KLASIFIKASI CITRA CACAR MONYET MENGGUNAKAN GRAY LEVEL CO-OCCURRENCE MATRIX DAN ALGORITMA LINEAR DISCRIMINANT ANALYSIS
Abstract
Monkeypox atau cacar monyet merupakan penyakit menular yang disebabkan oleh virus orthopoxvirus yang berasal dari hewan primata dan hewan pengerat. Berdasarkan data WHO sejak Januari 2022 sampai Juni 2023 terdapat 88.060 kasus terkonfirmasi cacar monyet dan 147 kasus kematian akibat cacar monyet yang tersebar di 112 negara di dunia. Penyebaran kasus cacar monyet yang terus meluas diberbagai negara, membuat cacar monyet menjadi salah satu penyakit yang banyak diperbincangkan. Pada penelitian ini dilakukan proses identifikasi citra lesi penyakit cacar monyet dan citra non-cacar monyet (campak dan cacar ayam) dengan melalui tahap preprocessing, tahap ekstraksi ciri GLCM dengan 7 fitur (contras, correlation, energi, homogenitas, entropi, mean dan variance), dan tahap pelatihan model pembelajaran mesin klasifikasi menggunakan algoritma LDA. Melalui proses evaluasi 10-fold cross validation didapakan hasil evaluasi model pembelajaran klasifikasi yang dibangun menunjukkan nilai performa rata-rata akurasi sebesar 80,55%, presisi 78%, recall 80%, dan spesificity 79%. Hasil ini menunjukkan bahwa model klasifikasi yang dikembangkan memiliki performa yang baik (good classification) dalam membedakan citra cacar monyet dan non-cacar monyet.
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