Pengujian Metode Inception V3 dalam Klasifikasi Penyakit Kulit Dermatitis Atopik dan Psoriasis

Dwi Mei  Rita Sari; Desti Destiansari  Istinabiyah; Iga  Apria

doi:10.55338/jumin.v7i2.7874

Authors

Dwi Mei Rita Sari, Politeknik Negeri Sriwijaya, Indonesia
Desti Destiansari Istinabiyah, Politeknik Negeri Sriwijaya, Indonesia
Iga Apria, Politeknik Negeri Sriwijaya, Indonesia

DOI:

https://doi.org/10.55338/jumin.v7i2.7874

Keywords:

Inception V3, CNN, Deep Learning, Dermatitis Atopik, Psoriasis

Abstract

Penelitian ini bertujuan untuk menguji performa arsitektur Convolutional Neural Network (CNN) menggunakan metode Inception V3 dalam mengklasifikasikan dua jenis penyakit kulit, yaitu dermatitis atopik dan psoriasis. Metode Inception V3 digunakan sebagai feature extractor melalui pendekatan transfer learning untuk meningkatkan akurasi klasifikasi citra penyakit kulit. Dataset yang digunakan terdiri dari citra dermatitis atopik dan psoriasis yang telah melalui tahap pra-pemrosesan, meliputi resizing, augmentasi data, digitalisasi, dan feature scaling. Hasil pengujian terbaik menunjukkan bahwa metode Inception V3 mencapai akurasi sebesar 84%, dengan nilai presisi 82% dan recall 80%. Hasil ini menunjukkan bahwa arsitektur Inception V3 mampu memberikan performa klasifikasi yang baik pada kasus penyakit kulit dengan tingkat kemiripan visual yang tinggi.

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