cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Tole Sutikno
Contact Email
-
Phone
-
Journal Mail Official
ij.aptikom@gmail.com
Editorial Address
9th Floor, 4th UAD Campus Lembaga Penerbitan dan Publikasi Ilmiah (LPPI) Universitas Ahmad Dahlan
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
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 89 Documents
 5   6   7   8   9 
Selected advanced themes in ethical hacking and penetration testing Buthayna AlSharaa; Saed Thuneibat; Rawan Masadeh; Mohammad Alqaisi
Computer Science and Information Technologies Vol 4, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v4i1.p69-75

Abstract

Since 1980 cyberattacks have been evolving with the rising numbers of internet users and the constant evolving of security systems, and since then security systems experts have been trying to fight these kinds of attacks. This paper has both ethical and scientific goals, ethically, to raise awareness on cyberattacks and provide people with the knowledge that allows them to use the world wide web with fewer worries knowing how to protect their information and their devices with what they can. Scientifically, this paper includes a deep understanding of types of hackers, attacks, and various ways to stay safe online. This research investigates how ethical hackers adapt to the current and upcoming cyber threats. The different approaches for some famous hacking types along with their results are shown. Python and Ruby are used for coding, which we run on Kali Linux operating system.
Antispoofing in face biometrics: A comprehensive study on software-based techniques Vinutha H; Thippeswamy G
Computer Science and Information Technologies Vol 4, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v4i1.p1-13

Abstract

The vulnerability of the face recognition system to spoofing attacks has piqued the biometric community's interest, motivating them to develop anti-spoofing techniques to secure it. Photo, video, or mask attacks can compromise face biometric systems (types of presentation attacks). Spoofing attacks are detected using liveness detection techniques, which determine whether the facial image presented at a biometric system is a live face or a fake version of it. We discuss the classification of face anti-spoofing techniques in this paper. Anti-spoofing techniques are divided into two categories: hardware and software methods. Hardware-based techniques are summarized briefly. A comprehensive study on software-based countermeasures for presentation attacks is discussed, which are further divided into static and dynamic methods. We cited a few publicly available presentation attack datasets and calculated a few metrics to demonstrate the value of anti-spoofing techniques.
Pakistan sign language to Urdu translator using Kinect Saad Ahmed; Hasnain Shafiq; Yamna Raheel; Noor Chishti; Syed Muhammad Asad
Computer Science and Information Technologies Vol 3, No 3: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v3i3.p186-193

Abstract

The lack of a standardized sign language, and the inability to communicate with the hearing community through sign language, are the two major issues confronting Pakistan's deaf and dumb society. In this research, we have proposed an approach to help eradicate one of the issues. Now, using the proposed framework, the deaf community can communicate with normal people. The purpose of this work is to reduce the struggles of hearing-impaired people in Pakistan. A Kinect-based Pakistan sign language (PSL) to Urdu language translator is being developed to accomplish this. The system’s dynamic sign language segment works in three phases: acquiring key points from the dataset, training a long short-term memory (LSTM) model, and making real-time predictions using sequences through openCV integrated with the Kinect device. The system’s static sign language segment works in three phases: acquiring an image-based dataset, training a model garden, and making real-time predictions using openCV integrated with the Kinect device. It also allows the hearing user to input Urdu audio to the Kinect microphone. The proposed sign language translator can detect and predict the PSL performed in front of the Kinect device and produce translations in Urdu.
The effect of segmentation on the performance of machine learning methods on the morphological classification of Friesien Holstein dairy cows Amril Mutoi Siregar; Yohanes Aris Purwanto; Sony Hartono Wijaya; Nahrowi Nahrowi
Computer Science and Information Technologies Vol 4, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v4i1.p59-68

