Article Per Year (5 Year)
p-Index From 2021 - 2026
2.392
P-Index
This Author published in this journals
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

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search

 1   2 
Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization Dasril, Yosza; Muslim, Much Aziz; Hakim, M. Faris Al; Jumanto , Jumanto; Prasetiyo, Budi
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 1 (2023): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i1.3060

Abstract

The credit risk evaluation is a vital task in the P2P Lending platform. An effective credit risk assessment method in a P2P lending platform can significantly influence investors' decisions. The machine learning algorithm that can be used to evaluate credit risk as LightGBM, however, the results in evaluating P2P lending need to be improved. The aim of this research is to improve the accuracy of the LightGBM algorithm by combining the Particle Swarm Optimization (PSO) algorithm. The novelty developed in this research is combining LightGBM with PSO for large data from the Lending Club Dataset which can be accessed on Kaggle.com. The highest accuracy also presented satisfactory results with 98.094% of accuracy, 90.514% of Recall, and 97.754% of NPV respectively. The combination of LightGBM and PSO shows better results.
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.
Peningkatan Manajemen Ujian Online Bagi Guru di SMK Negeri 1 Karimunjawa Prasetiyo, Budi; Hakim, M. Faris Al; Purwinarko, Aji; Putra, Anggyi Trisnawan; Subhan, Subhan
Jurnal Abdi Negeri Vol 1 No 1 (2023): Januari 2023
Publisher : Informa Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63350/jan.v1i1.3

Abstract

Program Pembelajaran dan Penilaian online di era pandemi COVID-19 saat ini telah berlangsung selama satu tahun di SMK Negeri 1 Karimunjawa. Penerapan e-learning di sekolah ini berdampak pada bertambahnya tuntutan peningkatan kompetensi guru dalam melakukan penilaian secara online. Bagi siswa, tentu akan berdampak terhadap cara mereka mengikuti ujian di sekolah. Siswa harus membiasakan diri untuk menggunakan fitur-fitur yang terdapat pada aplikasi e-learning. Berdasarkan hasil komunikasi dan observasi dengan Kepala SMK Negeri 1 Karimunjawa, dibutuhkan aplikasi yang efektif untuk digunakan dalam penyelenggaraan penilaian atau ujian online untuk siswa. Aplikasi Ujian online juga diharapkan dapat digunakan untuk simulasi Asesmen Kompetensi Minimal (AKM) pada tahun pelajaran 2021/2022. Oleh karena itu, Jurusan Ilmu Komputer, FMIPA, UNNES menawarkan solusi berupa penerapan aplikasi e-ujian yang merupakan produk penelitian yang telah memiliki hak cipta. Metode yang digunakan dalam kegiatan pengabdian ini terdiri dari 3 tahap yaitu Analisis Kebutuhan, Perancangan Aplikasi, Pengembangan Aplikasi, Pelaksanaan, dan Evaluasi. Hasil dari kegiatan pengabdian masyarakat yang telah dilaksanakan adalah pengurus sekolah dan guru memahami potensi dari manajemen ujian berbasis daring untuk pembelajaran di masa pandemi sebagai upaya untuk menjaga standar proses pembelajaran.
Implementasi E-Ujian Sebagai Sistem Penilaian Pembelajaran Daring di SMP Islam Roudlotus Saidiyyah Semarang Hakim, M. Faris Al; Sugiharti, Endang; Alamsyah, Alamsyah; Arifudin, Riza; Abidin, Zaenal; Putra, Anggyi Trisnawan
Jurnal Abdi Negeri Vol 2 No 1 (2024): Januari 2024
Publisher : Informa Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63350/jan.v2i1.18

Abstract

The presence of the COVID-19 outbreak has led to the implementation of online learning from the location of each home. SMP Islam Roudlotus Saidiyyah Semarang has transformed learning by utilizing various applications. However, for the purposes of final semester assessment or integrated assessment, an online exam application is needed that is easy to use and able to provide data on student learning outcomes accurately and quickly. The implementation method consists of preparation, training, and evaluation. The results of the training showed that the E-Ujian application as an application for online assessment has the potential to be applied at SMP Islam Roudlotus Saidiyyah Semarang. The utilization of the E-Ujian Application in learning activities in the partner environment is an effort to maintain the quality of learning.
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