Model Convolutional Neural Network (CNN) Custom Sequential untuk Klasifikasi Citra Ikan Hias Carassius Auratus pada Industri Akuakultur

Rodiah; Diana Tri Susetianingtias; Eka Patriya

doi:10.51454/decode.v5i3.1229

Authors

Rodiah Informatika Universitas Gunadarma
Diana Tri Susetianingtias Sistem Komputer Universitas Gunadarma
Eka Patriya Manajemen Universitas Gunadarma

DOI:

https://doi.org/10.51454/decode.v5i3.1229

Keywords:

Akuakultur, Carassius auratus, CNN, Custom Sequential, Ikan Hias

Abstract

Identifikasi varietas ikan hias Carassius auratus dengan keanekaragaman morfologi yang tinggi masih sering dilakukan secara manual, sehingga menimbulkan kesulitan bagi para pecinta ikan hias maupun pelaku akuakultur dalam membedakan jenisnya secara tepat. Kondisi ini menuntut adanya solusi berbasis teknologi yang mampu memberikan hasil identifikasi lebih cepat, praktis, dan presisi. Penelitian ini bertujuan untuk mengembangkan model klasifikasi citra menggunakan pendekatan Convolutional Neural Network (CNN) dengan arsitektur custom sequential sebagai sistem identifikasi visual otomatis. Tahapan penelitian dilakukan melalui pengumpulan 2.080 citra ikan yang mewakili delapan kelas varietas, dilanjutkan dengan proses pra-pemrosesan data agar citra siap digunakan pada tahap pelatihan model. Arsitektur CNN yang dibangun terdiri dari tujuh lapisan konvolusi dengan jumlah filter bertingkat mulai dari 32 hingga 256, disertai proses pooling, aktivasi ReLU, transformasi flatten, serta lapisan fully connected dengan mekanisme dropout untuk mengurangi overfitting, dan diakhiri dengan fungsi aktivasi softmax sebagai klasifikasi multi-kelas. Hasil eksperimen menunjukkan bahwa model mampu mengklasifikasikan citra ikan hias dengan tingkat akurasi mencapai 93,03% serta menghasilkan prediksi data uji secara konsisten tepat. Penelitian ini berkontribusi dalam menghadirkan pendekatan klasifikasi berbasis citra yang efisien, akurat, dan aplikatif, sehingga dapat mendukung proses identifikasi varietas ikan hias dalam industri akuakultur secara lebih modern dan berbasis teknologi.

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