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FACE DETECTION AND ANTI-SPOOFING ON DESKTOP APPLICATIONS USING YOU ONLY LOOK ONCE Faisal, Fairo Mahaputranda; Nurhaida, Ida
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/6qntes73

Abstract

In the digital era, facial recognition systems have become increasingly vulnerable to spoofing attacks, as demonstrated by cases of identity theft using photos or smartphone screens. This study develops a real-time face liveness detection system using YOLOv8 to address these vulnerabilities. Under controlled laboratory conditions, the system achieved exceptional performance metrics: accuracy of 1.0, precision of 1.0, and recall of 1.0, with a mean Average Precision (mAP) of 0.96. However, this study reveals critical insights about the challenges of real-world deployment, including significant performance degradation under poor lighting conditions where genuine faces were misclassified as spoofed images. Compared to existing methods such as Attention-Based Two-Stream CNN (accuracy: 0.91) and Deep Spatial Gradient approaches (accuracy: 0.90-0.92), our system demonstrates superior performance in controlled environments but highlights the persistent challenge of environmental variability in practical applications. These findings emphasize the need for robust preprocessing techniques and diverse training datasets to bridge the gap between laboratory performance and real-world reliability. The study contributes to understanding the limitations of current face anti-spoofing technologies and provides a foundation for developing more robust systems suitable for practical deployment.
Aplikasi Sistem Virtual Tour E-Panorama 360 Derajat Berbasis Android Untuk Pengenalan Kampus Mercu Buana Riyadi, Slamet; Nurhaida, Ida
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 1: Februari 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021864209

Abstract

Pemanfaatan internet untuk mencari informasi kini semakin mudah diakses kapanpun dan dimanapun bagi siapa saja terutama kalangan mahasiswa. Salah satu ciri utama kampus yang maju adalah tersedianya informasi yang muncul dalam berbagai media misalnya gambar. Maka skripsi dengan judul “Aplikasi Sistem Virtual Tour Berbasis E-Panorama 360 Derajat Untuk Pengenalan Kampus Mercu Buana” ini berfungsi sebagai media informasi kampus yang ditampilkan dalam bentuk gambar panorama 360 derajat tanpa batas sudut pandang. Metode Penelitian yang digunakan pada penelitian ini adalah metodologi Waterfall yang merupakan metode paling sesuai dengan menekankan 5 tahap pengambangan. Kebutuhan pembuatan virtual tour ini adalah perangkat keras berupa kamera dan laptop serta perangkat lunak berupa photoshop, panoweaver, xampp dan code editor. Website virtual tour ini menampilkan 4 scene dari berbagai titik dan lokasi yang dapat diakses melalui situs resmi dan peta Kampus Mercu Buana. Untuk Pembuatan Sistem Virtual Tour ini menghasilkan Output Website dan Aplikasi Untuk Android. AbstractUtilization of the internet to find information is now more easily accessible anytime and anywhere for anyone, especially among students. One of the main characteristics of an advanced campus is the availability of information that appears in various media such as images. Then the thesis titled "Application of Virtual Tour System Based on 360-Degree E-Panorama for Introduction to the Mercu Buana Campus" serves as the campus information media that is displayed in the form of 360-degree panoramic images without a limited viewing angle. The research method used in this study is the Waterfall methodology which is the most suitable method by emphasizing the 5 stages of floating. The need for making this virtual tour is hardware in the form of cameras and laptops as well as software in the form of photoshop, panoweaver, xampp and codeigniter. This virtual tour website displays 4 scenes from various points and locations that can be accessed through the official website and map of the Mercu Buana Campus. For making this Virtual Tour System, it produces Website and Application for Android.
Global Synergy, Local Impact : Optimizing Information Retrieval In Lampung Community Libraries Through Information Literacy Training Program By Lampung University And Charles Sturt University Windah, Andi; Nurhaida, Ida; Putra, Purwanto; Purnamayanti, Arnila; Maryani, Eri
International Journal Of Community Service Vol. 5 No. 2 (2025): May 2025 (Indonesia - Malaysia - Timor-Leste)
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijcs.v5i2.849

Abstract

International cooperation in community service is becoming increasingly crucial in the era of globalization. The D3 Library Study Program, FISIP Unila, in collaboration with the School of Information and Communication Studies-Charles Sturt University, carried out Community Service in International Cooperation (PKMKI) with a focus on improving information literacy for community library managers in Lampung Province. In an era of abundant information, the ability to search for accurate and relevant information is becoming increasingly important. However, many individuals have difficulty navigating the vast ocean of information. This service aims to overcome this problem by providing training on advanced information search techniques, especially through Google Advanced Search Operators. The methods used in this service include literature studies, field observations, interviews, and Focus Group Discussions (FGD) with community library managers. The results of this service are expected to improve the ability of library managers to provide better information services to the community. The outputs produced include a final service report, financial report, video documentation, and information literacy training modules.
LSTM-Based NLP Approach for Spelling Error Detection and Correction in Scientific Writing Indonesian Language Halim, Yeru Dwi Pratama; Nurhaida, Ida
Electronic Journal of Education, Social Economics and Technology Vol 5, No 1 (2024)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v5i1.309

