Sistem Klasifikasi Kondisi Greenhouse Berdasarkan Hasil Monitoring Kadar Gas Menggunakan Logika Fuzzy

Ramadhani, Alif Gufron (2026) Sistem Klasifikasi Kondisi Greenhouse Berdasarkan Hasil Monitoring Kadar Gas Menggunakan Logika Fuzzy. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kualitas udara di dalam greenhouse cenderung mengalami penurunan akibat akumulasi gas dari aktivitas pertanian seperti penggunaan pupuk. Jika tidak terpantau, kondisi ini dapat membahayakan kesehatan serta keselamatan pekerja di dalamnya. Penelitian ini bertujuan mengimplementasikan sistem klasifikasi kondisi greenhouse dengan memanfaatkan teknologi Internet of Things (IoT) untuk memantau kualitas udara secara terus-menerus. Perangkat yang dikembangkan menggunakan mikrokontroler ESP32 sebagai pengendali utama yang dilengkapi dengan berbagai sensor gas, meliputi MQ-135 untuk Amonia (NH₃), MQ-7 untuk Karbon Monoksida (CO), MQ-4 untuk Metana (CH₄), MQ-136 untuk Sulfur Dioksida (SO₂), Fermion MEMS untuk Nitrogen Dioksida (NO₂), serta sensor SCD41 untuk Karbon Dioksida (CO₂). Selain itu, sistem mengintegrasikan sensor BME680 untuk pengukuran suhu, kelembapan, tekanan udara, dan VOC guna memastikan kelengkapan data lingkungan. Data hasil pengukuran dari sensor tidak hanya disajikan secara numerik, melainkan diproses lebih lanjut menggunakan metode logika fuzzy. Metode ini mengolah variasi data pembacaan kuantitatif dari gas menjadi sebuah keputusan kualitatif yang mengklasifikasikan kondisi udara ke dalam tiga kategori status yaitu aman, waspada, atau berbahaya. Seluruh hasil klasifikasi tersebut dikirimkan melalui jaringan internet dan divisualisasikan secara berkelanjutan pada sebuah dasbor informatif. Hasil pengujian menunjukkan bahwa transmisi data berjalan stabil dengan rata-rata waktu tunda (delay) sebesar 2,5 detik, dan algoritma fuzzy terbukti tepat dalam merespons fluktuasi emisi gas serta mampu mengklasifikasikan kondisi kualitas udara secara otomatis melalui visualisasi dasbor.
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Air Air quality inside greenhouse tends to deteriorate due to the accumulation of gases from agricultural activities such as the use of fertilizers. If left unmonitored, these conditions can endanger the health and safety of workers inside. This study aims to implement a greenhouse condition classification system using Internet of Things (IoT) technology to continuously monitor air quality. The developed device uses an ESP32 microcontroller as the main controller, equipped with various gas sensors, including the MQ-135 for ammonia (NH₃), the MQ-7 for carbon monoxide (CO), the MQ-4 for methane (CH₄), the MQ-136 for sulfur dioxide (SO₂), the Fermion MEMS for nitrogen dioxide (NO₂), and the SCD41 sensor for carbon dioxide (CO₂). In addition, the system integrates a BME680 sensor for measuring temperature, humidity, air pressure, and VOCs to ensure comprehensive environmental data. The measurement data from the sensors is not only presented numerically but is also further processed using fuzzy logic methods. This method processes variations in quantitative gas readings into a qualitative decision that classifies air quality into three categories: safe, caution, or hazardous. All classification results are transmitted via the internet and continuously visualized on an informative dashboard. Test results show that data transmission is stable, with an average delay of 2.5 seconds, and the fuzzy algorithm has proven effective in responding to fluctuations in gas emissions and is capable of automatically classifying air quality conditions through dashboard visualization.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Dashboard , ESP32, Greenhouse , Internet of Things, Klasifikasi, Kualitas Udara, Logika Fuzzy, Dashboard, ESP32, Greenhouse, Internet of Things, Classification, Air Quality, Fuzzy Logic.
Subjects:	Q Science Q Science > QH Biology Q Science > QH Biology > QH541 Ecology Q Science > QH Biology > QH541.15.T68 Toxicity testing
Divisions:	Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User:	Alif Gufron Ramadhani
Date Deposited:	10 Aug 2026 02:14
Last Modified:	10 Aug 2026 02:14
URI:	http://repository.its.ac.id/id/eprint/144254

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