KLASIFIKASI PENYAKIT RADANG PARU-PARU MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE DAN GREY LEVEL CO-OCCURRENCE MATRIX BERDASARKAN FOTO RONTGEN

Ardhi Atmaja Karo Karo, . (2023) KLASIFIKASI PENYAKIT RADANG PARU-PARU MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE DAN GREY LEVEL CO-OCCURRENCE MATRIX BERDASARKAN FOTO RONTGEN. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Pneumonia is a disease that has claimed many lives. Recently, pneumonia has become quite popular in society because one type of cause, namely the corona virus, has caused a pandemic in almost all countries. There are several causes of pneumonia, such as bacteria and viruses. The many types of causes require a method that can effectively classify the various types of causes of pneumonia. Therefore, this study will classify the various types of causes of pneumonia using the Support Vector Machine (SVM) algorithm based on X-rays of the lungs of patients affected by each type of cause of the disease. Pneumococcal disease was classified using the SVM algorithm as well as GLCM feature extraction. There are four GLCM parameters used in this study, namely dissimilarity, contrast, homogeneity, and correlation. Then a machine learning model is created using the feature extraction results and then classified using SVM. Obtained an accuracy value of 0.6, a precision value of 0.69, and a recall value of 0.92 from the classification model made.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 1910511066] [Pembimbing: Bayu Hananto] [Penguji 1: Didit Widiyanto] [Penguji 2: Theresia Wati]
Uncontrolled Keywords: Classification, Lung, SVM, X-Ray Photos
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: Ardhi Atmaja Karo Karo
Date Deposited: 23 Aug 2023 02:00
Last Modified: 23 Aug 2023 02:03
URI: http://repository.upnvj.ac.id/id/eprint/26299

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