Distributed Denial of Service (DDoS) is a type of attack using the volume, intensity, and more costs mitigation to increase in this era. Attackers used many zombie computers to exhaust the resources available to a network, application or service so that authorize users cannot gain access or the network service is down, and it is a great loss for Internet users in computer networks affected by DDoS attacks. In the Network Forensic, a crime that occurs in the system network services can be sued in the court and the attackers will be punished in accordance with law. This research has the goal to develop a new approach to detect DDoS attacks based on network traffic activity were statistically analyzed using Naive Bayes method. Data were taken from the training and testing of network traffic in a core router in Master of Information Technology Research Laboratory University of Ahmad Dahlan Yogyakarta. The new approach in detecting DDoS attacks is expected to be a relation with Intrusion Detection System (IDS) to predict the existence of DDoS attacks.

Abstract-Cyber attacks by sending large data packets that deplete computer network service resources by using multiple computers when attacking are called Distributed Denial of Service (DDoS) attacks. Total Data Packet and important information in the form of log files sent by the attacker can be observed and captured through the port mirroring of the computer network service. The classification system is required to distinguish network traffic into two conditions, first normal condition, and second attack condition. The Gaussian Naive Bayes classification is one of the methods that can be used to process numeric attribute as input and determine two decisions of access that occur on the computer network service that is "normal" access or access under "attack" by DDoS as output. This research was conducted in Ahmad Dahlan University Networking Laboratory (ADUNL) for 60 minutes with the result of classification of 8 IP Address with normal access and 6 IP Address with DDoS attack access.

Network forensics is a computer security investigation to find sources of the attack

As technology is increasingly advanced and developing, shopping that was originally done in supermarkets is now done online. The COVID pandemic has also made people switch to shopping online, as in e-commerce. Research also shows that e-commerce in Indonesia has increased by 5–10 times during the pandemic. Ecommerce has always been associated with simple and convenient purchasing and payment methods. Ijabqabul.id is an e- commerce platform that provides a variety of product categories. In order to improve services for the development of ijabqabul.id e-commerce, particularly in terms of payment transactions, a payment gateway system as an online payment system is required. This research will result in a web service-based payment gateway system with JSON output. A payment gateway system is built using the Python programming language and the Flask framework. The Postman application is used to test a payment gateway system that is based on web services. Agile Development is the method used in the development of the payment gateway system. This method is carried out through brainstorming with researchers from the sharia study program. The developed payment gateway system generates a virtual account number, making the transaction process simpler, safer, and more convenient

Abstrak