Article Per Year (5 Year)
p-Index From 2021 - 2026
2.459
P-Index
This Author published in this journals
All Journal Register: Jurnal Ilmiah Teknologi Sistem Informasi IJoICT (International Journal on Information and Communication Technology) Faktor Exacta Jurnal Riset Informatika JSAI (Journal Scientific and Applied Informatics) ILKOMNIKA: Journal of Computer Science and Applied Informatics REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Walisongo Journal of Information Technology Brilliance: Research of Artificial Intelligence Journal of Artificial Intelligence and Technology Information DIGIMAS: Jurnal Transformasi Digital Masyarakat
Muhammad Andryan Wahyu Saputra
Universitas Jember
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Other

Published : 16 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : jsai journal scientific and applied informatics

 1 
Perbandingan Performa Algoritma Random Tree, K-NN, dan A-NN untuk Deteksi Serangan DDoS pada Software Defined Network (SDN) Akbar Pandu Segara; Muhammad Andryan Wahyu Saputra; Narandha Arya Ranggianto
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8387

Abstract

Software-Defined Networks (SDNs) with a centralized architecture are vulnerable to Distributed Denial of Service (DDoS) attacks, which can cause widespread network service failures. This study aims to compare the performance of three Machine Learning algorithms—K-Nearest Neighbor (K-NN), Artificial Neural Network (ANN), and Random Tree—in detecting DDoS attacks in an SDN environment. The DDoS-SDN dataset, consisting of 104,345 rows and 23 columns, was used with a data split of 70% for training and 30% for testing. Evaluation was conducted using accuracy, precision, recall, F1-score, and AUC-ROC metrics. The results showed that ANN achieved the best performance with an accuracy of 96.85%, precision of 94.35%, recall of 97.79%, F1-score of 96.04%, and AUC of 0.994, followed by K-NN with an accuracy of 88.89% and Random Tree with the lowest accuracy of 86.49%. The superiority of ANN is attributed to its ability to capture complex non-linear patterns, perform automatic feature extraction, and adapt to the heterogeneity of data from the 22 features used. These findings indicate that ANN is the optimal choice for implementing a real-time DDoS attack detection system in an SDN environment, providing a strong foundation for the development of intelligent and adaptive Machine Learning-based network security systems
Evaluasi Kualitas Layanan Digital Aplikasi Tomoro Coffee Terhadap Kepuasan Kaum Produktif Menggunakan Framework E-Service Quality Vina Dewi Ramadhanty; Martiana Kholila Fadhil; Muhammad Riza Darmawan; Fauziyah Azzahro; Muhammad Andryan Wahyu Saputra; Dananjaya Endi Pratama
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 3 (2025): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i3.9245

Abstract

The trend of drinking coffee among productive people has impacted the growth of coffee shops in Indonesia. To strengthen its market position, Tomoro Coffee utilizes mobile applications. However, there is dissatisfaction with the quality of Tomoro Apps' digital services in reviews. This study evaluated the quality of Tomoro's digital application services using the Electronic Service Quality model. The model focuses on comprehensive digital services from technical aspects and other aspects related to user satisfaction. The assessment was conducted on students of Jember University who made transactions through Tomoro Apps. Data was collected using a questionnaire involving 100 students as research samples. The data were processed using instrument testing, classical assumption testing, and multiple linear regression analysis. An analysis of the data showed that efficiency, responsiveness, and contact positively affected user satisfaction. From the data analysis, seven dimensions of e-service quality were known to have a significant positive and negative effect and were able to explain 88.3% of user satisfaction variability. Through this study, we found that there is still a gap between expectations and application performance. Therefore, improvements in digital service quality should be made in each dimension of electronic service quality, balanced and focused on service users, so that Tomoro Coffee continues to be a competitive advantage. These findings have managerial implications for Tomoro Coffee as recommendations on each dimension of Electronic Service Quality to improve the quality of digital services and strengthen its position in the market.
Co-Authors Akbar Pandu Segara Atmoko, Rizky Damar Novtahaning Dananjaya Endi Pratama Dwi Wijonarko Fauziyah Azzahro Fresy Nugroho Fresy Nugroho Hamim Tohari Hanis Setyowati Hikmatul Kamila Juniardi Nur Fadila Kartiko, Erik Yohan Khoirunnisa Afandi M. Habibullah Arief Martiana Kholila Fadhil Mokhamad Amin Hariyadi Muhammad Faisal Muhammad Riza Darmawan Narandha Arya Ranggianto Ririen Kusumawati Sri Harini Sri Harini Tamaulina Br Sembiring U'un Setiawati Vina Dewi Ramadhanty Wildan Alif Rioditama