Implementasi Convolutional Neural Network dengan Transfer Learning Inception-V3 untuk Membatasi Web Pornografi

Authors

  • Mukijo - Universitas Siber Asia, Indonesia
  • Syahid Abdullah Universitas Siber Asia, Indonesia
  • Riad Sahara Universitas Siber Asia, Indonesia

DOI:

https://doi.org/10.22441/incomtech.v15i3.30299

Keywords:

Deep Learning, Convolutional Neural Network, Transfer Learning, Klasifikasi Gambar, Pornografi

Abstract

Penyebaran pornografi melalui internet di masyarakat masih marak hingga saat ini dan dapat menimbulkan dampak negatif bagi penggunanya. Web pornografi semakin hari semakin berkembang dan bervariasi, demikian juga metode untuk mengaksesnya. Sistem yang efektif untuk membatasi peredaran pornografi menjadi kebutuhan penting untuk melengkapi sistem yang sudah ada. Convolutional Neural Network (CNN) merupakan sebuah algoritma klasifikasi yang dapat dimanfaatkan untuk mendeteksi web pornografi berdasarkan gambar yang ada pada halaman web tersebut. Algoritma CNN dipilih karena kemampuannya yang menjanjikan dalam mengekstraksi fitur gambar. Selain itu dengan mengimplementasikan transfer learning, proses pembuatan model bisa dilakukan dengan cepat, efektif dan efisien. Penelitian ini bertujuan untuk membangun model klasifikasi gambar dan mengimplementasikan model ke dalam aplikasi berbasis web di sisi pengguna. Metode yang digunakan dalam penelitian ini meliputi klasifikasi citra, transfer learning, web scrapping dan prototyping perangkat lunak. Eksperimen berhasil membangun model klasifikasi citra pornografi-non pornografi dengan akurasi 99.15%. Model kemudian diimplementasikan ke dalam aplikasi ekstensi browser Chrome agar dapat dilakukan klasifikasi secara otomatis. Pengujian terhadap aplikasi yang dibangun menunjukkan aplikasi bekerja cukup baik dan mampu memblokir sebagian besar halaman web dengan konten pornografi.

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Published

2026-01-02

How to Cite

[1]
M. -, S. Abdullah, and R. Sahara, “Implementasi Convolutional Neural Network dengan Transfer Learning Inception-V3 untuk Membatasi Web Pornografi”, InComTech, vol. 15, no. 3, pp. 228–242, Jan. 2026.

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