CO₂ mempunyai kesalahan sebesar 0.86%, sensor pH tanah mempunyai kesalahan 3.22%, sensor kelembaban tanah mempunyai kesalahan 1.46%. Uji fungsional menunjukkan sistem memberi respon menyalakan lampu growlight saat intensitas cahaya turun sampai 500 Lux dan menyalakan pompa saat kelembaban tanah turun di bawah 40% sesuai dengan setting titik threshold yang diberikan.