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Computer Science and Information Technologies
Published by Institute of Advanced Engineering and Science
ISSN : 2722323X     EISSN : 27223221     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Engineering
Computer Science and Information Technologies ISSN 2722-323X, e-ISSN 2722-3221 is an open access, peer-reviewed international journal that publish original research article, review papers, short communications that will have an immediate impact on the ongoing research in all areas of Computer Science/Informatics, Electronics, Communication and Information Technologies. Papers for publication in the journal are selected through rigorous peer review, to ensure originality, timeliness, relevance, and readability. The journal is published four-monthly (March, July and November).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 154 Documents
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Company clustering based on financial report data using k-means Firdaus, Gusti Aditya Aromatica; Wulandhari, Lili Ayu
Computer Science and Information Technologies Vol 5, No 3: November 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v5i3.p243-253

Abstract

Stock investment is the act of providing funds or assets to obtain future payments for gifts given. In its application, novice investors often make mistakes, one of which is not knowing the health condition of the company they want to target. By applying the machine learning clustering method based on company financial report data, it was found that 2 clusters were formed. This can show the current condition of the company so that it can be a consideration for investors, such as clusters of companies that have a profit trend that is always stable and increasing, or clusters of companies that are in the process of developing their business and groups of companies that have large amounts of debt from year to year.
Power of analytic tools in Oxygen Forensic® Detective based on NIST cybersecurity framework Sutikno, Tole; Busthomi, Iqbal
Computer Science and Information Technologies Vol 6, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i1.p8-19

Abstract

The National Institute of Standards and Technology (NIST) cybersecurity framework is a systematic approach for assessing and improving cybersecurity procedures in digital investigations. Oxygen Forensic® Detective is a digital forensic software that integrates multiple analytic tools to assist investigators in extracting valuable insights from digital evidence. The analytic tools, including timeline, social graph, image categorization, facial categorization, maps, data search, key evidence, optical character recognition, statistics, and translation, assist investigators in thoroughly analyzing digital artifacts, establishing connections, and accurately classifying images with precision and effectiveness. By incorporating these analytical resources into Oxygen Forensic® Detective, a comprehensive strategy is established to effectively combat cyber threats. The NIST cybersecurity framework is incorporated into the tool, offering a methodical approach to identifying and reducing cybersecurity risks. Law enforcement agencies can enhance the productivity and effectiveness of their forensic methodologies by implementing these advanced technologies. This can result in successful prosecutions and improved cybersecurity practices.  Overall, the utilization of analytical tools in criminological inquiries has experienced a substantial rise in the contemporary digital era.
Detection of android malware with deep learning method using convolutional neural network model Maulana, Reza; Stiawan, Deris; Budiarto, Rahmat
Computer Science and Information Technologies Vol 6, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i1.p68-79

Abstract

Android malware is an application that targets Android devices to steal crucial data, including money or confidential information from Android users. Recent years have seen a surge in research on Android malware, as its types continue to evolve, and cybersecurity requires periodic improvements. This research focuses on detecting Android malware attack patterns using deep learning and convolutional neural network (CNN) models, which classify and detect malware attack patterns on Android devices into two categories: malware and non-malware. This research contributes to understanding how effective the CNN models are by comparing the ratio of data used with several epochs. We effectively use CNN models to detect malware attack patterns. The results show that the deep learning method with the CNN model can manage unstructured data. The research results indicate that the CNN model demonstrates a minimal error rate during evaluation. The comparison of accuracy, precision, recall, F1 Score, and area under the curve (AUC) values demonstrates the recognition of malware attack patterns, reaching an average of 92% accuracy in data testing. This provides a holistic understanding of the model's performance and its practical utility in detecting Android malware.
Machine learning model approach in cyber attack threat detection in security operation center Saputra, Muhammad Ajran; Stiawan, Deris; Budiarto, Rahmat
Computer Science and Information Technologies Vol 6, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i1.p80-90