Abstract

Scientific writing requires precision and clarity to uphold credibility and effective communication. Errors such as spelling mistakes and typos can compromise the quality and reliability of scientific texts. This study proposes a Long Short-Term Memory (LSTM)-based approach to detect and correct spelling errors, enhancing text accuracy and readability. The dataset comprises 45,698 standard words, supplemented with typo variations to improve model performance. Data is sourced from the Indonesian Dictionary (KBBI) and undergoes normalization and preprocessing to capture diverse error patterns. The model’s performance is evaluated using a confusion matrix, achieving 93% accuracy and high precision, recall, and F1-score metrics. These results demonstrate that the proposed NLP-based LSTM model offers an effective and reliable solution for identifying and correcting spelling errors. This approach significantly enhances the quality of scientific writing, ensuring more transparent and credible communication.
Web-Based Face Recognition System for Attendance Management Pratiwi, Chelomitha Arsy; Nurhaida, Ida
Electronic Journal of Education, Social Economics and Technology Vol 5, No 2 (2024)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v5i2.291

Abstract

Studi ini berfokus pada pengembangan aplikasi absensi berbasis web yang memanfaatkan teknologi pengenalan wajah untuk mengatasi keterbatasan sistem absensi manual, seperti inefisiensi, kesalahan, dan kerentanan terhadap penipuan. Sistem yang diusulkan menggunakan algoritma Scale-Invariant Feature Transform (SIFT) untuk mengekstraksi fitur wajah, memastikan pengenalan yang akurat dalam berbagai kondisi. Set data terdiri dari 537 gambar wajah yang diberi anotasi, diproses terlebih dahulu melalui pengubahan ukuran dan konversi skala abu-abu untuk meningkatkan ekstraksi fitur. Pelatihan model, yang diimplementasikan dengan YOLOv8, mencapai akurasi 97,05%, presisi rata-rata rata-rata (mAP) 0,975, dan skor F1 0,95, yang menunjukkan keandalan deteksi dan pengenalan wajah yang tinggi. Aplikasi ini terintegrasi dengan REST API, yang memungkinkan verifikasi absensi waktu nyata dengan mencocokkan gambar wajah yang diambil dengan basis data terpusat. Meskipun sistem menghadapi tantangan dalam mengenali profil samping dan kondisi cahaya redup, sistem ini secara signifikan meningkatkan manajemen absensi dengan mengotomatiskan proses, meminimalkan kesalahan, dan meningkatkan keamanan data. Peningkatan di masa mendatang dapat menggabungkan teknik pembelajaran mendalam dan integrasi yang lebih luas dengan sistem manajemen personalia untuk mengoptimalkan kinerja, skalabilitas, dan efisiensi operasional.
Signature Originality Verification Using A Deep Learning Approach Saputra, Muhammad Azi; Nurhaida, Ida
Electronic Journal of Education, Social Economics and Technology Vol 5, No 1 (2024)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v5i1.310

Abstract

The rapid advancement of digital technology has heightened the need for reliable methods to verify signature authenticity, a critical aspect of document and transaction security. This study uses a deep learning approach to develop a mobile application to verify the originality of paper and digital media signatures. The dataset comprises 1,060 signature images, including authentic and forged categories for both media types. The system employs the EfficientNetV2M model, trained with augmented data, to enhance robustness. Model evaluation demonstrates strong performance with an accuracy of 82.07%, a global precision of 81.31%, a global recall of 83.25%, and a global F1-score of 82.18%. The model is implemented in an Android-based mobile application, providing an intuitive interface for users to upload and verify signatures in real time. These results underscore the potential of EfficientNetV2M for mitigating signature fraud across various domains while highlighting areas for improvement, particularly in classifying paper-based signatures. Future work will focus on expanding the dataset and refining feature extraction techniques to enhance classification performance.
Analisis Sentimen berbasis Deep Learning Terhadap Kesetaraan Gender di Bidang STEM: Perspektif dan Implikasinya Mariam, Siti; Nurhaida, Ida
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 1 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i1.29071

