Putri, Alfiani (2018) Implementasi Jaringan Saraf Tiruan untuk Pengenalan Plasmodium Falciparum pada Citra Sel Darah Merah. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
WHO (World Health Organization) mencatat sekitar 429.000 kasus malaria yang menyebabkan kematian di dunia. Hal ini dikarenakan ahli parasitologi yang sedikit di daerah endemik malaria, sehingga membuat pasien sulit untuk segera mendapat penanganan dini. Penelitian berjudul "Implementasi Jaringan Saraf Tiruan untuk Pengenalan Plasmodium Falciparum pada Citra Sel Darah Merah" telah melakukan analisis otomatis berdasarkan citra sel darah dalam mendiagnosa penyakit malaria dengan lebih cepat dan akurat. Pada penelitian ini digunakan metode jaringan saraf tiruan model Multi Perceptron, dengan dua tahapan. Tahap pertama, yaitu proses identifikasi plasmodium falciparum diawali dengan pengolahan citra digital untuk mendapatkan fitur area sel darah merah dan fitur area akromia sentral. Tahap kedua, yaitu proses deteksi sel darah stadium gametocyte berbentuk pipih. Proses deteksi gametocyte diawali dengan pre-processing, segmentasi dan operasi morphologi untuk mencari nilai eksentrisitas sel darah yang digunakan sebagai masukan JST Multi Perceptron. Nilai akurasi untuk identifikasi sel terinfeksi plasmodium falciparum pada stadium gametocyte dengan menggunakan JST Multi Perceptron adalah sebesar 92.3%.
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WHO (World Health Organization) recorded about 429,000 cases of malaria that cause death in the world. This is because a few parasitologists in the malaria endemic area, making it difficult for patients to get immediate treatment. The study, titled “Implementation of Neural Networks for Recognition of Plasmodium Falciparum on Red Blood Cells Images” has performed automatic analysis based on the image of blood cells in diagnosing malaria more quickly and accurately. In this research, Multi Perceptron model of artificial neural network using two stages. The first stage, which is the identification process plasmodium falciparum begins with digital image processing to obtain features of red blood cell area and features a central acromia area. The second stage, namely the process of blood cell staging gametocyte-shaped flat. The gametocyte detection process begins with pre-processing, segmentation and morphological operations to find the eccentricity of blood cells used as a Multi Perceptron JST input. The accuracy value for the identification of plasmodium falciparum infected cells at gametocyte stage using Multi Perceptron JST was 92.3%.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Pengenalan Plasmodium Falciparum, Jaringan Saraf Tiruan, Model Multi Perceptron |
| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science) |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Mathematics > 44201-(S1) Undergraduate Thesis |
| Depositing User: | alfiani putri |
| Date Deposited: | 09 Aug 2021 22:23 |
| Last Modified: | 09 Aug 2021 22:23 |
| URI: | http://repository.its.ac.id/id/eprint/53090 |
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