IMPLEMENTASI FASTER R-CNN DAN OCR DENGAN PENDEKATAN NATURAL LANGUAGE PROCESSING UNTUK DETEKSI IKLAN JUDI ONLINE

Maldini, Andry Syva (2025) IMPLEMENTASI FASTER R-CNN DAN OCR DENGAN PENDEKATAN NATURAL LANGUAGE PROCESSING UNTUK DETEKSI IKLAN JUDI ONLINE. Undergraduate thesis, Universitas Pembangunan Nasional Veteran Jawa Timur.

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Abstract

The proliferation of online gambling advertisements on social media has increasingly adopted covert strategies such as visual watermarks and textual euphemisms, making manual content moderation ineffective. This research aims to develop an automated detection system for identifying online gambling advertisements using an end-to-end artificial intelligence approach. The methodology involves object detection using Faster R-CNN (ResNet-50 + FPN), text extraction using Transformer-based Optical Character Recognition (TrOCR), and semantic classification using BERT-based Natural Language Processing. The dataset was collected and annotated manually, followed by augmentation using Roboflow. Evaluation results show that the Faster R-CNN model achieved a mAP@0.50 of 98.1%, TrOCR recorded a Character Error Rate (CER) of 4.6% and a Word Error Rate (WER) of 29%, while the BERT classification model achieved 99% accuracy, with high precision and recall for both classes. These components were integrated into a Flask-based web pipeline, allowing users to upload images or short videos for automatic detection and classification. The system effectively detects both explicit and obfuscated gambling advertisements and provides a practical tool to support content moderation efforts on digital platforms.

Item Type:

Thesis (Undergraduate)

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	Saputra, Wahyu Syaifullah Jauharis	NIDN0725088601	wahyu.s.j.saputra.if@upnjatim.ac.id
Thesis advisor	Prasetya, Dwi Arman	NIDN0005128001	arman.prasetya.sada@upnjatim.ac.id

Subjects:

H Social Sciences > HM Sociology
H Social Sciences > HN Social history and conditions. Social problems. Social reform
Q Science > QA Mathematics > QA76.6 Computer Programming

Divisions:

Faculty of Computer Science > Departemen of Data Science

Depositing User:

Andry Syva Maldini

Date Deposited:

05 Aug 2025 07:58

Last Modified:

05 Aug 2025 07:58

URI:

https://repository.upnjatim.ac.id/id/eprint/41565