Sistem Kendali Fuzzy Untuk Stabilisasi Suhu, Kelembapan, Dan Konsentrasi CO₂ Pada Silo Biji Jagung

Zakara, Yusuf (2025) Sistem Kendali Fuzzy Untuk Stabilisasi Suhu, Kelembapan, Dan Konsentrasi CO₂ Pada Silo Biji Jagung. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penyimpanan biji jagung dalam grain storage silo memerlukan kendali suhu, kelembapan relatif (RH), dan konsentrasi CO₂ yang ketat agar kualitas terjaga dan pertumbuhan mikroba ditekan. Sistem pemantauan manual yang biasa digunakan di industri pakan ternak belum mampu merespons perubahan lingkungan secara cepat dan adaptif. Penelitian ini merancang prototipe sistem kendali dengan menggunakan Internet of Things yang menggabungkan mikrokontroler ESP32, sensor DHT22 dan MH-Z19, serta pengendali fuzzy Sugeno tiga-masukan dua-keluaran dengan 27 fuzzy rule. Data suhu, RH, dan CO₂ diakuisisi lalu diproses dengan urutan fuzzifikasi–inferensi–defuzzifikasi sehingga menghasilkan sinyal kendali frekuensi blower (0–50 Hz) melalui Variable Frequency Drive dan sudut ventilasi servo DS5160 (4°–57°). Prototipe silo logam berkapasitas 350 kg digunakan sebagai studi kasus. Hasil eksperimen menunjukkan penurunan suhu rata-rata dari 30,50 °C menjadi 26,54 °C, kestabilan RH pada 70 %, serta penurunan CO₂ dari 1012 ppm ke 781 ppm dengan steady-state 540 ppm. Settling time tercatat 31 menit untuk suhu dan 99 detik untuk CO₂. Verifikasi terhadap simulasi MATLAB menghasilkan angka deviasi 0,07 (blower) dan 0,02 (ventilasi), menegaskan kesetaraan logika fuzzy pada sistem dengan model numerik. Seluruh data dikirim ke server MySQL dan divisualisasikan di dashboard web untuk pemantauan real-time. Temuan ini membuktikan bahwa kombinasi ESP32 dan fuzzy Sugeno efektif dan adaptif dalam menjaga kondisi ruang penyimpanan, dan siap diintegrasikan pada silo industri berskala lebih besar guna meningkatkan efisiensi penyimpanan dan menjaga kualitas biji jagung.
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Corn-kernel storage in grain silos demands strict control of temperature, relative humidity (RH), and CO₂ concentration to preserve quality and suppress microbial growth. Manual monitoring systems commonly used in the animal-feed sector cannot respond rapidly and adaptively to environmental changes. This study designs an IoT-based control prototype that integrates an ESP32 microcontroller, DHT22 and MH-Z19 sensors, and a three-input, two-output Sugeno fuzzy controller with 27 rules. Data on temperature, RH, and CO₂ are acquired every few seconds and processed through fuzzification, inference, and defuzzification to generate two control signals: blower frequency (0–50 Hz) via a Variable Frequency Drive and ventilation angle (4°–57°) via a DS5160 servo. A 350 kg metal-drum silo serves as the case study. Experiments reduce average temperature from 30.50 °C to 26.54 °C, maintain RH at 70 %, and lower CO₂ from 1012 ppm to 781 ppm, reaching a steady state of 540 ppm. Settling times are 31 min for temperature and 99 s for CO₂. Verification against MATLAB simulation yields deviations of only 0.07 for blower output and 0.02 for ventilation, confirming the accuracy of the embedded fuzzy logic. All data are transmitted to a MySQL server and visualised on a web dashboard for real-time monitoring. These results demonstrate that the ESP32–Sugeno fuzzy combination is effective, adaptive, and cost-efficient for maintaining silo microclimates and is ready to be scaled up to industrial-size silos to enhance storage efficiency and corn quality.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	ESP32, fuzzy logic, grain storage silo, IoT, jagung, corn
Subjects:	Q Science > QA Mathematics > QA39.3 Fuzzy mathematics Q Science > QA Mathematics > QA9.64 Fuzzy logic Q Science > QA Mathematics > QA248_Fuzzy Sets Q Science > QC Physics > QC271 Temperature measurements T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2692 Inverters T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2785 Electric motors, Induction. T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control
Divisions:	Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User:	Yusuf Zakaria
Date Deposited:	04 Aug 2025 09:15
Last Modified:	04 Aug 2025 09:15
URI:	http://repository.its.ac.id/id/eprint/125903

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