PENERAPAN MULTIMODAL LATE FUSION UNTUK IDENTIFIKASI SITUS WEB JUDI ONLINE DI INDONESIA

RISKI, AZZAN DWI (2025) PENERAPAN MULTIMODAL LATE FUSION UNTUK IDENTIFIKASI SITUS WEB JUDI ONLINE DI INDONESIA. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Online gambling has become a serious issue in Indonesia over the past few years. Although the government has blocked millions of websites, new domains continue to appear, making automated detection highly necessary. This study proposes a Multimodal Late Fusion approach to detect online gambling websites in Indonesia by combining visual and textual information from web pages. The image classification model is built using EfficientNet-B3, while the text classification model uses IndoBERT. Both models are trained independently, and its prediction outputs are combined using a late fusion strategy. Experimental results show that the text-based model (IndoBERT) outperforms the image-based model. However, the fusion of both models achieves the best overall performance, with accuracy, precision, recall, and F1-score all reaching 99.71%. Although the fusion model delivers the highest performance, it also requires longer inference time compared to single-modality models. Therefore, implementing this system in real-world scenarios must consider the trade-off between accuracy and efficiency. Keywords: online gambling, multimodal late fusion, EfficientNet-B3, IndoBERT, website detection Perjudian online di Indonesia telah menjadi permasalahan serius selama beberapa tahun terakhir. Meskipun pemerintah telah melakukan pemblokiran jutaan situs, munculnya domain baru secara terus-menerus membuat deteksi otomatis menjadi sangat dibutuhkan. Penelitian ini mengusulkan pendekatan Multimodal Late Fusion untuk mendeteksi situs judi online di Indonesia berdasarkan kombinasi informasi visual dan tekstual dari halaman web. Model klasifikasi gambar dibangun menggunakan EfficientNet-B3, sementara model klasifikasi teks menggunakan IndoBERT. Kedua model dilatih secara independen, kemudian hasil prediksi digabungkan menggunakan strategi late fusion. Eksperimen menunjukkan bahwa model teks berbasis IndoBERT memberikan performa lebih baik dibandingkan model gambar. Namun, kombinasi keduanya melalui model fusion mampu menghasilkan performa tertinggi, dengan accuracy, precision, recall dan F1-score masing-masing sebesar 99.71%. Meskipun model fusion memberikan performa terbaik, waktu inferensinya relatif lebih tinggi dibandingkan model tunggal. Oleh karena itu, implementasi sistem ini dalam lingkungan nyata perlu mempertimbangkan keseimbangan antara akurasi dan efisiensi. Kata kunci: judi online, multimodal late fusion, EfficienNet-B3, IndoBERT, deteksi situs web

Item Type:	Thesis (S1)
Call Number CD:	FIK/INFO. 25 124
NIM/NIDN Creators:	41521010053
Uncontrolled Keywords:	judi online, multimodal late fusion, EfficienNet-B3, IndoBERT, deteksi situs web
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.3 Artificial Intelligence/Kecerdasan Buatan 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.7 Multimedia Systems/Sistem-sistem Multimedia > 006.75 Social Multimedia/Multimedia Social
Divisions:	Fakultas Ilmu Komputer > Informatika
Depositing User:	khalimah
Date Deposited:	06 Aug 2025 07:01
Last Modified:	06 Aug 2025 07:01
URI:	http://repository.mercubuana.ac.id/id/eprint/96609

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