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All Journal Jurnal Rekayasa Sistem Informasi dan Teknologi
Istanto, Nazla Abay Daud
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Computer Science & IT Decision Sciences, Operations Research & Management

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IMPLEMENTASI ALGORITMA FASTER R-CNN DALAM DETEKSI AKTIVITAS MEROKOK DI LINGKUNGAN KAMPUS Istanto, Nazla Abay Daud; Bagus Satrio Waluyo Poetro
Jurnal Rekayasa Sistem Informasi dan Teknologi Vol. 3 No. 1 (2025): Agustus
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jrsit.v3i1.2647

Abstract

The implementation of smoke-free area regulation in campus environment faces challenges in terms of supervision and enforcement. This study aims to determine the performance of deep learning-based object detection algorithm, namely Faster R-CNN, in detecting smoking activity in the campus area of ​​Universitas Islam Sultan Agung (UNISSULA). The dataset used consists of 1935 annotated images of smoking activity obtained from Roboflow, with data division of 85% training and 15% validation. The model was trained using Google Colab and tested based on evaluation metrics such as accuracy, precision, recall, and f1-score. The results show that Faster R-CNN has superior performance with the best evaluation value reaching 100% at a threshold of 0.5. These findings conclude that Faster R-CNN is suitable for use in a smoking activity detection system in a campus environment, especially in the context of detection accuracy and consistency.
Co-Authors Bagus Satrio Waluyo Poetro