Article Per Year (5 Year)
p-Index From 2021 - 2026
3.799
P-Index
This Author published in this journals
All Journal Teika Electro Luceat Jurnal CoreIT CogITo Smart Journal Jurnal Komtika (Komputasi dan Informatika) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknologi Dan Sistem Informasi Bisnis Informatics and Digital Expert (INDEX) J-Icon : Jurnal Komputer dan Informatika Riwayat: Educational Journal of History and Humanities Masyarakat: Jurnal Pengabdian Jurnal Komtika (Komputasi dan Informatika) Management of Education: Jurnal Manajemen Pendidikan Islam
Sihotang, Jay Idoan
Universitas Advent Indonesia
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Social Sciences Other

Published : 31 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 31 Documents
Search

 1   2   3   4 
Perancangan Sistem Konversi Mata Kuliah Berbasis Web Menggunakan OCR dan Gemini AI Andrew Jonathan Jordy Simbolon; Jay Idoan Sihotang
TeIKa Vol 16 No 2 (2026): Jurnal TeIKa Volume 16, Nomor 2, Oktober 2026
Publisher : Fakultas Teknologi Informasi - Universitas Advent Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36342/r0yr4s37

Abstract

In the era of digital transformation, academic services are required to be managed quickly, accurately, and in an integrated manner. However, the process of submitting course conversion requests may still be conducted manually, potentially causing recording errors, processing delays, and limited transparency of request status. This research aims to design and develop a web-based course conversion system utilizing Optical Character Recognition (OCR) and Gemini AI to automatically extract data from academic transcript documents. The development method used is Rapid Application Development (RAD), consisting of the Requirements Planning, User Design, Construction, and Cutover phases. The system was developed using React, TypeScript, Supabase, and PostgreSQL, with features including online submission, transcript upload, automatic data extraction, multi-level verification, and digital report generation. Black Box Testing showed that the main system functions operated according to the defined test scenarios. OCR testing on one academic transcript containing seven courses resulted in 20 of 21 data items being extracted correctly, with an overall accuracy of 95.24%. An error was found in the extraction of one course name, while the remaining data in the tested document were extracted correctly. These results indicate that the developed system can support the digital submission and verification of course conversion requests, while the extracted data should still be reviewed by users.
Co-Authors Abraham Butar-butar Andrew Fernando Pakpahan Andrew Jonathan Jordy Simbolon Arli Hope Sianturi Bangun, Winda Ebina Br Danielle Eudora Crystle Rampen Deca Kezia Caren Kurniawan Elmor Benedict Wagiu Erienika Meiling Lompoliu Gabriel Putra Advent Yakop Sihombing Ivan Royanto Hutabarat Jacko Pastorius Jessica Sabbathiny Buyung Jimmy H Moedjahedy Joe Yuan Mambu Jonathan, Bern Martin, Stanley Marvel Zefanya Yang Mendrofa, Seprianto Michelle Cantika Pontoan Oktiviana Perangin-angin Purba, Antonius Radja Boy Rawlson Yoshua Limbong Raymond Maulany Rianti Ruth Florenza Tambunan Ritonga, Jody Jeremi Hadrian Shaan, Peter Valerian Leony Bianto Wellyne Victoria I Winda Ebina Br Bangun Wiranto Horsen Silitonga Yang, Marvel Zefanya