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All Journal Foristek JUSIFO : Jurnal Sistem Informasi JURNAL IQRA´ Sistemasi: Jurnal Sistem Informasi Mimbar Agribisnis: Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING Edukasi Islami: Jurnal Pendidikan Islam Technomedia Journal Islamic Management: Jurnal Manajemen Pendidikan Islam AT-TURAS: Jurnal Studi Keislaman Jurnal Sistem Cerdas JISIP: Jurnal Ilmu Sosial dan Pendidikan JUPE : Jurnal Pendidikan Mandala JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CCIT (Creative Communication and Innovative Technology) Journal EDUMATIC: Jurnal Pendidikan Informatika Jurnal Review Pendidikan dan Pengajaran (JRPP) ScientiCO : Computer Science and Informatics Journal EDUTEC : Journal of Education And Technology Khazanah Theologia Khazanah Theologia Jurnal Pendidikan Kewarganegaraan Al Marhalah Jurnal Teknik Informatika (JUTIF) JIHAD : Jurnal Ilmu Hukum dan Administrasi PERTANIAN TROPIK Proceeding Muhammadiyah International Public Health and Medicine Conference Journal Education and Government Wiyata Transcendent Journal of Mathematics and Applications Celebes Journal of Language Studies JER Moderation: Journal of Islamic Studies Review
Syahrullah Syahrullah
UIN Sunan Gunung Djati Bandung
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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

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Analysis of the Use of MTCNN and Landmark Technology to Improve the Accuracy of Facial Recognition on Official Documents Chandra, Ferri Rama; Ngemba, Hajra Rasmita; Hamid, Odai Amer; Lapatta, Nouval Trezandy; Hendra, Syaiful; Nugraha, Deny Wiria; Syahrullah, Syahrullah
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8814

Abstract

A face recognition system consists of two stages: face detection and face recognition. Detection of features such as eyes and mouth is important in facial image processing, especially for official documents such as identity cards. To ensure identification accuracy, this research applies facial landmark extraction technology and MTCNN (Multi-Task Cascaded Convolutional Neural Network). The purpose of this research is to evaluate the accuracy of MTCNN in detecting facial features at the Department of Population and Civil Registration (dukcapil) Palu City, using facial landmarks and waterfall methods as an application development methodology. The evaluation results show that MTCNN has high face recognition accuracy and good positioning ability regardless of what GPU in use as long have right CPU and System Operation. In comparison, the Viola-Jones algorithm is effective for high-speed applications, while SSD offers balanced performance with GPU device requirements for optimal performance. While MTCNN proved to be effective, challenges still exist, such as false positives and false negatives, especially in poor lighting conditions and extreme poses. Image and camera quality, including resolution and facial expression, also affects detection accuracy. These findings suggest that the application of MTCNN can improve face recognition accuracy for official documents, although it requires addressing existing challenges. With this technology, it is expected that errors in facial recognition can be minimized, resulting in more reliable data that meets the standards for issuing identity documents. This research contributes to the development of a more accurate and efficient face recognition system for personal identification applications.
Co-Authors Abdul Hadi Abdul Mahatir Najar Abdurrohman, Firman Muhammad Afiah, Nurul Anggun Afwah, Raden Agustinus Kali Aji Saputra, Andi Andi Hendra Anita Ahmad Kasim Ardiyansyah, Rizka Arskal Salim Atmowidjoyo, Sutardjo Bagaskara, Febrian Chrissma Baso Mukhlis Chairunnisa Ar. Lamasitudju Chandra, Ferri Rama Darman, Guna Dede Rosyada Deden Edi Delia, Fenita Deny Wiria Nugraha Dessy Santi Dharmakirti, Dharmakirti Dwi Shinta Angreni Dwimanhendra, Muhammad Rifaldi Dwiwijaya, Kadek Agus Edi, Deden Eva Nugraha Fadlilah, Dina Rahma Fahmi, Moh. Faisal Faisal Fajar Harguna Endra Putra Faldiansyah, Faldiansyah Filhaq, Raghib Hajra Rasmita Ngemba Hakim, Ibrahim Hamid, Odai Amer Hardjadinata, Hardjadinata Hastuti, Saptiyani Heru Budi Santoso Ihwan, Abib Raifmuaffah Iman Santoso Indrajaya, Muhammad Aristo Irsyadiah, Nur Irwan Irwan Jannah, Aulia Raudhatul Kartika, Rina Kasaedja, Tafania Natalia Kasim, Erni Kasmar, Kasmar Khasanah, Siti Uswatun Kunaenih, Kunaenih Laila, Rahma Lakatjinda, Adiatma Lamasitudju, Chairunnisa Lapatta, Nouval Trezand Luthfi, Atabik Magfirah, Magfirah Maharani, Wulan Maulidyani Abu Mohamad Irfan, Mohamad Mohammad Yazdi Pusadan Muhammad Afif Muhammad Muhammad Murmayani Mustika, Muhammad Fery Nahuda, Nahuda Nasrullah Nasrullah Nouval Trezandy Lapatta Noviantika, Noviantika Nuari, Feby Nabiilah Nur Khasanah Prakoso, Dicky Dwi Pramadinda, Alda Nur Pratama, Septiano Anggun Priska, Salsa Dilah Pusadan, Yazdi Putra, Fajar Harguna Endra Rahmah Laila Rasmita Ngemba, Hajra Rasmita, Hajra Ratnandari, Luluk Dwi Resnawati Rifki, Moh Rinianty, Rinianty Rizaldi, Andi Risfan Rizka Ardiansyah Ryfial Azhar, Ryfial Sani, Ilham Abdillah Sanusi, Gufran Saputra, Soni Adi Sau, Tenri Siti Khairunnisa, Siti Sukardi Weda, Sukardi Syaiful Hendra Syairozi, Ishak Syarif Firmansyah Syarifuddin Dollah Tenri Sau Triasni, Aprilia Wawagalang, A. Nolly Sandra Widiani, Ni Nengah Wijaya, Padma Wildan Imaduddin Muhammad, Wildan Imaduddin Wirdayanti Wongkar, Noel Marcell Jonathan Yanti, Wirda Yayan Sopyan Yuri Yudhaswana Joefrie Yusuf Anshori Zulkifli Zulkifli