Arasi, Muhammad Ardi Rizki (2024) Rancang Bangun Sistem Kontrol Temperatur, Kelembapan dan Intensitas Cahaya Buatan Pada Kumbung Jamur Tiram Menggunakan Metode Fuzzy Logic Terintegrasi Internet Of Things. Other thesis, Institut Teknologi Sepuluh Nopember.
![[thumbnail of 5009201061_Undergraduate_Thesis_Muhammad Ardi Rizki Arasi.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
5009201061_Undergraduate_Thesis_Muhammad Ardi Rizki Arasi.pdf - Accepted Version Restricted to Repository staff only until 1 October 2026. Download (5MB) | Request a copy |
Abstract
Penelitian ini mengembangkan sistem logika fuzzy yang mengintegrasikan monitoring dan kontrol menggunakan FLC dan Thingspeak. Integrasi perangkat keras melibatkan sensor intensitas cahaya BH1750, serta sensor suhu dan kelembaban DHT22. Aktuator yang digunakan termasuk dimmer untuk mengatur intensitas cahaya dan BTS 7960 untuk mengendalikan kelembaban melalui pompa. Sistem kontrol FLC dikombinasikan dengan IoT untuk meningkatkan kualitas budidaya jamur tiram. Sebelumnya, dilakukan kalibrasi dan karakterisasi sensor dan aktuator, diikuti dengan pengujian open loop dan closed loop untuk mengevaluasi respons sistem. Hasil penelitian menunjukkan bahwa FLC berhasil mengatur parameter fisik dengan akurasi yang diinginkan, yang terbukti melalui penyesuaian PWM sesuai dengan set point yang ditetapkan. Integrasi IoT dan sistem closed-loop berhasil mengontrol parameter fisik sesuai dengan kebutuhan yang telah ditetapkan. Pengembangan sistem kontrol fuzzy logic menunjukkan hasil,untuk kontrol kelembapan, waktu penyelesaian (settling time) adalah 6000 detik dengan waktu naik (rise time) 4680 detik, didampingi maksimum overshoot 5.8% dan error steady state 4%. Sementara itu, kontrol suhu menunjukkan waktu penyelesaian 11460 detik, rise time 10620 detik, dengan maksimum overshoot 3.7% dan error steady state 1%.
========================================================================================================
This study developed a fuzzy logic system that integrates monitoring and control using FLC (Fuzzy Logic Controller) and Thingspeak. The hardware integration included BH1750 light intensity sensor, and DHT22 temperature and humidity sensors. Actuators employed in the system comprised a dimmer for regulating light intensity and BTS 7960 for managing humidity through a pump. The FLC control system was combined with IoT (Internet of Things) to enhance the quality of oyster mushroom cultivation. Prior to implementation, calibration and characterization of sensors and actuators were conducted, followed by testing in both open loop and closed loop modes to evaluate system responsiveness. Research findings demonstrated that the FLC effectively regulated physical parameters with desired accuracy, as evidenced by PWM (Pulse Width Modulation) adjustments aligned with predetermined set points. Integration of IoT and closed-loop systems successfully controlled physical parameters according to predefined requirements. The development of the fuzzy logic control system yielded specific outcomes: for humidity control, settling time was approximately 6000 seconds with a rise time of 4680 seconds, accompanied by a maximum overshoot of 5.8% and a steady-state error of 4%. Meanwhile, temperature control indicated a settling time of 11460 seconds, rise time of 10620 seconds, with a maximum overshoot of 3.7% and a steady-state error of 1%. Overall, this research underscores the advancement achieved through integrating fuzzy logic control with IoT, offering significant potential for improving efficiency and precision in mushroom cultivation practices.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Kalibrasi, IoT (Internet of Things), Jamur tiram, monitoring dan kontrol Calibration, IoT (Internet of Things), Oyster Mushrooms, monitoring and Control |
| Subjects: | Q Science > QA Mathematics > QA9.64 Fuzzy logic Q Science > QA Mathematics > QA248_Fuzzy Sets Q Science > QC Physics > QC100.5 Measuring instruments (General) Q Science > QC Physics > QC271.8.C3 Calibration Q Science > QC Physics > QC271 Temperature measurements Q Science > QC Physics > QC389 Light--Transmission--Mathematical models. Q Science > QP Physiology > QP82.2.H8 humidity T Technology > T Technology (General) > T57.62 Simulation |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering |
| Depositing User: | Arasi Muhammad Ardi Rizki |
| Date Deposited: | 06 Aug 2024 01:32 |
| Last Modified: | 06 Aug 2024 01:32 |
| URI: | http://repository.its.ac.id/id/eprint/109889 |
Actions (login required)
 |
View Item |