Abstract

The evolution of technology roles attracted cyber security threats not only compromise stable technology but also cause significant financial loss for organizations and individuals. As a result, organizations must create and implement a comprehensive cybersecurity strategy to minimize further loss. The founding of a cybersecurity surveillance center is one of the optimal adopted strategies, known as security operation center (SOC). The strategy has become the forefront of digital systems protection. We propose strategy optimization to prevent or mitigate cyberattacks by analyzing and detecting log anomalies using machine learning models. This study employs two machine learning models: the naïve Bayes model with multinomial, Gaussian, and Bernoulli variants, and the support vector machine (SVM) model with radial basis function (RBF), linear, polynomial, and sigmoid kernel variants. The hyperparameters in both models are then optimized. The models with optimized hyperparameters are subsequently trained and tested. The experimental results indicate that the best performance is achieved by the RBF kernel SVM model, with an accuracy of 79.75%, precision of 80.8%, recall of 79.75%, and F1-score of 80.01%; and the Gaussian naïve Bayes model, with an accuracy of 70.0%, precision of 80.27%, recall of 70.0%, and F1-score of 70.66%. Overall, both models perform relatively well and are classified in the very good category (75%‒89%).
Geoinformation system for monitoring forest fires and data encryption for low-orbit vehicles Moldamurat, Khuralay; Bakyt, Makhabbat; Yergaliyev, Dastan; Kalmanova, Dinara; Galymzhan, Anuar; Sapabekov, Abylaikhan
Computer Science and Information Technologies Vol 6, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i1.p58-67

Abstract

This article discusses two important aspects of unmanned aerial vehicles (UAVs): forest fire monitoring and data security for low-orbit vehicles. The first part of the article is devoted to the development of a geographic information system (GIS) for monitoring and forecasting the spread of forest fires. The system uses intelligent processing of aerospace data obtained from UAVs to timely detect fires, determine their characteristics and forecast the dynamics of development. The second part of the article focuses on the problem of high-speed encryption of data transmitted from low-orbit aircraft. An effective encryption algorithm is proposed that ensures high data processing speed and reliable protection of information from unauthorized access. The article presents the results of modeling and analysis of the effectiveness of the proposed solutions.
Matrix inversion using multiple-input multiple-output adaptive filtering Anjum, Muhammad Yasir Siddique; Iqbal, Javed
Computer Science and Information Technologies Vol 6, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i1.p1-7

Abstract

A new approach for matrix inversion is introduced. The approach is based on vector representation of multiple-input multiple-output (MIMO) channel matrix, in which the channel matrix is described by a linear combination of channel vectors weighted by their respective system inputs. The MIMO system output is then fed into a bank of adaptive filters, wherein the response of a given adaptive filter is iteratively minimized to match its output to the given system input. In doing so, adaptive filters equalize the impact of respective channel vectors on the MIMO channel output, while simultaneously orthogonalizing themselves from all other channel vectors, forming the channel matrix inverse. The method demonstrates satisfactory convergence and accuracy in Monte Carlo simulations conducted with varying signal-to-noise ratios (SNRs) and matrix conditioning scenarios. The suggested approach, by virtue of its adaptable characteristics, can also be employed for time-varying linear equation systems.
Retraction Notice: Quay crane assignment in container terminals using a genetic algorithm Sanaa, Aidi; Imane, Torbi; Mohamed, Mazouzi
Computer Science and Information Technologies Vol 6, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i1.p40-47

Abstract

Notice of Retraction: A. Sanaa, T. Imane, and M. Mohamed, "Quay crane assignment in container terminals using a genetic algorithm," Computer Science and Information Technologies, vol. 6, no. 1, 2023, pp. 40-47, doi: 10.11591/csit.v6i1.p40-47." This article has been determined to have contravened IAES publication principles following a thorough and thoughtful review of its content by a duly established expert committee, following the report of Hizia Amani and Rachid Chaib. In particular, the content of the following source was copied without proper attribution in this article: H. Amani, L. Bouyaya, R. Chaib, F. Z. Djekrif, and M. Aizi, "Optimization of Quay Crane Scheduling Problem at the Port of Algeria," in I. Kabashkin, I. Yatskiv, and O. Prentkovskis, Eds. Cham: Springer International Publishing, 2023, pp. 232–241, doi: 10.1007/978-3-031-26655-3_21. Consequently, IAES has removed the content of this article from this online system. The authors concurred with the decision to retract when it was communicated. Additionally, the authors requested that the article be removed.The article is not suitable for research or citation. We apologize for any inconvenience this may have caused.
Secure e-voting system using Schorr's zero-knowledge identification protocol Laleb, Indah Octaviani; Kasse, Daniel M.D.U.
Computer Science and Information Technologies Vol 6, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i1.p20-27

