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All Journal Indonesian Journal of Mathematics and Natural Sciences Journal of Engineering and Technological Sciences Scientific Journal of Informatics Register: Jurnal Ilmiah Teknologi Sistem Informasi JITK (Jurnal Ilmu Pengetahuan dan Komputer) SANITAS: Jurnal Teknologi dan Seni Kesehatan Journal of Soft Computing Exploration INTERNATIONAL JOURNAL OF CULTURAL AND SOCIAL SCIENCE Scientific Journal of Informatics Journal of Advances in Information Systems and Technology Jurnal Abdi Negeri
Hakim, M. Faris Al
Department Of Islamic Economic And Business, State Islamic University Of North Sumatera
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Public Health Social Sciences

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Journal : Scientific Journal of Informatics

 1 
Sign Language Detection System Using YOLOv5 Algorithm to Promote Communication Equality People with Disabilities Ningsih, Maylinna Rahayu; Nurriski, Yopi Julia; Sanjani, Fathimah Az Zahra; Hakim, M. Faris Al; Unjung, Jumanto; Muslim, Much Aziz
Scientific Journal of Informatics Vol. 11 No. 2: May 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i2.6007

Abstract

Purpose: Communication is an important asset in human interaction, but not everyone has equal access to this key asset. Some of us have limitations such as hearing or speech impairments, which require a different communicative approach, namely sign language. These limitations often present accessibility gaps in various sectors, including education and employment, in line with Sustainable Development Goals (SDGs) numbers 4, 8, and 10. This research responds to these challenges by proposing a BISINDO sign language detection system using YOLOv5-NAS-S. The research aims to develop a sign language detection model that is accurate and fast, meets the communicative needs of people with disabilities, and supports the SDGs in reducing the accessibility gap. Methods: The research adopted a transfer learning approach with YOLOv5-NAS-S using BISINDO sign language data against a background of data diversity. Data pre-processing involved Super-Gradients and Roboflow augmentation, while model training was conducted with the Trainer of SuperGradients. Result: The results show that the model achieves a mAP of 97,2% and Recall of 99.6% which indicates a solid ability in separating sign language image classes. This model not only identifies sign language classes but can also predict complex conditions consistently. Novelty: The YOLOv5-NAS-S algorithm shows significant advantages compared to previous studies. The success of this performance is expected to make a positive contribution to efforts to create a more inclusive society, in accordance with the Sustainable Development Goals (SDGs). Further development related to predictive and real-time integration, as well as investigation of possible practical applications in various industries, are some suggestions for further research.
Optimization of Logistic Regression Algorithm Using Grey Wolf Optimizer for Credit Card Fraud Detection Puspita, Wiyanda; Hakim, M. Faris Al
Scientific Journal of Informatics Vol. 12 No. 4: November 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i4.26807

Abstract

Purpose: The advancement of digital technology has significantly changed the financial transaction system, but has also led to an increase in cybercrime, especially credit card fraud. This crime poses a significant financial threat, with reported losses reaching hundreds of millions of dollars annually. This study aims to improve the effectiveness of fraud detection using the Logistic Regression (LR) algorithm, which although widely used in binary classification, is still vulnerable to challenges with imbalanced data. The goal is to optimize LR using the Grey Wolf Optimizer (GWO) to improve accuracy and reliability. Methods: This research implements a Logistic Regression (LR) model whose hyperparameters are optimized using Grey Wolf Optimizer (GWO) algorithm. The model was trained and tested on a public Kaggle dataset containing 284,807 credit card transactions. Data preprocessing includes handling outliers using Interquartile Range (IQR) method and handling class imbalance using KMeansSMOTE. Evaluation metrics include accuracy, precision, recall, f1-score, and specificity based on confusion matrix. Result: The baseline LR model achieved 99.92% accuracy, 75.18% precision, 74.73% recall, 75.45% F1-score, and 99.96% specificity. After GWO optimization, the model improved to 99.94% accuracy, 85.96% precision, 83.08% recall, 84.01% F1-score, and 99.97% specificity, showing a significant performance boost. This represents a notable improvement in key metrics for fraud detection, with an increase of 14.3% in precision, 11.2% in recall, and 11.3% in the F1-score, demonstrating a more robust model. Novelty: This study proposed the application of the Grey Wolf Optimizer (GWO) for hyperparameter tuning of a Logistic Regression model in the context of fraud detection. Unlike conventional optimization techniques that can be computationally expensive, our GWO-based approach offers an efficient and effective method for discovering optimal model settings. The optimized model not only outperforms the baseline LR but also presents a scalable and powerful solution for financial institutions to improve the accuracy of their fraud detection systems.
Co-Authors Adel S.M.A Alsaeed Ahniar, Nur Hasanah Aji Purwinarko, Aji Alamsyah - Anggyi Trisnawan Putra Annisa M Nasution Atika Hendryani Aulia, Muhammad Kahfi Budi Prasetiyo, Budi Damayanti, Dela Rista Endang Sugiharti, Endang Faieza Abdul Aziz Gita Rindang Lestari Ilham, Ahmad Bagas Aditya Irwansyah P Marpaung Jumanto , Jumanto Jumanto Jumanto, Jumanto Jumanto Unjung Listiaji, Prasetyo Mardiansyah, M Fadil Mohd Khairol Anuar Mohd Ariffin Much Aziz Muslim Ningsih, Maylinna Rahayu Nurhotma Tambak Nurriski, Yopi Julia Pradana, Fadli Dony Pratama, Rizka Nur Puspita, Wiyanda Rawat, Bibek Reynaldi, Reynaldi Rinda Nur Hidayati Riski Ihsan Riza Arifudin S.Pd. M Kes I Ketut Sudiana . Sanjani, Fathimah Az Zahra Shamsuddin Sulaiman Subhan Subhan Subhan Subhan Syafrizal, Wahyu Utama, Reiki Aziz Yoga Wicaksono, Suntoro Widya Pangestika Wijaya, Dandi Indra Yahya Nur Ifriza Yosza Dasril Zaenal Abidin