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All Journal Jurnal Ilmiah Poli Rekayasa Elektron Jurnal Ilmiah Jurnal Momentum JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Journal of Information Technology and Computer Engineering Journal of Applied Computer Science and Technology (JACOST) JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Abdimas: Pengabdian dan Pengembangan Masyarakat International Journal of Advanced Science Computing and Engineering Vox Populi: Jurnal Umum Pengabdian Kepada Masyarakat
Deni Satria
Politeknik Negeri Padang
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : JOIV : International Journal on Informatics Visualization

 1 
Web Application Penetration Testing Using SQL Injection Attack Alde Alanda; Deni Satria; M.Isthofa Ardhana; Andi Ahmad Dahlan; Hanriyawan Adnan Mooduto
JOIV : International Journal on Informatics Visualization Vol 5, No 3 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.3.470

Abstract

A web application is a very important requirement in the information and digitalization era. With the increasing use of the internet and the growing number of web applications, every web application requires an adequate security level to store information safely and avoid cyber attacks. Web applications go through rapid development phases with short turnaround times, challenging to eliminate vulnerabilities. The vulnerability on the web application can be analyzed using the penetration testing method. This research uses penetration testing with the black-box method to test web application security based on the list of most attacks on the Open Web Application Security Project (OWASP), namely SQL Injection. SQL injection allows attackers to obtain unrestricted access to the databases and potentially collecting sensitive information from databases. This research randomly tested several websites such as government, schools, and other commercial websites with several techniques of SQL injection attack. Testing was carried out on ten websites randomly by looking for gaps to test security using the SQL injection attack. The results of testing conducted 80% of the websites tested have a weakness against SQL injection attacks. Based on this research, SQL injection is still the most prevalent threat for web applications. Further research can explain detailed information about SQL injection with specific techniques and how to prevent this attack.
Network Security Assessment Using Internal Network Penetration Testing Methodology Deni Satria; Alde Alanda; Aldo Erianda; Deddy Prayama
JOIV : International Journal on Informatics Visualization Vol 2, No 4-2 (2018): Cyber Security and Information Assurance
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2300.569 KB) | DOI: 10.30630/joiv.2.4-2.190

Abstract

The development of information technology is a new challenge for computer network security systems and the information contained in it, the level of awareness of the importance of network security systems is still very low. according to a survey conducted by Symantec, the desire to renew an existing security system within a year within a company has the result that only 13% of respondents consider changes to the security system to be important from a total of 3,300 companies worldwide as respondents. This lack of awareness results in the emergence of security holes that can be used by crackers to enter and disrupt the stability of the system. Every year cyber attacks increase significantly, so that every year there is a need to improve the security of the existing system. Based on that, a method is needed to periodically assess system and network security by using penetrarion testing methods to obtain any vulnerabilities that exist on the network and on a system so as to increase security and minimize theft or loss of important data. Testing is carried out by using internal network penetration testing method which tests using 5 types of attacks. From the results of the tests, each system has a security risk of 20-80%. From the results of these tests it can be concluded that each system has a security vulnerability that can be attacked.
A Comparative Study of Image Retrieval Algorithm in Medical Imaging Abdullah, Yang Muhammad Putra; Bakar, Suraya Abu; Hj Wan Yussof, Wan Nural Jawahir; Hamzah, Raseeda; Hamid, Rahayu A; Satria, Deni
JOIV : International Journal on Informatics Visualization Vol 8, No 3-2 (2024): IT for Global Goals: Building a Sustainable Tomorrow
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3-2.3447

Abstract

In recent times, digital environments have become more complex, and the need for secure, efficient, and reliable identification systems is growing in demand. Consequently, image retrieval has emerged as a critical area focusing on artificial intelligence and machine learning applications. Medical image retrieval has become increasingly crucial in today's healthcare field, as it involves accurate diagnostics, treatment planning, and advanced medical research. As the quantity of medical imaging data grows rapidly, the ability to efficiently and accurately retrieve relevant images from extensive datasets becomes critical. Advanced retrieval systems, such as content-based image retrieval, are imperative for managing complex data, ensuring that healthcare professionals can access the most relevant information to improve patient outcomes and advance medical knowledge. This paper compares three algorithms: Scale Invariant Feature Transform, Speeded Robust Features, and Convolutional Neural Networks in the context of two medical image datasets, ImageCLEF and Unifesp. The findings highlight the trade-offs between precision and recall for each algorithm, providing invaluable insights into selecting the most suitable algorithm for specific tasks. The study evaluates the algorithms based on precision and recall, two critical performance metrics in image retrieval.
Co-Authors Abdullah, Yang Muhammad Putra Alde Alanda, Alde Aldo Erianda Amelia Yolanda - Andi Ahmad Dahlan Anggara Nasution Bakar, Suraya Abu Dahri, Muhtar Danang, Satria Deddy Prayama Febrian Chandra Gusriyani, Nessie Hamid, Rahayu A Hamzah, Raseeda Hanriyawan Adnan Mooduto Harmaini Harmaini Hidayatul Sidiq Hidra Amnur Hidra Amnur Hj Wan Yussof, Wan Nural Jawahir Humaira, Humaira Ikhsan Yusda PP Indri Rahmayuni Julianto, Tegar M.Isthofa Ardhana Meri Azmi Mohammad Arqon Naimah Naimah Nuria Sisma Putri Putri Febriani, Widia Rafiq Mulia Putra Rahmat Hidayat Ramahdan, Gion Reynaldi, Reynaldi Rika Idmayanti Roni Putra Sasgita, Nabila Syofiana Sari, Rica Taradipa, Maharani Yanto, Widja Yuhefizar Yuhefizar Yulherniwati -