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All Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Ilmu Komputer dan Informatika
Dinda Syafitri
Universitas Negeri Medan
Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mathematics

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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.
Pengembangan Aplikasi Belanja Pintar Berbasis Linked List dengan Fitur Checklist dan Prioritas Juliana Gloria Sipayung; Dinda Syafitri; Muhammad Farrel Evan Yuri; Raja Ansel Haratama Sihombing
Jurnal Ilmu Komputer dan Informatika | E-ISSN : 3063-9026 Vol. 2 No. 2 (2025): Oktober - Desember
Publisher : GLOBAL SCIENTS PUBLISHER

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Abstract

Shopping activities in daily life require proper recording to stay organized and efficient. Manual recording using paper or simple applications often creates difficulties when updates are needed, such as adding new items, removing purchased goods, or rearranging priorities. This study develops a web-based Smart Grocery List application utilizing the linked list data structure. The research stages were carried out independently, starting from idea planning, application design, system implementation, and testing to ensure proper functionality. The application provides core features such as item addition, item deletion, and categorization into immediate and later groups. The results show that the system works according to user needs, supports more systematic shopping list management, and has the potential to be developed further as a practical digital solution.
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

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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.
Co-Authors Adidtya Perdana, Adidtya Frengki Alfredo Matondang Hermawan Syahputra Juliana Gloria Sipayung Kayla Amelia Putri Muhammad Farrel Evan Yuri Raja Ansel Haratama Sihombing Sahara Lani Lestari