Article Per Year (5 Year)
p-Index From 2021 - 2026
0.562
P-Index
This Author published in this journals
All Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal Ilmu Komputer dan Informatika
Kayla Amelia Putri
Universitas Negeri Medan
Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mathematics

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Smart Absen Implementation of a Facial Recognition-Based Student Attendance System Using the Haar Cascade Method and LBPH Frengki Alfredo Matondang; Sahara Lani Lestari; Dinda Syafitri; Kayla Amelia Putri; Hermawan Syahputra
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2301

Abstract

Manual attendance systems in higher education institutions are often hampered by inefficiency, data inaccuracy, and vulnerability to fraud such as proxy attendance. This study presents the design and implementation of Absen Smart, a face recognition-based attendance system developed using the Haar Cascade and Local Binary Pattern Histogram (LBPH) algorithms within the React.js and Flask frameworks. This system enables the automatic and real-time identification of students via a webcam without requiring additional hardware. Face detection is performed using the Haar Cascade classifier from OpenCV, while face recognition uses the LBPH Face Recognizer with a confidence threshold of 50. Testing was conducted with 28 registered students from the Computer Science Program at UNIMED, Class A, 2024 cohort. Functional evaluation results show that all seven core system features—including face detection, face recognition, duplicate prevention, automatic absence tracking, and Excel report generation—were successfully executed with a 100% success rate. The system achieved a facial recognition accuracy of 92.86%, with an average processing time of 1.2 seconds per verification. These results indicate that the proposed system is an effective, practical, and scalable solution for automating academic attendance in a university setting.
Implementasi Algoritma Merge Sort Berbasis Divide and Conquer untuk Pengurutan Data Nilai Akademik Mahasiswa pada Sistem Informasi Akademik Universitas Sahara Lani Lestari; Frengki Alfredo Matondang; Dinda Syafitri; Kayla Amelia Putri; Adidtya Perdana
Jurnal Ilmu Komputer dan Informatika | E-ISSN : 3063-9026 Vol. 2 No. 4 (2026): April - Juni
Publisher : GLOBAL SCIENTS PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study examines the application of the Merge Sort algorithm in the process of sorting student academic data within an academic information system (SIAKAD). The issue addressed is the suboptimal processing of academic data, which has the potential to cause delays and errors in the presentation of information. The objective of this study is to implement and evaluate the performance of the Merge Sort algorithm by comparing it with Bubble Sort and Insertion Sort. The method used is an experimental approach through testing on various dataset sizes, ranging from small to large scales, as well as under different data conditions, namely random, sorted, and reversed. Implementation was carried out using a Command Line Interface (CLI)-based application and a web interface to simulate real-world usage. The results of the study indicate that Merge Sort performs more efficiently and consistently than other algorithms, particularly on large datasets. Additionally, this algorithm possesses stable sort properties that maintain the relative order of data with the same values, making it more reliable for academic data processing.
Rancang Bangun Aplikasi E-Commerce Produk Kecantikan Dengan Sistem Rekomendasi Personal Berbasis Jenis Kulit Dan Undertone Dinda Syafitri; Sahara Lani Lestari; Kayla Amelia Putri; Deby Yandra Niska
BETRIK Vol. 17 No. 02 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/yyg9jb02

Abstract

The rapid growth of digital technology has encouraged small beauty businesses to shift toward digital platforms, yet many consumers still struggle to find products that match their skin condition. This study aims to develop a web-based e-commerce application called BeautyMatch, equipped with a Beauty Quiz feature using the Content-Based Filtering (CBF) method to provide personalized skincare product recommendations based on skin type and makeup recommendations based on undertone. The system was built using Node.js and Express.js for the backend, HTML5, CSS3, and JavaScript for the frontend, and MySQL as the database, with an Agile development approach. Functional testing using Black-Box Testing across 12 scenarios yielded a 100% success rate, while User Acceptance Testing (UAT) conducted on 50 respondents produced an average score of 4.48 out of 5. The results demonstrate that integrating the Beauty Quiz feature with the CBF algorithm effectively helps users find beauty products that best match their skin profile.
Co-Authors Adidtya Perdana, Adidtya Deby Yandra Niska Dinda Syafitri Frengki Alfredo Matondang Hermawan Syahputra Sahara Lani Lestari