Tomara Indrajaya
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Sistem Informasi Penerimaan Peserta Didik Baru (PPDB) Berbasis Web Menggunakan Bootstrap Tomara Indrajaya; Arsito Ari Kuncoro; Budi Hartono
Jurnal Manajemen Informatika & Teknologi Vol. 6 No. 1 (2026): Mei : Jurnal Manajemen Informatika & Teknologi
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/5zst1a74

Abstract

The traditional New Student Admissions (PPDB) procedure is frequently plagued by major issues, such as administrative responsibilities, data entry mistakes, and a lack of actual real-time public transparency (Rosmiati, 2020). By concentrating on the design and implementation of a responsive, web-based PPDB information system, this study seeks to resolve these challenges. The underlying technological solution involves using the Bootstrap framework (Susanto & Permata, 2020) to guarantee that the system's interface is strong, user-friendly, and performs at its best across all platforms. a range of user gadgets (Wijaya & Hadi, 2023). The system is developed using the Waterfall methodology, which includes a thorough needs analysis, system design, implementation using PHP and MySQL, and extensive testing (Setiawan & Cahyono, 2020). According to the research, the integrated system was successful in optimizing the registration process, which is a critical component of increasing administrative efficiency (Purnomo & Wibowo, 2024). Additionally, the use of Bootstrap resulted in a uniform and contemporary user interface, which greatly enhanced the experience for potential students (Pratama et al. , 2022). In conclusion, the web-based PPDB system that has been developed and is supported by the responsive capabilities of the Bootstrap framework provides a practical, open, and scalable solution for today's needs. instructional establishments. The integration of a document verification component utilizing machine learning should be the subject of future research.