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All Journal Journal of Information Systems and Technology Research Sistem Pendukung Keputusan dengan Aplikasi
Navea, Roy Francis
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Direct implementation of AI-Based Facial Recognition for ITSI students Prayogi, Andi; Navea, Roy Francis; Dian, Rahmad; Pane, Muhammad Akbar Syahbana; Siregar, Ratu Mutiara; Sugianto, Raden Aris; Simbolon, Hasanal Fachri Satia
Journal of Information Systems and Technology Research Vol. 3 No. 3 (2024): September 2024
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v3i3.898

Abstract

The development of artificial intelligence (AI)-based facial recognition technology has become a significant research topic in the field of computing and security. At the Indonesian Palm Oil Institute (ITSI), AI-based facial recognition is introduced to students to improve their skills in developing AI-based applications. This study aims to implement and test a facial recognition system using a Python program by utilizing a dataset generated independently. This research method involves several stages, namely collecting ITSI students' facial data, data processing, creating a facial recognition model using a machine learning algorithm, and evaluating model performance. The dataset used was developed through a live shooting session involving active student participation. The facial recognition model was trained using a convolutional neural network (CNN) algorithm that was optimized to improve accuracy. The results of the study showed that the developed model was able to achieve high facial recognition accuracy, with an average accuracy rate of 92%. The discussion includes an analysis of factors that affect accuracy, such as variations in lighting and shooting angles, as well as the potential use of this technology in a campus environment, including for attendance and security purposes. The conclusion of this study shows that the implementation of AI-based facial recognition can be effectively applied in an academic environment, as well as providing students with practical experience in developing and testing AI applications. This study also opens up opportunities for further research on improving the performance of facial recognition systems and their application in various real-world scenarios.
Pembentukan Model Hirarki Tren Penelitian Berdasarkan Analisis Bibliometrik: Studi Kasus ANP Menggunakan Bibliometrix di R Irawan, Muhammad Dedi; Ikhwan, Ali; Navea, Roy Francis
Sistem Pendukung Keputusan dengan Aplikasi Vol 3 No 2 (2024)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v3i2.884

Abstract

Penelitian ini menggunakan perangkat lunak Bibliometrix dalam R untuk menganalisis tren penelitian terkait Analytic Network Process (ANP) selama lima tahun terakhir (2019-2024) berdasarkan dataset dari Web of Science. Setelah melakukan analisis terhadap 968 artikel ilmiah, penelitian ini tidak hanya menghasilkan wawasan mendalam tentang tren penelitian ANP, tetapi juga membentuk model hirarki yang terdiri dari: 1) Goal – tren penelitian ANP, 2) Kriteria – komponen analisis bibliometrik seperti tren kata kunci, jurnal berpengaruh, serta negara dan penulis yang aktif, dan 3) Alternatif – hasil analisis bibliometrik yang mencerminkan tren topik dalam penelitian ANP. Temuan ini menunjukkan bahwa analisis bibliometrik dapat digunakan untuk menentukan kriteria dan alternatif dalam perankingan tren penelitian, serta memberikan kontribusi bagi berbagai metode Sistem Pendukung Keputusan (SPK), termasuk AHP dan ANP
Co-Authors Ali Ikhwan Andi Prayogi Muhammad Akbar Syahbana Pane Muhammad Dedi Irawan Rahmad Dian Ratu Mutiara Siregar Simbolon, Hasanal Fachri Satia Sugianto, Raden Aris