Analisis dan Implementasi Arsitektur Software Menggunakan Model Event Driven Architecture (EDA) (Studi Kasus: Aplikasi Manajemen Logistik pada Perusahaan Dagang Retail)

ABSTRAKSI: Persaingan bisnis semakin lama semakin kompetitif, jumlah pesaing pun semakin banyak. Seiring hal tersebut evolusi perkembangan IT untuk menunjang bisnis pun mengalami kemajuan yang cepat. Salah satu hal yang menjadikan suatu perusahaan dapat memenangkan persaingan adalah memiliki sistem IT yang berkembang dan efisien di perusahaan tersebut. Mengacu pada hal tersebut maka diperlukan suatu model arsitektur software yang dapat mengolah secara cepat. Dalam tugas akhir ini digunakan Event-driven architecture yang merupakan model arsitektur software untuk mendesain dan membangun suatu aplikasi atau sistem yang mengacu pada suatu peristiwa atau event dan diolah secara cepat. Analisa data dilakukan dengan membandingkan waktu pemrosesan berbagai proses yang sesuai dengan proses bisnis pada sistem manajemen logistik yang menggunakan event-driven architecture dengan existing system. Skenario dirancang untuk dapat menggambarkan karakteristik arsitektur dan kinerja sistem. Kata Kunci : arsitektur software, arsitektur event-driven, event-driven, event, event processingABSTRACT: Business competition increase competitively, the number of competitors even more. Along this the development of IT evolution to support the business underwent rapidly. One of the things that make a company can win the competition is having the IT system that was developed and efficient.Referring to this, a software architecture model that can process quickly is needed. In this final task is using Event-driven architecture, a software architecture model for designing and building an application or system that refers to an event and processed quickly.Data analysis was done by comparing between the processing time of various processes in accordance with business process logistic management systems that use event-driven architecture and the existing system. Scenarios designed to depict the architecture characteristics and system performance.Keyword: software architecture, event-driven archotecture, event-driven, event, event processin

Cross-site Scripting Attack Detection Using Machine Learning with Hybrid Features

This study aims to measure the classification accuracy of XSS attacks by using a combination of two methods of determining feature characteristics, namely using linguistic computation and feature selection. XSS attacks have a certain pattern in their character arrangement, this can be studied by learners using n-gram modeling, but in certain cases XSS characteristics can contain a certain meta and synthetic this can be learned using feature selection modeling. From the results of this research, hybrid feature modeling gives good accuracy with an accuracy value of 99.87%, it is better than previous studies which the average is still below 99%, this study also tries to analyze the false positive rate considering that the false positive rate in attack detection is very influential for the convenience of the information security team, with the modeling proposed, the false positive rate is very small, namely 0.039%This study aims to measure the classification accuracy of XSS attacks by using a combination of two methods of determining feature characteristics, namely using linguistic computation and feature selection. XSS attacks have a certain pattern in their character arrangement, this can be studied by learners using n-gram modeling, but in certain cases XSS characteristics can contain a certain meta and synthetic this can be learned using feature selection modeling. From the results of this research, hybrid feature modeling gives good accuracy with an accuracy value of 99.87%, it is better than previous studies which the average is still below 99%, this study also tries to analyze the false positive rate considering that the false positive rate in attack detection is very influential for the convenience of the information security team, with the modeling proposed, the false positive rate is very small, namely 0.039

Optimasi Pencarian Alamat IP Menggunakan Counting Bloom Filter Pada Web Application Firewall

Proses pencarian IP pada Web Application Firewall menjadi sebuah tantangan ketika database IP yang dikumpulkan mulai membesar. WAF harus dapat dengan cepat memberikan keputusan apakah sebuah IP masuk kedalam kategori buruk (blacklisted ip) atau tidak. Berdasarkan penelitian-penelitian sebelumnya algoritma bloom filter dapat dengan mengurangi waktu pencarian secara signifikan, namun hal itu tidak cukup karena bloom filter memiliki kelemahan pada struktur datanya yang tidak dapat dilakukan penghapusan, berdasarkan masalah tersebut kami mengajukan pemodelan baru pencarian IP pada WAF dengan menggunakan algoritma Counting Bloom Filter