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BASTIAN, ALVIAN
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Aplikasi Penanganan dan Pendampingan Korban Kekerasan Seksual Berbasis Web dan Android Bastian, Alvian; Simamora, Rebeka Frederika; Ahyar, Muh; Ismail, Ismalandari
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 13, No 3 (2024): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v13i3.5045

Abstract

In an effort to prevent and handle sexual violence and support the Regulation of the Minister of Education and Culture, Research and Technology concerning the Prevention and Handling of Sexual Violence, an application media is needed that allows survivors of sexual violence to report sexual crimes and receive psychological assistance. The purpose of this research is to create a media application that can help survivors of sexual violence get help and assistance as well as a medium for sharing stories so that other users can be more aware of the dangers of sexual violence. The method used in this research is using Android Studio and Visual Studio Code as an Integrated Development Environment (IDE) based on Android and using a no-relational (NoSQL) realtime database on firebase and MySQL database. The advantage of the research is that the system to be developed does not use physical servers anymore but all databases are stored in the cloud system. To help survivors to report sexual violence, this application makes it easy to contact law enforcement, contact a psychologist for psychological assistance via online chat, contact the nearest health facility, and contact the Women and Children Protection Unit. Based on testing, applications built based on android and websites can be concluded that they can run well and can be used as reporting and consulting media for survivors of sexual violence
Improving Antivirus Signature For Detection Ransomware Attacks With Machine Learning Bastian, Alvian
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 10, No 1 (2021): Smart Comp : Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v10i1.2190

Abstract

Cybercrime activities are difficult separate from the development of malware. In Internet Security Threat Report, crime by exploiting malware becomes the ultimate crime. One of the highest spreading malwares is ransomware. Ransomware infections has increased year by year since 2013 and there are 1,271 detections for one day in 2017. Meanwhile, in 2018 there was a shift in attacks where 81 percent of attacks targeted enterprise so that ransomware infections increased by 12 percent. For solve this problem, this research proposed antivirus signature based on DLL Files and API Calls of ransomware files. Detection files based on antivirus signature has high theoretical value and practical significance. The experiment showed detection ransomware files based on DLL Files and functional API Calls with machine learning have a good result than detection files based on MD5 and hexdump. For testing and detection ransomware files, this research is using machine learning algorithms such as KNN, SVM, Decision Trees, and Random Forest. Experiment result showed the successful detection ransomware files, improved detection object and method research for antivirus signature.Kata Kunci : Ransomware, Antivirus, Machine Learning, Malware.
Co-Authors Ahyar, Muh Ahyar, Muh. Alwali, Muhammad Amrullah Amrullah Anggun Winursito Asriyadi Asriyadi HR, Yuliani Ika Puspita, Ika Irdan, Anggi Amelia Ismail, Ismalandari Novita Maulidya Jalal Paramita, Vilia Darma Ramadan, Syahrul Mifta Simamora, Rebeka Frederika Solihin, Muhammad Affiq Sukasri, Arifah Syamsiar, Syamsiar Tjambolang, Tjare Anugerah Utomo, Muhammad Nur Yasir