Article Per Year (5 Year)
p-Index From 2021 - 2026
2.958
P-Index
This Author published in this journals
All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Register: Jurnal Ilmiah Teknologi Sistem Informasi IJEBD (International Journal Of Entrepreneurship And Business Development) Informatik : Jurnal Ilmu Komputer Journal of Information Systems and Informatics bit-Tech International Journal of Advances in Data and Information Systems Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Nusantara Science and Technology Proceedings Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences International Journal of Robotics and Control Systems International Journal Of Computer, Network Security and Information System (IJCONSIST) Jurnal Impresi Indonesia Literasi Nusantara Journal of International Conference Proceedings Jurnal Ilmiah Edutic : Pendidikan dan Informatika Signal and Image Processing Letters
Diyasa, I Gede Susrama Mas
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Physics Social Sciences Other

Published : 23 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 23 Documents
Search

 1   2   3 
Data Augmentation of Sperm Images Using Generative Adversarial Networks (WGAN-GP) Diyasa, I Gede Susrama Mas; Kuswardhani , Hajjar Ayu Cahyani; Idhom, Mohammad; Riyantoko, Prismahardi Aji; Dewi , Deshinta Arrova
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 12 No 1 (2026): January (In Progress)
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v12i1.5954

Abstract

This study analyzes the use of WGAN-GP for data augmentation in the analysis of sperm morphology. WGAN-GP has been the focus in this study for generating sperm microscopy images, which in turn aims to mitigate the problem of data scarcity in medical imaging. A heterogeneous dataset with mixed object categories was initially employed, leading to an FID score of 134, which in turn reflected a high incidence of mode collapse. For this reason, the dataset was divided into subcategories of Normal, Abnormal, and Non-Sperm identifications, with the scores of the subcategories being 59.19, 74.92, and 83.56, respectively, and showing better balanced model stability. This study's primary contribution is the use of WGAN-GP for the first time for sperm image data augmentation and the generation of more realistic synthetic images. Furthermore, this study illustrates the first understanding of the intricacies of data distribution's complexity and its effect on the model's performance, indicating the possibility of improvement using class-based techniques and sophisticated architectures for the generator. The innovation of this study is the application of WGAN-GP to sperm morphology datasets, improving image quality and the stability of the results, coupled with extensive model performance analysis and providing a further understanding of the field of medical image data augmentation.
Face Detection Based on Anti-Spoofing with FaceNet Method for Filtering Contract Cheating in Online Exam Ujianto, Erik Iman Heri; Diyasa, I Gede Susrama Mas; Junaidi, Achmad; Fatullah, Ryan Reynickha; Permanasari, Wahyu Melinda; Sari, Allan Ruhui Fatmah
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1167

Abstract

This study develops a reliable face-based verification system for online examinations by integrating a face recognition model with a blink detection mechanism to minimize the risk of identity fraud, also known as "contract cheating," and static image manipulation. "Contract cheating" refers to the practice where students hire others to complete their exams or assignments, compromising academic integrity. The growing reliance on online exams has raised concerns about the credibility of facial verification, as conventional methods are often vulnerable to spoofing attempts. To address this issue, the proposed system combines FaceNet, a deep learning model for identity recognition, with Dlib’s eye blink detection to provide a stronger layer of protection. The system was evaluated using 5-fold and 10-fold K-fold cross-validation, and additional testing assessed the impact of different video frame rates on performance. The results show that the system performs effectively in identifying legitimate users and detecting spoofing. FaceNet achieved an accuracy of 96.67 percent, outperforming DeepFace, which showed poorer results in precision, recall, and F1 score for some participants. Both models were evaluated on the same dataset, consisting of 150 images. The preprocessing pipeline, including face detection using MTCNN, cropping, and resizing, was applied consistently to both models to ensure a fair comparison of their performance. The system also demonstrated adaptability, achieving correct classifications at both 15 and 30 frames per second. Anti-spoofing tests based on the eye blink detection system detected all real faces, while static images were classified as spoofing. These results confirm that combining face recognition with liveness detection enhances the security of online examination platforms. The findings demonstrate the system's potential to reduce contract cheating and impersonation fraud, making online examinations more credible. Future work may focus on implementing adaptive thresholding for blink detection and integrating multimodal verification techniques to improve robustness across diverse real-world environments.
Fuzzy Time Series Cheng Optimasi Adaptive Particle Swarm Optimization (APSO) untuk Optimalisasi Prediksi Harga Beras di Kota Surabaya Ulayya, Yasmin; Idhom, Mohammad; Diyasa, I Gede Susrama Mas
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 1: Februari 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2026131

