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All Journal JETT (Jurnal Elektro dan Telekomunikasi Terapan) JOIV : International Journal on Informatics Visualization JOURNAL OF ELECTRICAL AND SYSTEM CONTROL ENGINEERING Jurnal Ilmiah FIFO TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika IJAIT (International Journal of Applied Information Technology) Journal of Computer, Electronic, and Telecommunication (COMPLETE) Jurnal Ilmiah Teknik Elektro eProceedings of Engineering Jurnal Ilmiah Agroust
Suryo Adhi Wibowo
Universitas Telkom
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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Journal : IJAIT (International Journal of Applied Information Technology)

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Generating Information of URL Based on Web Scraping Using YOLOv3 Face Recognition Technology Lulud Annisa Ainun Mahmuddah; Suryo Adhi Wibowo; Gelar Budiman
IJAIT (International Journal of Applied Information Technology) Vol 05 No 02 (November 2021)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v5i02.3910

Abstract

Artificial Intelligence (AI) is a system developed to learn and apply human intelligence. Some technologies produced from the development of Al are face recognition and web scraping. Face recognition is used for identifying or verifying the identity of an individual using their face. The result of a face recognition process can be used to collect information on the internet with a web scraping technique. This paper proposes a face recognition model and web scraping system using You Only Look Once (YOLO) object detection method and Request library written in Python. The face recognition model performed fine-tuning in two hyperparameters, which are learning rate and step training. The proposed model for face recognition is using custom datasets that contain 8000 images divided into 5 classes and evaluated using the Mean Average Precision (mAP) performance parameter, while the web scraping system is evaluated using the precision rate parameter. From the test results, the best configuration was obtained at a learning rate of 0.0001 and step training of 10K. The highest mAP that is achieved is 0.90 with a recall and precision value of 0.75 for each, while the average precision rate is 0.87. The results of this paper are expected to contribute to the development of biometric security technology.
Co-Authors Agniya Tazkiya Aulia Agus Pratondo Akhmad Yusuf Nasirudin Aldo Tripolyta Alvaro Septra Dominggo Nauw Angga Rusdinar Anky Aditya P Annisa Istiqomah Atina Nur Azizah Bambang Hidayat Bambang Hidayat Bambang Setia Nugroho Casi Setianingsih Dany Eka Saputra Devita Rahma Apriliani Dini Himmah Al Aliyyah Al Aliyyah Djoko Heru Pamungkas Dwiki Kurniawan Dyah Avita Sari Fahmi Oscandar Fahmi Oscandar Faiz Nashrullah Farah Hana Kusumaputri Felix Corputty Fiky Yosef Suratman Fityanul Akhyar Gelar Budiman Hanaluthfina Nurhadiati Hashfi Fadhillah Iwan Iwut Tritoasmoro JANGKUNG RAHARJO Koredianto Usman Kusuma Nindia Rizki Ledya Novamizanti Liyana Faiza Lulud Annisa Ainun Mahmuddah Lyra Vega Ugi Muhammad Alief Hidayah Baso Muthia Saada Nadya Sindi Safitri Oriza Intani Prasaja Wibawa Utama Putri Utami Hafgianti Raditiana Patmasari Ricky Hilmi Sudrajad Rissa Rahmania Rissa Rahmania Rissa Rahmania Rissa Rahmania Rita Purnamasari Tembang Florian Falah Viky Premeita Mitayani Vivian Alfionita Sutama Wiwit Ratri Wulandari Yacobus Sunaryo Yurika Ambar Lita Yuti Malinda