Pengendalian Polusi Bau Limbah Peternakan Ayam Dengan Menggunakan Fuzzy Logic Controller

Sugiarto, Kharis (2019) Pengendalian Polusi Bau Limbah Peternakan Ayam Dengan Menggunakan Fuzzy Logic Controller. Masters thesis, Institut Teknologi Sepuluh Nopember.

Text 07111750040003-Master_Thesis.pdf Restricted to Repository staff only Download (9MB) | Request a copy

Abstract

Polusi bau dari limbah ternak menyebabkan kualitas udara yang buruk, sehingga dapat berdampak negatif terhadap kesehatan hewan maupun manusia di sekitar area peternakan. Penelitian ini merancang dan merealisasikan sistem kontrol bau limbah ternak menggunakan metode Fuzzy Logic Controller (FLC) yang diterapkan pada mikrokontroler Arduino Due. Sistem menggunakan sensor gas semikonduktor oksida logam dan metode Neural Network (NN) untuk mengidentifikasi serta mengukur tingkat bau limbah. Katup elektronik dengan nosel digunakan untuk menyemprotkan cairan Yucca schidigera sebagai zat penghilang bau. Hasil percobaan menunjukkan bahwa pengontrol logika fuzzy mampu menurunkan kadar polusi dari 27,59 ppm menjadi 3,95 ppm dalam waktu 4,5 menit. Efisiensi penurunan menggunakan Fuzzy Logic Controller mencapai 85,68%. Pada kondisi bau limbah ternak yang tidak dikendalikan, rata-rata kadar amonia (NH₃) dan hidrogen sulfida (H₂S) masing-masing sebesar 9,93 ppm dan 1,16 ppm. Sementara itu, pada kondisi yang dikendalikan, rata-rata kadar amonia dan hidrogen sulfida masing-masing sebesar 1,18 ppm dan 1,13 ppm. Penurunan kadar amonia dan hidrogen sulfida mencapai 88,11%. Selain itu, sistem kontrol ini mampu mengurangi penggunaan cairan Yucca schidigera hingga 25% dibandingkan dengan penyemprotan secara manual.
=================================================================================================================================
Pollution from livestock waste causes poor air quality, which can negatively affect both animals and humans in the surrounding area. This study designed and implemented a livestock waste odor control system using a Fuzzy Logic Controller (FLC) applied to an Arduino Due microcontroller. The system employs metal oxide semiconductor gas sensors and an Artificial Neural Network (ANN) to identify and measure livestock waste odor levels. An electronic valve equipped with nozzles was used to spray Yucca schidigera extract as a deodorizing agent. Experimental results showed that the fuzzy logic controller reduced pollution levels from 27.59 ppm to 3.95 ppm within 4.5 minutes, achieving a reduction efficiency of 85.68%. Under uncontrolled conditions, the average concentrations of ammonia (NH₃) and hydrogen sulfide (H₂S) were 9.93 ppm and 1.16 ppm, respectively. Under controlled conditions, the average concentrations decreased to 1.18 ppm for ammonia and 1.13 ppm for hydrogen sulfide. Overall, the reduction in ammonia and hydrogen sulfide concentrations reached 88.11%. In addition, the automated spraying system reduced the consumption of Yucca schidigera solution by 25% compared with manual application.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Fuzzy logic controller, neural network, polusi bau, sensor gas, yucca schidigera
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Electrical Technology > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User:	Kharis Sugiarto
Date Deposited:	05 Aug 2026 07:30
Last Modified:	05 Aug 2026 07:30
URI:	http://repository.its.ac.id/id/eprint/67357

Actions (login required)

View Item