Penerapan Grey Wolf Optimizer Dan Ensemble Learning Voting Untuk Mendeteksi Penyakit Paru-Paru Manusia Menggunakan Citra Chest X-Ray

Putra, Al Fatoni Nugroho (2022) Penerapan Grey Wolf Optimizer Dan Ensemble Learning Voting Untuk Mendeteksi Penyakit Paru-Paru Manusia Menggunakan Citra Chest X-Ray. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penyakit paru-paru pada manusia merupakan salah satu penyakit yang berbahaya dan telah mengakibatkan banyak korban jiwa di dunia. Hasil foto sinar X (X-Ray) pada paru-paru merupakan salah satu solusi untuk bisa mengidentifikasi jenis penyakit yang diderita oleh pasien. Teknologi pengolahan citra digital merupakan salah satu teknologi yang berkembang sangat pesat untuk dapat menganalisis suatu hasil foto atau citra. Grey Wolf Optimizer adalah salah satu metode seleksi fitur yang sangat penting pada prapemrosesan dikarenakan dapat menyeleksi beberapa fitur yang tidak relevan pada data ekstraksi fitur sehingga dapat juga meningkatkan accuracy rate dan mengurangi process time. Multi Support Vector Machine, Extreme Learning Machine, dan Gaussian Process Classification merupakan metode klasifikasi yang digunakan sebagai kombinasi masukan dalam metode Ensemble Learning Voting sehingga menghasilkan prediksi final dengan cara pemungutan suara. Pada penelitian tugas akhir ini diterapkan Grey Wolf Optimizer dan Ensemble Learning Voting untuk mendeteksi penyakit paru-paru menggunakan citra Chest X-Ray. Terdapat 3 jenis penyakit yang diidentifikasi, yaitu covid-19, pneumonia, dan tuberkulosis. Tingkat akurasi tertinggi yang diperoleh saat menerapkan Grey Wolf Optimizer dan Ensemble Learning Voting adalah sebesar 95%
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Lung disease in humans is one of the most dangerous diseases and has resulted in many deaths in the world. The results of X-rays (X-Ray) on the lungs are one solution to be able to identify the type of disease suffered by the patient. Digital image processing technology is a technology that is developing very rapidly to be able to analyze a photo or image. Gray Wolf Optimizer is a feature selection method that is very important in preprocessing because it can select some irrelevant features in the feature extraction data so that it can also increase the accuracy rate and reduce process time. Multi Support Vector Machine, Extreme Learning Machine, and Gaussian Process Classification are classification methods that are used as a combination of inputs in the Ensemble Learning Voting method to produce final predictions by voting. In this final project, Gray Wolf Optimizer and Ensemble Learning Voting are applied to detect lung disease using Chest X-Ray images. There are 3 types of diseases identified, namely covid-19, pneumonia, and tuberculosis. The highest level of accuracy obtained when applying the Gray Wolf Optimizer and Ensemble Learning Voting is 95%

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Penyakit Paru-Paru, X-Ray, Pengolahan Citra Digital, Grey Wolf Optimizer, Metode Ensemble Learning Voting, Lung Disease, X-Ray, Image Processing, Grey Wolf Optimizer, Ensemble Learning Voting Method
Subjects:	Q Science > QA Mathematics > QA401 Mathematical models.
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	22 Oct 2025 02:04
Last Modified:	22 Oct 2025 02:04
URI:	http://repository.its.ac.id/id/eprint/128657

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