Sistem Pengenalan Karat Pada Besi Menggunakan CNN
DOI:
https://doi.org/10.30736/jti.v11i1.1584Keywords:
Sistem Pengenalan Karat, Convolutional Neural Network (CNN), Korosi Besi, Deteksi Citra, KlasifikasiAbstract
Besi adalah material krusial dalam kehidupan modern, mulai dari konstruksi hingga peralatan dapur, dihargai karena kekuatan dan ketersediaannya. Namun, kelemahan mendasarnya adalah kerentanan terhadap korosi—proses yang dipicu oleh oksigen dan air—yang bisa menyebabkan kerugian besar jika tidak ditangani. Solusi yang diangkat dalam penelitian ini adalah menciptakan sebuah sistem pengenalan karat dini menggunakan Convolutional Neural Network (CNN) dengan arsitektur MobileNetV2, sebuah pendekatan yang menjanjikan akurasi tinggi dalam klasifikasi citra. Sistem ini dilatih menggunakan dataset kecil sebanyak 1279 gambar (terdiri dari 693 besi berkarat dan 586 tidak berkarat), Hasil eksperimen menunjukkan bahwa model mampu mencapai tingkat akurasi yang sangat tinggi, yakni 0.98 untuk kelas "Berkarat" dan 0.97 untuk kelas "Tidak Berkarat". Hasil ini menunjukkan bahwa model yang diusulkan efektif dalam mengenali karat pada besi, sehingga diharapkan dapat membantu dalam perawatan material besi sejak dini
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