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All Journal JIK Jurnal Ilmu Komputer JOIV : International Journal on Informatics Visualization IKRA-ITH Informatika : Jurnal Komputer dan Informatika Jurnal Pengabdian Masyarakat AbdiMas IKRA-ITH ABDIMAS Simtek : Jurnal Sistem Informasi dan Teknik Komputer JATI (Jurnal Mahasiswa Teknik Informatika) JI-Tech Jurnal Teknologi Informatika dan Komputer Journal of Social Research Journal of Comprehensive Science Jurnal Indonesia Sosial Sains Eduvest - Journal of Universal Studies Innovative: Journal Of Social Science Research Kohesi: Jurnal Sains dan Teknologi
Nixon Erzed
Sekolah Tinggi Teknologi Informasi NIIT
Aerospace Engineering Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Neuroscience Physics Public Health Social Sciences Other

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Journal : Journal of Comprehensive Science

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Implementasi Teknologi OCR dan Model LLM untuk Otomatisasi Pengisian Formulir Berdasarkan Dokumen Sertifikat untuk Universitas Esa Unggul Bekasi Samuel Angelino Simanjorang, Calvin; Erzed, Nixon
Journal of Comprehensive Science Vol. 4 No. 3 (2025): Journal of Comprehensive Science (JCS)
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/jcs.v4i3.3061

Abstract

Document administration at educational institutions, such as Esa Unggul University, often faces challenges in filling out forms manually, making them time-consuming and prone to human error. This research develops a form filling automation system based on Optical Character Recognition (OCR) and Large Language Model (LLM) technology. OCR technology is used to extract text from certificate documents automatically, while LLMs are used to understand context and identify specific information, such as names, activity titles, and execution dates. The research method used a waterfall approach, with Fishbone Diagram analysis to identify the root of the problem and system design using General OCR Theory (GOT) for text extraction as well as the Llama 3 model for data interpretation. The system is tested with a variety of certificate formats to evaluate the level of accuracy and efficiency compared to manual methods. The results showed that the system was able to achieve an accuracy of more than 90%, reduce input errors, and speed up the form filling process. He concluded that the developed system has succeeded in improving the efficiency, accuracy, and reliability of the administrative process at Esa Unggul University. This system is expected to be implemented to support more efficient and accurate campus administration, as well as be the basis for the development of document automation technology in the future.
Co-Authors Aan Sulistyo Ahmad, Ahluddin Saiful Alfiana, Rita Andrew Ercole, Bradley Anggun Rospita Annisa Fitria Antara, Nyoman Putra Badie Uddin Binastya Anggara Sekti BUDI TJAHJONO Evi Martaseli Firmansyah, Gerry Freddy Harris, Freddy Gusti, Aldo Prima Hendry Gunawan, Hendry Herwanto, Agus Hidayah, Taufika Iswahyudi, Raden Teddy Iwan Setiawan Jefry Sunupurwa Asri Lisasih, Nin Yasmine Mooduto, Hanriyawan Adnan Muhlasin, Muhlasin Nizirwan Anwar Nugroho Budhisantosa Prasetio, Martin Segal Putra Rahman, Arizki Rahaman, Mosiur Rahmahani, Adhining Prabawati RR. Ella Evrita Hestiandari Samuel Angelino Simanjorang, Calvin Sembiring, Rinawati Setiawati, Popong Sheha, Kholid Nur Suhendar Suhendar, Suhendar Trihanggara, Galuh Utami, Aliph Putri Wahyudi, Endik Wasahua, Idris Widyawan, Tri Ismardiko Yudhi, Muhammad Febri Yulfitri, Alivia Yulhendri Yulhendri Zaki Nurfadiilah, Alif