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Benchmarking MySQL and NoSQL Databases on Egovbench Application Nur Aini Rakhmawati; Muhammad Zuhri; Radityo Prasetianto Wibowo; Anwar Romadhon; Herdy Ardiansyah; Olive Khoirul
Journal of Information Technology and Its Utilization Vol 2, No 1 (2019)
Publisher : Sekolah Tinggi Multi Media (STMM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jitu.2.1.2080

Abstract

E-Government is a result of technological advances in the government field. E-government assessment is needed to encourage the development of e-government in a better direction. The e-Government assessment can be measured using the Egovbench application. Egovbench performs crawling to obtain information from related websites or social media. The process of crawling done by Egovbench produces extensive data, which reduced performance in data processing. Therefore, there is a need for a database solution that has the best performance such as high processing speed and small database size. This study examined the comparison between relational databases and non-relational databases based on selected metrics to obtain the most suitable database solution for Egovbench. The results show that the MySQL database has the advantage of complex query processing and the use of the database with the smallest storage space. MongoDB database has the advantage of low data transfer volumes. Couchbase database has the advantage of short and straightforward query processing with a high number. The evaluation results show that MySQL is more suitable for Egovbench needs, which is the best response time and query per second. MySQL outperformed the other two databases on backup and storage file sizes testing.
Enhancing Guest Security in Smart Hospitality: Face Recognition-Based Hotel Room Verification Using Haar Cascade Algorithm Putra, Adzanil Rachmadhi; Prayoga, Aji; Gumiwang, Zacky Yaser Malik; Karim, Mohammad Daniel Sulthonul; Wicaksono, Muhammad Galang Satrio; Faishol, Olive Khoirul Lukluil Maknun Al; Prisyanti, Affifiana
IJCONSIST JOURNALS Vol 7 No 1 (2025): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijconsist.v7i1.163

Abstract

This study aims to design and implement a hotel room verification system based on facial recognition using the Haar Cascade algorithm. The research was motivated by the growing need to enhance both security and service efficiency in the modern hospitality industry. The study was conducted through several stages, including facial image data collection using a webcam, preprocessing (RGB to grayscale conversion, image resizing, and cropping), model training, and real-time face recognition testing. The Haar Cascade algorithm was employed to detect facial features by utilizing Haar-like features combined with the Adaboost method to accelerate classification. The experimental results showed a recognition accuracy of 55% under varying lighting conditions and viewing angles. These findings indicate that the Haar Cascade algorithm performs adequately in detecting faces under ideal conditions, although further optimization is required to handle lighting variations and facial stability. This research contributes to the application of artificial intelligence technology in hotel security systems, with potential future improvement through the integration of deep learning methods to enhance accuracy and reliability in face verification. Keywords: face recognition, Haar Cascade, hotel room verification, facial detection, digital security.