Putri, SufiaAdha (2014) Deteksi dan Kuantifikasi Bakteri Tuberculosis Bacilli dengan Chamfer Matching. Sarjana thesis, Universitas Brawijaya.
Abstract
Tuberculosis (TB) menjadi masalah kesahatan utama di Indonesia dan sebagian negara di dunia. Diperkirakan di Indonesia terjadi 500.000 kasus dan 175.000 diantaranya meninggal dunia di setiap tahunnya. Salah satu pendeteksian seseorang terinfeksi TB adalah dengan melakukan pengecekkan terhadap dahak penderita, apakah terdapat bakteri Tuberculosis Bacilli atau tidak. Sampel dahak tersebut diwarnai dengan metode Ziehl-Neelsen. Salah satu solusi yang ditawarkan adalah pendektesian sampel dengan citra hasil mikroskop digital dan dengan program yang mampu mendekteksi sampel tersebut. Metode chamfer matching digunakan untuk mendeteksi dan mengkuantifikasi bakteri. Citra yang digunakan adalah citra hasil swab dahak pasien dengan bentuk .jpg dengan ukuran panjang 1600 px dan lebar 1200 px. Sistem telah mampu mendeteksi dan menguantifikasi bakteri dengan chamfer matching dengan rata-rata recall 0.695, presisi senilai 0.424, dan F-Measure senilai 0.494 dengan nilai threshold dan nilai pertambahan rotasi teroptimal 0.1 dan 5. Salah satu saran penulis adalah diperlukan penambahan fitur untuk mendeteksi bakteri seperti fitur-fitur geometri agar dapat meningkatkan hasil presisi.
English Abstract
Tuberculosis have been a major health problem in Indonesia and the other country in the world. Appoxiametly 500.000 cases and 175.000 have been died in every year. If someone have TB bacteria in his sputum, that means he is infected by TB. The sputum stained by Ziehl-Neelsen method. The solution that we offer is automatic detection bacteria using digital image from digital microscop and a program that can detect the bacteria. Chamfer matching method is used to detect and quantification the bacteria. The image that we used is stained sputum with ZN method in .jpg with 1600 px in witdh and 1200 px in length. The system was able to detect and quantify bacteria using chamfer matching with an average recall of 0.695, precision of 0.424, and F-Measure worth 0494 with the threshold value and the value-added rotation most optimize are 0.1 and 5. One of author’s suggestion is addition of features to detect bacteria such as geometry features in order to improve the precision results.
Other obstract
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| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | 004 |
| Uncontrolled Keywords: | Tuberculosis, deteksi bakteri, chamfer matching -Tuberculosis, Bacteria Detection, Chamfer Matching. |
| Subjects: | 000 Computer science, information and general works > 005 Computer programming, programs, data |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Hasbi |
| Date Deposited: | 07 Aug 2014 14:27 |
| Last Modified: | 23 Dec 2021 03:30 |
| URI: | http://repository.ub.ac.id/id/eprint/145942 |
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