Abstract

Many classification algorithms are in the form of image pattern recognition; the approach to the complexity of the problem should be a feature of feasibility for representing images. The morphology of dairy cows greatly affects their health and milk production. The paper will apply several classification methods based on the morphology of Holstein Friesian dairy cows. To improve the accuracy of the model used, the segmentation process is the right step. In this paper, we compare several machine learning algorithms to get optimal accuracy. The algorithm used a support vector machine (SVM), artificial neural networks, random forests and logistic regression. Segmentation methods used are mask region-based convolutional neural network (R-CNN) and Canny; optimal accuracy is expected to create intelligent applications. The success of the method is measured with accuracy, precision, recall, and F1 Score, as well as testing by conducting a training-testing ratio of 90:10 and 80:20. This study discovered an artificial neural network optimal model with Canny with an accuracy of 82.50%, precision of 87.00%, recall of 79.00%, F1-score of 81.62%, and testing ratio of 90:10. While the models with the highest 80:20 ratio achieved 84.39% accuracy, 88.46% precision, 80.47%, and 83.00% F1-score with mask R-CNN with logistic regression.
Fraudulent transactions detection on cryptocurrency blockchain: a machine learning approach Anoop Reddy Thatipalli; Vijayakumar Kuppusamy
Computer Science and Information Technologies Vol 4, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v4i1.p%p

Abstract

Blockchain technologies have gained a huge amount of importance in recent years, and the use of the blockchain concept in cryptocurrency transactions has always gained the faith of industrial standards. Ethereum is a blockchain platform that allows customers to conduct cryptocurrency transactions, which are then used to build and deploy the API using smart contracts. Blockchain can be used to change the value of money in crypto exchanges and banking systems. even though the blockchain system is consistent and reliable. Attackers still try to steal the money by executing well-known techniques like Ponzi scheme attacks or by using malware software. As the participants in the Ethereum platform are "anonymous," users can access multiple accounts under the same hash identity. As a result, it will be difficult to find the malicious users who are contributing to the fraudulent activities. Although activities such as Ponzi schemes are to be monitored by the authority in order to keep the API safe from scammers and the platform legitimate, In this paper, we detect malicious transaction nodes with the help of machine learning-based anomaly detection and also give the structural architecture for creating a secure API wallet, which solves the basic security protection from Ponzi-scheme multiple identity attacks by introducing KYC contracts in smart contracts of the Ethereum platform such that no duplicate users can misuse the cryptocurrencies. In this case, we use two different machine learning models that detect with a 95.24% accuracy and a 0.88% false positive ratio. and then we compare the capabilities of random forest and support vector machine classifiers to identify the anomaly-based accounts, which are on datasets of around 300 accounts. By introducing HD-Wallets for API, we show the rules for digital wallets and cryptocurrency transactions that protect against malware.
Improved authenticated elliptic curve cryptography scheme for resource starve applications Esau Taiwo Oladipupo; Oluwakemi Christiana Abikoye
Computer Science and Information Technologies Vol 3, No 3: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v3i3.p169-185

Abstract

Elliptic curve cryptography (ECC) remains the best approach to asymmetric cryptography when it comes to securing communication among communication partners in low-computing devices such as wireless sensor networks (WSN) and the Internet of Things (IoT) due to its effectiveness in generating small keys with a strong encryption mechanism. The ECC cuts down on power use and improves device performance, so it can be used in a wide range of devices that don't have a lot of resources. However, most of the existing ECC implementations suffer from implementation flaws that make them vulnerable to cryptanalysis attacks. In this study, flaws in the existing implementation of ECC are identified. A new scheme where the identified flaws are remedied was developed. The results of the security analysis show that the new scheme is an indistinguishable authenticated adaptive chosen ciphertext attack (IND-CCA3), resistant to malleability and man-in-the-middle attacks (MIMA). The results of comparative security analysis show that the mapping scheme employed in the new scheme maps any blocks of plaintext to distinct points on an elliptic curve, which makes it resistant to all attacks that the existing schemes are vulnerable to without having a negative effect on its encryption and decryption time, throughput, or power consumption.
The antecedent e-government quality for public behaviour intention, and extended expectation-confirmation theory Taqwa Hariguna; Untung Rahardja; Qurotul Aini
Computer Science and Information Technologies Vol 4, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v4i1.p33-42

Abstract

An The main objective of the study is to identify the antecedent of leadership quality, public satisfaction and public behaviour intention of e-government service. Also, this study integrated e-government quality to expectation-confirmation model. In order to achieve these goals, observational research was then carried out to collect primary information, using the method of data dissemination and obtaining the opinion of 360 from the public using the e-government service and some of the e-government and software quality experts. The results of the study show that the positive association among the e-government services quality and public perceived usefulness, public expectation confirmation, leadership quality and public satisfaction that also play a positive role on the public behavior intention.
Exploring application portfolio management in Indonesia: A case study of the Indonesia agency for the assessment and application of technology Riri Kusumarani; Raden Putri Ayu Pramesti
Computer Science and Information Technologies Vol 4, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v4i1.p76-84