Abstract

Harga beras rentan mengalami fluktuasi, berdampak signifikan pada kesejahteraan masyarakat, terutama kelompok berpendapatan rendah. Di Surabaya, kenaikan harga beras mendorong perlunya prediksi akurat untuk mitigasi dampak ekonomi. Penelitian ini bertujuan meramalkan harga beras menggunakan metode Fuzzy Time Series Cheng (FTS Cheng) yang dioptimalkan dengan Adaptive Particle Swarm Optimization (APSO) untuk menangani data non-linear dan fluktuatif. Data sekunder diambil dari Dinas Perindustrian dan Perdagangan Provinsi Jawa Timur (Siskaperbapo) periode 1 Januari 2023 hingga 31 Maret 2025, mencakup harga beras premium dan medium di Pasar Tambahrejo dan Pasar Wonokromo. Metode utama adalah FTS Cheng dengan optimasi APSO untuk meningkatkan akurasi prediksi. Model menunjukkan akurasi tinggi dengan MAPE (Mean Absolute Percentage Error) sangat rendah. Di Pasar Tambahrejo, MAPE beras premium 0,09% dan medium 0,00%. Di Pasar Wonokromo, MAPE premium 6,38% dan medium 0,85%. Optimasi APSO berhasil menurunkan MAPE, misalnya di Pasar Tambahrejo (premium turun 0,38%, medium turun 0,68%). Kombinasi FTS dan APSO menghasilkan prediksi harga beras yang presisi. Temuan ini dapat mendukung kebijakan stabilisasi harga, manajemen stok, dan perencanaan produksi beras lebih efektif, sekaligus meningkatkan stabilitas ekonomi rumah tangga.   Abstract Rice prices are prone to fluctuations, significantly impacting public welfare, especially low-income groups. In Surabaya, rising rice prices necessitate accurate predictions to mitigate economic impacts. This research aims to forecast rice prices using the Fuzzy Time Series Cheng (FTS Cheng) method optimized with Adaptive Particle Swarm Optimization (APSO) to handle non-linear and fluctuating data. Secondary data was obtained from the East Java Provincial Department of Industry and Trade (Siskaperbapo) for the period January 1, 2023, to March 31, 2025, covering premium and medium rice prices at Tambahrejo Market and Wonokromo Market. The main method is FTS Cheng with APSO optimization to improve prediction accuracy. The model demonstrates high accuracy with very low MAPE (Mean Absolute Percentage Error). At Tambahrejo Market, MAPE for premium rice is 0.09% and medium rice is 0.00%. At Wonokromo Market, MAPE for premium rice is 6.38% and medium rice is 0.85%. APSO optimization successfully reduces MAPE, for example at Tambahrejo Market (premium decreased by 0.38%, medium decreased by 0.68%). The combination of FTS Cheng and APSO produces precise rice price predictions. These findings can support price stabilization policies, stock management, and more effective rice production planning, while improving household economic stability.
Co-Authors A, Denisa Septalian A. A. Ngurah Gunawan Achmad Junaidi, Achmad Adila, Ma’ratul Agussalim, Agussalim Ali, Munawar Ani Dijah Rahajoe Awang, Wan Suryani Wan Bambang Trigunarsyah, Bambang Basuki Rahmat Masdi Siduppa Damaliana, Aviolla Terza Dewi , Deshinta Arrova Dwi Arman Prasetya Erik Iman Heri Ujianto Erma Suryani Eva Yulia Puspaningrum Fahrudin, Tresna Maulana Faikul Umam Fatullah, Ryan Reynickha Fetty Tri Anggraeny Henki Bayu Seta Humairah, Sayyidah I Made Merdana Ibrahim, Mohd Zamri Bin idhom, Mohammad Karim, Mohammad Daniel Sulthonul Kartika Maulida Hindrayani Kusuma, Nugraha Varrel Kuswardana, Dendy Arizki Kuswardhani , Hajjar Ayu Cahyani Made Hanindia Prami Swari Mudjahidin Najma P., Safira NYOMAN DITA PAHANG PUTRA, NYOMAN P, Made Hanindia Permana, Eriko Indra Permanasari, Wahyu Melinda Prayoga, Aji Putra, Handie Pramana Riyantoko, Prismahardi Aji Rizky Mahendra, Rakha Sampurno, Ilham Ade Widya Saputra, Wahyu Syaifullah Jauharis Sari, Allan Ruhui Fatmah Sari, Refika Ayuna Sibarani, Michael Alexander Justin Audison Sugiarto S Trenggono, Brahmantio Widyo Trimono Trimono, Trimono Ulayya, Yasmin Viet Ha, Nguyen Yisti Vita Via Zahrah, Fathima Zamri, Mohd