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All Journal JOIV : International Journal on Informatics Visualization INVOTEK: Jurnal Inovasi Vokasional dan Teknologi Journal of Information Technology and Computer Engineering JITSI : Jurnal Ilmiah Teknologi Sistem Informasi International Journal of Advanced Science Computing and Engineering

Alde Alanda, Alde

Politeknik Negeri Padang, Indonesia

Author-ID : 619778

Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Transportation

Published : 12 Documents Claim Missing Document

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Articles

Title

Design of Private Geographycal Information System (GIS) Server for Battlefield Management System Alde Alanda; Erwadi Bakar
JOIV : International Journal on Informatics Visualization Vol 1, No 1 (2017)
Publisher : Politeknik Negeri Padang

Geographic Information System (GIS) data is needed for model earth surface in 3D simulation for SAR operation to make simulation process as real as possible. Adding integrated GIS data server to simulation system make simulation application user does not need to input and prepare the GIS data manually, by reducing simulation application user task, user can more concentrate on simulation process.In this research the design and implementation of GIS data application that can provide the data needed by a simulation application using existing data on the online map provider. Application designed to display data necessary to carry out the conversion of GIS data to the format used in the simulation . Based on the test resuls of the conversion of GIS data to map format generated simulation has the same texture to the original map. Simulations can be run by using the map conversion and the simulation can run using real map but the level of height accuracy is not optimal.

Combining Deep Learning Models for Enhancing the Detection of Botnet Attacks in Multiple Sensors Internet of Things Networks Abdulkareem A. Hezam; Salama A. Mostafa; Zirawani Baharum; Alde Alanda; Mohd Zaki Salikon
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.733

Distributed-Denial-of-Service impacts are undeniably significant, and because of the development of IoT devices, they are expected to continue to rise in the future. Even though many solutions have been developed to identify and prevent this assault, which is mainly targeted at IoT devices, the danger continues to exist and is now larger than ever. It is common practice to launch denial of service attacks in order to prevent legitimate requests from being completed. This is accomplished by swamping the targeted machines or resources with false requests in an attempt to overpower systems and prevent many or all legitimate requests from being completed. There have been many efforts to use machine learning to tackle puzzle-like middle-box problems and other Artificial Intelligence (AI) problems in the last few years. The modern botnets are so sophisticated that they may evolve daily, as in the case of the Mirai botnet, for example. This research presents a deep learning method based on a real-world dataset gathered by infecting nine Internet of Things devices with two of the most destructive DDoS botnets, Mirai and Bashlite, and then analyzing the results. This paper proposes the BiLSTM-CNN model that combines Bidirectional Long-Short Term Memory Recurrent Neural Network and Convolutional Neural Network (CNN). This model employs CNN for data processing and feature optimization, and the BiLSTM is used for classification. This model is evaluated by comparing its results with three standard deep learning models of CNN, Recurrent Neural Network (RNN), and long-Short Term Memory Recurrent Neural Network (LSTMâ€“RNN). There is a huge need for more realistic datasets to fully test such models' capabilities, and where N-BaIoT comes, it also includes multi-device IoT data. The N-BaIoT dataset contains DDoS attacks with the two of the most used types of botnets: Bashlite and Mirai. The 10-fold cross-validation technique tests the four models. The obtained results show that the BiLSTM-CNN outperforms all other individual classifiers in every aspect in which it achieves an accuracy of 89.79% and an error rate of 0.1546 with a very high precision of 93.92% with an f1-score and recall of 85.73% and 89.11%, respectively. The RNN achieves the highest accuracy among the three individual models, with an accuracy of 89.77%, followed by LSTM, which achieves the second-highest accuracy of 89.71%. CNN, on the other hand, achieves the lowest accuracy among all classifiers of 89.50%.

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

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

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.

Liquefaction Potential Map based on Coordinates in Padang City with Google Maps Integration - Liliwarti; - Satwarnirat; Alde Alanda; Rizka Hadelina
JOIV : International Journal on Informatics Visualization Vol 4, No 1 (2020)
Publisher : Society of Visual Informatics

Abstractâ€” Padang City is prone to liquefaction phenomena due to earthquakes. These phenomena can cause various damages to structures, infrastructures, and even can also cause deaths. Therefore, as one of the urban populated cities, the information about liquefaction potential is needed. One of them is by providing a liquefaction potential map, which is useful for mitigation and seismic disaster risks strategies. This article aims to provide a digital map of liquefaction potential in Padang City that integrates with Google Maps. The map is based on 40 coordinates in 7 subdistricts in the city with 3 colored markers that represent the levels of potential liquefaction i.e. no liquefaction level, moderate liquefaction level, and severe liquefaction level. The levels are classified based on the analysis of the secondary Cone Penetration Test data by using the calculation of the Factor of Safety and Liquefaction Potential Index with an earthquake assumption of 8 SR. The result shows that the map has ben able to display information about liquefaction potential, where 32.05% coordinates are classified as no liquefaction level with the highest percentage are in Kuranji, 22.5% are classified as moderate liquefaction level with the highest percentage are in Padang Utara, and 45.0% are classified as severe liquefaction level with the highest percentage are in Koto Tangah.

Co-Authors - Liliwarti - Rasyidah Abdulkareem A. Hezam Ade Irma Suryani Aldo Erianda Aldo Erianda Aldo Erianda Alfajri Maulana Ibrahim Andi Ahmad Dahlan Deni Satria Dwiny Meidelfi Erwadi Bakar Hanriyawan Adnan Mooduto Hanriyawan Adnan Mooduto Humaira, Humaira Indri Rahmayuni Indri Rahmayuni Iswandi Saputra M.Isthofa Ardhana Meri Azmi Mohd Zaki Salikon Putri Huriati Rizka Hadelina Salama A. Mostafa Sarah Latifah Marif Satwarnirat Satwarnirat Yance Sonatha Zirawani Baharum

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