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All Journal JURIKOM (Jurnal Riset Komputer) Infotekmesin Journal of Innovation Information Technology and Application (JINITA) Madani : Indonesian Journal of Civil Society
Arif Wirawan Muhammad
Unknown Affiliation
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Mechanical Engineering

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A Classification Data Packets Using the Threshold Method for Detection of DDoS Sukma Aji; Davito Rasendriya Rizqullah Putra; Riadi, Imam; Fadlil , Abdul; Faiz , Muhammad Nur; Arif Wirawan Muhammad; Purwaningrum, Santi; Sari, Laura
Journal of Innovation Information Technology and Application (JINITA) Vol 6 No 1 (2024): JINITA, June 2024
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v6i1.2224

Abstract

Computer communication is done by first synchronizing one computer with another computer. This synchronization contains Data Packages which can be detrimental if done continuously, it will be categorized as an attack. This type of attack, when performed against a target by many computers, is called a distributed denial of service (DDoS) attack. Technology and the Internet are growing rapidly, so many DDoS attack applications result in these attacks still being a serious threat. This research aims to apply the Threshold method in detecting DDoS attacks. The Threshold method is used to process numeric attributes so obtained from the logfile in a computer network so that data packages can be classified into 2, namely normal access and attack access. Classification results using the Threshold method after going through the fitting process, namely detecting 8 IP Addresses as computer network users and 6 IP addresses as perpetrators of DDoS attacks with optimal accuracy.
Pengembangan Perangkat Lunak Untuk Deteksi DDoS Berbasis Neural Network Arif Wirawan Muhammad; Muhammad Nur Faiz; Ummi Athiyah
Infotekmesin Vol 13 No 2 (2022): Infotekmesin: Juli, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i2.1544

Abstract

System security issues are a vital factor that needs to be considered in the operation of systems and networks, which will later be used for disaster mitigation and preventing attacks on the network. Distributed Denial of Services (DDoS) is a form of attack carried out by individuals or groups to damage data through servers or malware in the form of flooding packets, therefore it can paralyze the network system used. Network security is a factor that must be maintained and considered in an information system. DDoS can take the form of Ping of Death, flood, Remote control attack, User Data Protocol (UDP) flood, and Smurf Attack. This study aims to develop software to detect DDoS attacks based on network traffic logs. The software has been tested and run according to the neural network algorithm. This software was developed with an interface that makes it easier for users to detect the source IP whether the IP is carrying out a DDoS attack or normal.
Peningkatan Kapasitas Penjualan Pada Kader Pemberdayaan Masyarakat Desa Melalui Pelatihan Pemasaran Digital Athiyah, Ummi; Alika, Shintia Dwi; Dewi, Atika Ratna; Habiburrahman, Muhammad Quthb; Sa’adah, Oktavia Jazilatus; Arif Wirawan Muhammad
Madani : Indonesian Journal of Civil Society Vol. 6 No. 2 (2024): Madani : Agustus 2024
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/madani.v6i2.2193

Abstract

Empowering rural communities is essential for sustainable development, especially in the economic sector. This community service program aims to increase the sales capacity of the Sunyalangu Village Community Empowerment Cadres (KPMD) through digital marketing training. The main problems include simple packaging, conventional marketing methods, and poor business management practices. This program uses a community service method, Service Learning (SL), which involves practical steps such as product packaging training and digital marketing strategy workshops. This project significantly improved participants' skills in using sealer machines and promoting products online, especially on platforms like Shopee. The method of implementing strategic digital marketing communication training was carried out with a structured and interactive approach over two meetings. The results showed the importance of digital literacy in rural areas to achieve maximum business potential and improve economic sustainability. This training has successfully introduced participants to the world of online trading and provided them with practical skills in utilizing digital platforms to market processed products from the community.
Eksplorasi Teknik Pre-Processing Berbasis eXtreme Gradient Boosting (XGBoost) pada Serangan DDoS Nur Faiz, Muhammad; Sari, Laura; Imam Riadi; Arif Wirawan Muhammad; Sukma Aji
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 6 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i6.9380

Abstract

Distributed Denial of Service (DDoS) attacks represent a critical threat to modern network security, particularly within Internet of Things (IoT) environments characterized by large-scale and heterogeneous traffic patterns. The primary challenges in detecting such attacks involve class imbalance, irrelevant features, and noise within the data, all of which can degrade the performance of machine learning-based detection models. This study evaluates the impact of a pre-processing pipeline—comprising the Synthetic Minority Over-sampling Technique (SMOTE), correlation-based feature selection, and advanced feature selection methods—on the performance of the XGBoost algorithm in detecting DDoS attacks using the CIC-IoT2023 dataset. Experimental results indicate that the XGBoost model trained on RAW data achieves exceptionally high performance, with an accuracy of 0.999983, precision of 0.985531, recall of 0.961390, and an F1-score of 0.999983. However, after applying the pre-processing techniques, all metrics experienced a decline, with accuracy decreasing to 0.958899, precision to 0.865729, recall to 0.748332, and the F1-score to 0.959158. The reduction in recall suggests a higher number of undetected attacks, whereas the drop in precision indicates an increase in false alarms. Nevertheless, the F1-score remaining above 0.95 demonstrates that the model continues to perform effectively overall. These findings reveal that pre-processing does not always lead to performance improvements, especially when the raw dataset is already relatively clean and balanced. This study provides deeper insights into how SMOTE, feature selection, and noise injection influence the generalization of XGBoost on IoT traffic, and emphasizes that the effectiveness of pre-processing is highly dependent on dataset characteristics and the intended application context of intrusion detection systems.
Co-Authors Alika, Shintia Dwi Atika Ratna Dewi Davito Rasendriya Rizqullah Putra Fadlil , Abdul Faiz , Muhammad Nur Habiburrahman, Muhammad Quthb Imam Riadi Muhammad Nur Faiz Nur Faiz, Muhammad Purwaningrum, Santi Sa’adah, Oktavia Jazilatus Sari, Laura Sukma Aji Ummi Athiyah