{"id":88401,"date":"2024-02-02T14:00:20","date_gmt":"2024-02-02T07:00:20","guid":{"rendered":"https:\/\/www.its.ac.id\/news\/?p=88401"},"modified":"2025-03-02T23:35:55","modified_gmt":"2025-03-02T16:35:55","slug":"mahasiswa-its-inovasikan-alternatif-deteksi-copd-melalui-cairan-ludah","status":"publish","type":"post","link":"https:\/\/www.its.ac.id\/news\/mahasiswa-its-inovasikan-alternatif-deteksi-copd-melalui-cairan-ludah\/","title":{"rendered":"Mahasiswa ITS Inovasikan Alternatif Deteksi COPD melalui Cairan Ludah"},"content":{"rendered":"
\"Anggota
Anggota tim, Muhammad Ardi Rizki Arasi, ketika melakukan pengukuran nilai permitivitas pada sampel saliva sebagai sumber data pada model\u00a0deep\u00a0learning<\/figcaption><\/figure>\n

Kampus ITS, ITS News \u2013 <\/strong><\/span>Seiring meningkatnya kasus kematian akibat Chronic Obstructive Pulmonary Disease<\/em> (COPD), diperlukan adanya sistem deteksi penyakit yang salah satunya menggunakan spirometer yang cukup kompleks. Hal tersebut menginspirasi tim mahasiswa Institut Teknologi Sepuluh Nopember (ITS)<\/a> untuk menginovasikan alternatif sistem deteksi COPD melalui perubahan nilai permitivitas pada cairan ludah yang disebut CoDetector.<\/p><\/blockquote>\n

COPD atau juga disebut Penyakit Paru Obstruktif Kronik (PPOK) merupakan penyakit peradangan pada paru-paru dalam jangka waktu lama yang sering menyerang perokok aktif dan pasif. Penderita COPD akan mengalami kerusakan pada bronkus dan selaput paru atau pleura. Guna mendeteksi COPD, Global Initiative for Chronic Obstructive Lung Disease<\/em> (GOLD) mempunyai sistem deteksi standar menggunakan spirometer.<\/p>\n

Ketua tim Fani Ahmad Refansah menuturkan, sistem deteksi COPD menggunakan spirometer dinilai kompleks karena memerlukan biaya yang mahal, waktu deteksi yang lama, dan memerlukan operator yang terampil. Bukan hanya itu, deteksi menggunakan spirometer tidak dapat diterapkan pada pasien yang mengalami eksaserbasi atau kondisi memburuknya gejala pernapasan. \u201cSehingga diperlukan alternatif sistem deteksi COPD untuk mengatasi kompleksitas tersebut,\u201d jelasnya.<\/p>\n

\"Salah
Salah satu anggota tim, Fabel Azzam Dedat, ketika melakukan fabrikasi sistem pendeteksi penyakit Chronic Obstructive Pulmonary\u00a0Disease\u00a0(COPD)<\/figcaption><\/figure>\n

Fani mengungkapkan, ada sebuah penelitian yang menyatakan penyakit COPD juga dapat dideteksi menggunakan komposisi sekresi mukosa. Hal tersebut terjadi karena penyakit COPD dapat memengaruhi kekentalan mukosa penderitanya. Selain itu, pasien COPD juga mengalami penurunan kadar aquaporin-5 pada saliva atau cairan ludah yang memengaruhi sifat permitivitasnya.<\/p>\n

Sifat permitivitas tersebut, imbuh Fani, merupakan kemampuan suatu benda menyimpan energi potensial listrik dalam pengaruh medan listrik. Nilai permitivitas ini dapat ditentukan dengan memanfaatkan konduktor pelat sejajar. Pada saat saliva diletakkan dalam suatu wadah berupa kuvet plastik yang berada di antara dua konduktor pelat sejajar, akan diperoleh nilai kapasitansinya. \u201cDengan menggunakan persamaan fisika, akan diperoleh nilai permitivitasnya,\u201d bebernya.<\/p>\n

Berdasarkan fakta tersebut, Fani dan tim di bawah bimbingan dosen Dr rer nat Ruri Agung Wahyuono ST MT berhasil menginovasikan alat deteksi COPD menggunakan biosensor kapasitif berdasarkan nilai permitivitas cairan ludah. Tak hanya itu, algoritma deep learning<\/em> pun diimplementasikan guna menganalisis data medis lain, seperti usia, gender, dan riwayat merokok pasien. \u201cPenerapan algoritma tersebut bertujuan untuk memperkuat diagnosis COPD,\u201d imbuhnya.<\/p>\n

\"Tim
Tim mahasiswa Departemen Teknik Fisika ITS yang berhasil menginovasikan alternatif deteksi Chronic Obstructive Pulmonary Disease (COPD) melalui\u00a0sekresi\u00a0mukosa<\/figcaption><\/figure>\n

Lewat kolaborasi Fani bersama Fabel Azzam Dedat, Muhammad Husein Az Zahro Saifulloh, M Ardi Riski Arasi, dan Laila Nurfitria Devi, alat detektor tersebut memiliki akurasi hingga 91,4 persen dan presisi mencapai 88,2 persen. Tak hanya itu, inovasi CoDetector tersebut juga telah membawa tim Program Kreativitas Mahasiswa kategori Karsa Cipta (PKM-KC) ITS ini berhasil meraih medali perak dalam Pekan Ilmiah Mahasiswa Nasional (Pimnas) 2023<\/a> lalu.<\/p>\n

Ke depannya, tim yang berasal dari Laboratorium Material Fungsional Maju, Departemen Teknik Fisika ITS<\/a> tersebut berharap agar inovasinya ini dapat terus dikembangkan akurasinya sehingga bisa menjadi alternatif detektor COPD. \u201cDengan biaya yang relatif terjangkau, semoga alat ini dapat dimanfaatkan oleh fasilitas kesehatan tingkat bawah,\u201d tutupnya penuh harap. (HUMAS ITS)<\/strong><\/p>\n

 <\/p>\n

Reporter: Mohammad\u00a0Febryan\u00a0Khamim<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

Kampus ITS, ITS News \u2013 Seiring meningkatnya kasus kematian akibat Chronic Obstructive Pulmonary Disease (COPD), diperlukan adanya sistem deteksi penyakit yang salah satunya menggunakan spirometer yang cukup kompleks. Hal tersebut menginspirasi tim mahasiswa Institut Teknologi Sepuluh Nopember (ITS) untuk menginovasikan alternatif sistem deteksi COPD melalui perubahan nilai permitivitas pada cairan ludah yang disebut CoDetector. COPD […]<\/p>\n","protected":false},"author":311,"featured_media":88403,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[14,3661,12,3689,26,60,1],"tags":[1947,1746,1274],"class_list":["post-88401","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-berita-utama","category-good-health-well-being","category-headline","category-innovation-infrastructure","category-kampus-kita","category-kkn-abmas","category-riset-dan-teknologi","tag-feb","tag-humas-its","tag-zan"],"yoast_head":"\nMahasiswa ITS Inovasikan Alternatif Deteksi COPD melalui Cairan Ludah - ITS News<\/title>\n<meta name=\"description\" content=\"Mahasiswa ITS menginovasikan alternatif sistem deteksi COPD melalui perubahan nilai permitivitas pada cairan ludah yang disebut CoDetector.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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