ANALISIS PERBANDINGAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK DAN ALGORITMA MULTI-LAYER PERCEPTRON NEURAL DALAM KLASIFIKASI CITRA SAMPAH
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Abstrak
Menurut laporan bank dunia sampah merupakan salah satu permasalahan yang dihadapi dunia. Image clasification adalah salah satu bidang machine learning yang mampu melakukan klasikasi sampah berdasarkan jenisnya. Salah satu algoritma klasifikasi yang populer dan banyak digunakan adalah algoritma CNN yang merupakan algoritma deep learning. Pada penelitian ini kami akan melakukan analisis perbandingan kinerja algoritma CNN dengan algoritma MLP dalam melakukan klasifikasi jenis sampah. Dari penelitian yang kami lakukan, CNN mendapatkan performa yang lebih baik dimana hasil precision, recall, f1-score, dan accuracy sebesar 0,98 dan model CNN lebih efektif dalam melakukan klasifikasi sampah berdasarkan kelasnya.
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Referensi
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