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Syaiful Hendra
Information Technology Department, Engineering Faculty, Tadulako University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation

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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

 1 
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 - Ifandi A Djufri, Isdar Abdul Mahatir Najar Aimar Anand Alamsyah Alamsyah - Alda Nur Pradinda Amalia, Liza Andhyka, Andhyka Angraeni, Dwi Shinta Anita Ahmad Kasim Anjany, Ni Luh Verha Anugrah Aidin Yotolembah Anwar, Asriani Azizah Azizah Batara, Mohammad Chairunnisa Ar. Lamasitudju Chandra, Ferri Rama Delia, Fenita Deny Wiria Nugraha Dharmakirti, Dharmakirti Djohari, Riyandi Dwitama Dodu , Albertch Yordanus Erwin Dwi Shinta Angreni Dwi Wijaya, Kadek Agus Dwiwijaya, Kadek Agus Elyana Aulia Chandra Fadjryani, Fadjryani Hajra Rasmita Ngemba Hamid, Odai Amer Hardianti Hardianti, Hardianti I Gusti Ngurah Agung Kade Dwi Arsana Idhamsyahreza, Idhamsyahreza Indrajaya, Muhammad Aristo Ismail, Nurmasita Iswandi, A.Avri Junaidi Junaidi Junus Widjaja Kade Dwi Arsana, I Gusti Ngurah Agung Laila, Rahma Lakatjinda, Adiatma Lintine, Gabriella Bamba Ratih Liza Amalia Mandra Mohamad Irfan, Mohamad Muh Alif Alghifari Muh. Aristo Indrajaya Muhamad Aristo Indrajaya Muhammad Jindan Muhammad Nauval Daffa Ulhaq Muhammad Yazdi Ngemba, Hajra Nouval Daffa Ulhaq, Muhammad Nouval Trezandy Lapatta Nur Muliyana P. Dominggo, Nenita Penidas Fodinggo Tanaem Pradinda, Alda Nur Pratama, Moh. Asry Eka Pratama, Septiano Anggun Putra Ramadhan, Adjie Putri Febrina, Annisa Putri, Fadiah Suryani Rahmah Laila Raivandy, I Made Randhy Rasmita Ngemba, Hajra Rasmita, Hajra Rifai, Muhammad Fajar Risaldi Pata’Dungan, Adi Rizana Fauzi, Rizana Rizka Ardiansyah Rosmala Nur Ryfial Azhar, Ryfial Setiawan, Iman Siti Rahmawati Sitti Ainul Yakin Sri Kusumadewi Sukardi Sukardi Suryadi Hadi Suryani Putri, Fadiah Syahrullah Syahrullah Syahrullah Ulhaq, Muhammad Naufal Daffa Uswary, Jonathan Albert Vivi Peggie Rantung Winarta, Ardhiansyah Wirdayanti Wirdhayanti, Wirdhayanti Yuri Yudhaswana Joefrie Yusuf Anshori