Rancang Bangun Electronic Nose Untuk Deteksi Penyakit Asma Menggunakan Neural Network

Wahyu Wardani, Petty (2025) Rancang Bangun Electronic Nose Untuk Deteksi Penyakit Asma Menggunakan Neural Network. Bachelor thesis, Institut Teknologi Kalimantan.

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Abstract

Asma merupakan penyakit kronis pada sistem pernapasan yang ditandai oleh peradangan saluran udara, menyebabkan sesak napas, batuk, dan mengi. Di Indonesia, asma termasuk penyakit tidak menular dengan dampak ekonomi dan sosial yang signifikan. Diagnosis konvensional seperti spirometri dan FeNO memerlukan biaya tinggi, waktu lama, dan tenaga medis terlatih, sehingga kurang ideal untuk wilayah terpencil. Penelitian ini bertujuan mengembangkan sistem electronic nose (e-nose) berbasis neural network untuk mendeteksi asma secara cepat, hemat, dan non-invasif. Sistem ini memanfaatkan kombinasi sensor gas TGS-2602, MQ-135, dan TGS-2600 untuk mendeteksi senyawa organik volatil seperti amonia, hidrogen sulfida, dan karbon monoksida dalam napas pasien. Data VOC dianalisis menggunakan algoritma Multilayer Perceptron Neural Network (MLP-NN) dengan arsitektur 3 neuron pada input layer, 4 neuron pada hidden layer, dan 1 neuron pada output layer, serta metode feedforward dan backpropagation dengan fungsi aktivasi sigmoid. Hasil evaluasi menunjukkan sistem bekerja secara konsisten dengan akurasi sebesar 94,44% pada data train dan 97,92% pada data test pada tahap pelatihan awal. Saat diintegrasikan dengan perangkat keras, sistem memperoleh akurasi 91,67% (train) dan 92,68% (test), serta 90,62% (test data baru). Sistem e-nose ini berpotensi sebagai solusi deteksi dini asma yang efisien, portabel, dan terjangkau, terutama untuk daerah dengan keterbatasan akses layanan kesehatan Kata kunci: Asma, Electronic Nose, Mq-135, Neural Network, TGS-2602, VOC.

Item Type:	Thesis (Bachelor)
Subjects:	T Technology > T Technology (General)
Divisions:	Jurusan Teknologi Industri dan Proses > Teknik Elektro
Depositing User:	Petty Wahyu Wardani
Date Deposited:	11 Jul 2025 00:24
Last Modified:	11 Jul 2025 00:24
URI:	http://repository.itk.ac.id/id/eprint/24106

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