Abstract

In today's era of technological progress, the electoral system has changed significantly with the introduction of electronic voting (e-voting). The traditional voting system poses many vulnerabilities to manipulation, potential human error, and problems with voter privacy. These limitations can lead to reduced trust and participation in elections. E-voting has emerged to address this issue, aiming to improve the convenience, security, and privacy of voters. E-voting systems are evaluated on accuracy, security, privacy, and transparency; however, ensuring voter privacy while maintaining these principles remains a significant challenge. A potential solution to improving privacy in e-voting is Schorr's zero-knowledge identification protocol. This protocol allows voters to confirm their identity without revealing personal information, maintaining voter privacy throughout the process. By implementing these protocols, the e-voting system can strengthen security and privacy, making elections more transparent and trustworthy. As technology evolves, adopting solutions like Schorr's zero-knowledge identification protocol can help e-voting systems meet the growing demand for safe, fair, and private elections.
Field programmable gate array simulation and study on different multiplexer hardware for electronics and communication Kumar, Arvind; Kumar, Adesh; Agrawal, Anurag Vijay
Computer Science and Information Technologies Vol 6, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i1.p28-39

Abstract

Multiplexing is the technique of transmitting two or more separate signals concurrently using a single communication channel. Multiplexing enables the augmentation of communication channels and consequently the volume of data that may be transmitted. Communication networks utilize diverse multiplexing techniques. An input multiplexer amalgamates various network signals into a singular composite signal before transmission over a shared medium. The composite signal is broken back into its component signals by a demultiplexer, when it reaches its destination, allowing further operations to utilize them separately. The design of the hardware chip depends on the configuration of the multiplexer and demultiplexer in the communication system. The work is presented as a study of the digital logic design and simulation of the different configurations of the multiplexer hardware. The performance evaluation is carried out on the different series of Xilinx field programmable gate array (FPGA) such as Spartan-6, Spartan-3E, Virtex-5, and Virtex-6 with logically checked in Xilinx ISE waveform simulator software. The current analysis of the design and simulation of different configurations of the multiplexer design helps the designers to estimate the chip performance. The novelty of the work lies in its scalable and programmable architecture fitted for specific communication systems that assess performance based on latency, frequency, and power consumption that can be further linked with communication protocols.
Analysis of telehealth acceptance for basic life support training in sudden cardiac arrest in Pontianak Iswara, Ruhil; Kusumadewi, Sri; Kurniawan, Rahadian
Computer Science and Information Technologies Vol 6, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i1.p48-57

Abstract

Sudden cardiac arrest (SDA), which is one of the most prevalent causes of mortality, can be prevented by quickly conducting basic life support (BLS). In Pontianak City, the challenges associated with obtaining emergency health training, such as BLS, remain high. This study aims to evaluate user acceptance of telehealth as well as its effectiveness in BLS training. We will also discuss its impact on community knowledge and skills in managing cardiac arrest. We used the HOT-Fit method to analyze the level of acceptance of telehealth in BLS training. We collected data from 60 respondents who underwent telehealth-based BLS training. The results showed that participants' understanding and readiness in dealing with heart attack emergencies had increased significantly, by 90% and 92%, respectively. Analysis of the level of acceptance with HOT-Fit showed that system quality had the greatest influence on system use (0.611). Service quality exerted the most significant impact on user satisfaction (0.568). The net benefit was influenced by system use, user satisfaction, and organizational support, with user satisfaction having the greatest influence (0.600). Further research will be conducted on the utilization of augmented reality (AR) or virtual reality (VR) technology to implement telehealth for BLS training.

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