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All Journal Aurelia: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia VISA: Journal of Vision and Ideas
Singgam, Pritiy
Unknown Affiliation
Humanities Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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Analysis of Travel Time Approximation on Trips Using Maclaurin Series Singgam, Pritiy; Silalahi, Anggi; Tampubolon, Josua Deo; Harliana, Putri
AURELIA: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Vol 4, No 1 (2025): January 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/aurelia.v4i1.4754

Abstract

Mathematical approximation plays an important role in the analysis of travel time which is influenced by factors such as speed, distance, and acceleration. This study uses the Maclaurin series to approximate the value of travel time based on the distance traveled (x) and the number of terms in the series (n). The calculation was done manually and implemented using MATLAB for the case of distance x = 2 with the first five terms n = 5. The results of the manual calculation showed an estimated travel time of 0.9094 seconds, while the calculation using MATLAB resulted in 0.9093 seconds. The small difference between the two methods shows the accuracy of the Maclaurin series in travel time approximation. By increasing the number of terms in the sequence, the calculation results will be closer to a more precise value. This study emphasizes the benefits of the Maclaurin sequence method in simplifying mathematical analysis and improving calculation efficiency in physical and computational applications. 
Utilizing Capa in Kali Linux for Wannacry Malware Identification and Analysis Singgam, Pritiy; Nasution, Afifah Naila; Waruwu, Pedro Stella Mario Meyar
AURELIA: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Vol 4, No 1 (2025): January 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/aurelia.v4i1.4775

Abstract

Purpose: This study aims to analyze the WannaCry ransomware using Kali Linux and the Common Access Platform Assistant (CAPA) method to provide a deeper understanding of the malware's attack tactics, capabilities, and behaviors. Methods/Study design/approach: The research was conducted by installing CAPA version 7.4.0 downloaded from GitHub, followed by file extraction and access permission configuration. The WannaCry malware was obtained from the "thezoo" repository on GitHub, extracted, and analyzed using CAPA commands in the Linux terminal. The analysis results were presented in tables showing the malware's tactics, techniques, and behaviors. Result/Findings: The analysis revealed that CAPA effectively identified various tactics and techniques used by WannaCry, confirming its classification as malware. Validation through antivirus services indicated that 68 out of 72 services flagged the file as malicious, emphasizing the importance of robust cybersecurity measures. Novelty/Originality/Value: This study offers new insights into the working mechanisms of WannaCry ransomware and highlights the effectiveness of the CAPA method in malware analysis. The findings contribute to a better understanding of cybersecurity threats and provide valuable information for professionals in the field to enhance defense strategies against malware.
Penerapan Algoritma Quick Sort untuk Menyortir Array Berdasarkan Kriteria Tertentu untuk Meningkatkan Efisiensi Komputasi Nasution, Afifah Naila; Singgam, Pritiy; Al-Hafiz, Ahmad Yusuf; Alvansyah, Oka; Tampubolon, Josua Deo
VISA: Journal of Vision and Ideas Vol. 4 No. 3 (2024): VISA: Journal of Vision and Ideas
Publisher : IAI Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/visa.v4i3.5409

Abstract

This research focuses on implementing the Quick Sort algorithm for sorting arrays based on specific criteria, with the aim of increasing computational efficiency in data management. Quick Sort was chosen because of its superiority in sorting data with an average time complexity of O(n log n), making it efficient for use on large datasets. This research applies this algorithm to student data sorted by NIM and name, and considers the grouping of student entry routes. The research results show that the implementation of Quick Sort in sorting student data not only speeds up the data processing process but also allows for more efficient processing in various data conditions.
Co-Authors Al-Hafiz, Ahmad Yusuf Alvansyah, Oka Nasution, Afifah Naila Silalahi, Anggi Tampubolon, Josua Deo Waruwu, Pedro Stella Mario Meyar