Abstract

Women's participation in Science, Technology, Engineering, and Mathematics (STEM) is still low due to discrimination, gender stereotypes, and lack of access to equal career opportunities. This research analyzes public sentiment about gender equality in STEM fields using the Knowledge Discovery in Database (KDD) approach with the Long Short-Term Memory (LSTM) algorithm. The data consists of 1,200 tweets (2018-2024) collected through web crawling and processed using KDD techniques such as preprocessing, transformation, data mining and evaluation. The resulting LSTM model showed 86.25% accuracy, 88.18% precision, 82.20% recall, and 85.00% F1-score. Sentiment analysis showed support and appreciation for women in STEM (positive sentiment) and criticism of gender discrimination and stereotypes (negative sentiment). This study faced challenges in the form of data imbalance and the model's difficulty in understanding the Indonesian context. Our findings confirm the importance of policies that support gender equality and inclusive work environments. This research is expected to improve people's perception of gender equality and increase the representation of women in STEM fields, especially in Indonesia.
Aplikasi Artificial intelligence untuk Klasifikasi Lengkungan Kaki: Solusi berbasis Radiografi Haris, Abdul; Nurhaida, Ida
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 1 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i1.29098

Abstract

Identifying foot arch types is crucial for maintaining health and comfort. Flat foot arches can cause pain and discomfort, potentially interfering with activities such as sports. This research aims to develop an Artificial intelligence (AI)-based application to detect normal and flat foot arch types through X-ray images. The YOLOv8 model with bounding box is converted to TensorFlow Lite format to be integrated into a mobile platform through Android Studio. The application uses a waterfall model without maintenance, starting from the analysis of x-ray dataset needs, development and testing of the YOLOv8 model, conversion to TensorFlow Lite, design, black box testing, and application on Android devices. This application can only identify x-ray photos of the soles of the feet looking right and left. Confusion matrix application testing with 150 epochs shows performance with recall 86.2%, precision 77.1%, accuracy 83.3%, mAP50 94.9%, and mAP50-95 76.2%. Black box testing on mobile devices using datasets augmented with 45° horizontal shear and 90° rotation resulted in maximum identification accuracy compared to traditional methods such as the wet foot test. Traditional methods print the soles of the feet with an identification process that requires precision of the patient's standing position. This app detects flatfoot early, improving comfort in daily activities and sports.
The Effect of Financial Innovation, Risk Management, and Monetary Policy on the Stability of Fintech Startup Companies in Jakarta Ali, Husain; Sirat, Abdul Hadi; Nurhaida, Ida
West Science Business and Management Vol. 2 No. 04 (2024): West Science Business and Management
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsbm.v2i04.1556

Abstract

This study investigates the effects of financial innovation, risk management, and monetary policy on the stability of fintech startup companies in Jakarta. Using a quantitative approach, data were collected from 35 fintech startups through structured questionnaires with responses measured on a Likert scale of 1-5. Data analysis was conducted using SPSS version 25, employing correlation and multiple regression analysis. The results reveal that financial innovation is the most significant predictor of fintech stability, followed by risk management and monetary policy. The combined influence of these factors explains 74% of the variance in fintech stability. These findings underscore the importance of integrating innovation with robust risk management practices and aligning operations with macroeconomic trends for sustained stability. This research provides valuable insights for fintech stakeholders and policymakers to foster resilience and growth in the rapidly evolving financial ecosystem.
Fostering Sustainable Digital Leadership in Educational Organization, Systematic Literature Review using NVIVO and PRISMA Giovanni, Netaniel; Ali, Hapzi; Nurhaida, Ida
Dinasti International Journal of Economics, Finance & Accounting Vol. 5 No. 3 (2024): Dinasti International Journal of Economics, Finance & Accounting (July - August
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijefa.v5i3.2853

Abstract

This research identifies the role of digital leadership in educational organizations. The analysis uses qualitative analysis. The research method used is SLR (Systematic Literature Review) with the PRISMA protocol through stages supported by the Publish or Perish and NVIVO applications. All supporting publications were searched through Publish or Perish and Dimension Database. The article search results found 543 related studies in 2020-2024, then filtered through the PRISMA protocol to 35 articles selected to answer the research questions. The results of the article are: 1) Sustainable digital leadership involves several essential aspects: agility, resilience, and adaptability. 2) There are 10 sustainable digital leadership competencies that digital leaders need to have: Focus on Vision, Repetitiveness, Communication and Collaboration, Flexibility, Resourcefulness, Risk-Taking and Recovery, Critical Thinking, Culture of Learning, Responsiveness, and Creativity and Innovation. 3) Future leaders must prioritize understanding digital change and assessing digital leadership competencies. This competency development can take the form of training, talent development, support from experts, and digital leadership assessments. 4) Essential to provide financial resources, infrastructure, work environment, and access to the latest learning technology. 5) The most vital aspect of digital leadership is how leaders collaborate and empower to realize the vision, implement change, and create a creative and innovative educational organizational environment.