Abstract

Due to rapid information and communication technology (ICT) growth, government agencies must manage more digital apps to support public service operations and administration. In Indonesia, at least 400,000 applications have been received by various ministries and government agencies. This amount will hurt the ICT budget’s investment and waste if no approach is employed. Problems can be solved with application portfolio management (APM). Indonesian government agencies’ AMP implementation is unclear. APM is applied at the government research institute agency for the assessment and application of technology (BPPT) in this study. BPPT was chosen due to APM’s lack of ICT investment management. This research examined 41 submissions from the 2019 digital transformation initiative. APM selected two mapping models. The outcome indicates how APM may offer ICT strategies for current applications to government entities. This analysis mapped existing applications into two models: McFarlan’s strategic grid and gartner’s TIME model. Mapping findings from these two models-technical health evaluations and regulatory compliance-may be used for application sustainability suggestions. 11 treatments were advised for maintenance and investment, while 4 applications were recommended for removal. This research helps us understand how the Indonesian government institute maintains its application portfolio and how APM might be a valuable method for application management.
A preliminary empirical study of react library related questions shared on stack overflow Ganno Tribuana Kurniaji; Yusuf Sulistyo Nugroho; Syful Islam
Computer Science and Information Technologies Vol 4, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v4i1.p14-23

Abstract

React is a JavaScript library to develop user interfaces for single-page applications. Developers utilize react to build large web apps that allow users to update data without refreshing the page. Despite its benefits, many developers face react-related issues in the implementation. To find a solution, developers commonly shared and discussed their issues on stack overflow (SO). Although recent studies have demonstrated the benefits of utilizing react in web development, the trends of the users’ attentions remain unknown. In this study, we conducted a preliminary empirical study of react library-related questions shared on SO. We applied an exploratory data analysis technique to investigate the distribution of problems shared by the developers. The findings reveal that although the quantity of react-related topics on SO has risen over time, community interest is beginning to decrease. This is shown by the increase of the unsolved questions and the decrease of the number of views per year. Regarding the react users’ activity, most of them are more active in providing answers rather than commenting and providing scores. The findings of this study might point to future research that recommends approaches to assist the react community in overcoming issues while using react in the early phases.
Investigating the impact of data scaling on the k-nearest neighbor algorithm Muasir Pagan; Muhammad Zarlis; Ade Candra
Computer Science and Information Technologies Vol 4, No 2: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v4i2.p135-142

Abstract

This study investigates the impact of data scaling techniques on the performance of the k-nearest neighbor (KNN) algorithm using ten different datasets from various domains. Three commonly used data scaling techniques, min-max normalization, Z-score, and decimal scaling, are evaluated based on the KNN algorithm's performance in terms of accuracy, precision, recall, F1-score, runtime, and memory usage. The study aims to provide insights into the applicability and effectiveness of different scaling techniques in different contexts, aid in the design and implementation of machine learning systems, and help identify the strengths and weaknesses of each technique and their suitability for specific types of data. The results show that data scaling significantly affects the performance of the KNN algorithm, and the choice of scaling method can have significant implications for practical applications. Moreover, the performance of the three scaling techniques varies across different datasets, suggesting that the choice of scaling technique should be made based on the specific characteristics of the data. Overall, this study provides a comprehensive analysis of the impact of data scaling techniques on the KNN algorithm's performance and can help practitioners and researchers in the machine learning community make informed decisions when designing and implementing machine learning systems.

Page 7 of 9 | Total Record : 89

 5   6   7   8   9 

Filter by Year

2020 2023


Reset
Filter By Issues
All Issue Vol 4, No 3: November 2023 (In Progress) Vol 4, No 2: July 2023 Vol 4, No 1: March 2023 Vol 3, No 3: November 2022 Vol 3, No 2: July 2022 Vol 3, No 1: March 2022 Vol 2, No 3: November 2021 Vol 2, No 2: July 2021 Vol 2, No 1: March 2021 Vol 1, No 3: November 2020 Vol 1, No 2: July 2020 Vol 1, No 1: May 2020 List of Accepted Papers (with minor revisions) More Issue