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Data Science: Journal of Computing and Applied Informatics
Published by Universitas Sumatera Utara
ISSN : 25806769     EISSN : 2580829X     DOI : -
Core Subject : Science,
Computer Science & IT
Data Science: Journal of Computing and Applied Informatics (JoCAI) is a peer-reviewed biannual journal (January and July) published by TALENTA Publisher and organized by Faculty of Computer Science and Information Technology, Universitas Sumatera Utara (USU) as an open access journal. It welcomes full research articles in the field of Computing and Applied Informatics related to Data Science from the following subject area: Analytics, Artificial Intelligence, Bioinformatics, Big Data, Computational Linguistics, Cryptography, Data Mining, Data Warehouse, E-Commerce, E-Government, E-Health, Internet of Things, Information Theory, Information Security, Machine Learning, Multimedia & Image Processing, Software Engineering, Socio Informatics, and Wireless & Mobile Computing. ISSN (Print) : 2580-6769 ISSN (Online) : 2580-829X Each publication will contain 5 (five) manuscripts published online and printed. JoCAI strives to be a means of periodic, accredited, national scientific publications or reputable international publications through printed and online publications.
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Articles 91 Documents
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Narrative Literature Review : The Role of Ethics in Business Information Aprilia, Cindy
Data Science: Journal of Computing and Applied Informatics Vol. 8 No. 2 (2024): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v8.i2-15855

Abstract

Abstract. This paper investigates the critical role of ethics in business information, highlighting the challenges posed by the rapid evolution of ICT, which can hardly be addressed by formal legislative responses. A narrative literature review has been conducted to study how computer ethics acts as guidance in addressing the ambiguities and "grey areas" encountered in this field. Through a detailed exploration of the definitions, importance, objectives, and dimensions of computer ethics, the study showcases real-life examples of ethical dilemmas in information rights, property rights, accountability, system quality, and quality of life. The paper concludes that integrating ethical considerations into business practices is essential for responsible and sustainable digital transformation and for filling the gaps where laws may still blur. Keyword: Computer Ethics, Business Information Technology, Digital Transformation, Ethical Dilemmas, ICT, Legal Ambiguities, Sustainable Digital Transformation. Abstrak. Karya tulis ini membahas mengenai peran daripada etika terhadap perkembangan bisnis terkait teknologi informasi, dengan menekankan terhadap tantangan yang dihadapi oleh bisnis terkait perubahan ICT yang sangat cepat, dan sulit terkejar oleh perubahan legalitas. Penelitian dengan tinjauan literatur naratif dilakukan untuk mempelajari bagaimana etika dapat memberikan tuntunan untuk menhadapi ambiguitas dan “area abu-abu” daripada penerapan teknologi didalam bisnis terkait teknologi informasi. Melalui eksplorasi terperinci mengenai definisi, kepentingan, tujuan, dan dimensi etika komputer, penelitian ini menampilkan contoh nyata dilema etika dalam hak informasi, hak milik, akuntabilitas, kualitas sistem, dan kualitas hidup. Karya tulis ini menyimpulkan bahwa mengintegrasikan pertimbangan etis ke dalam praktik bisnis sangat penting untuk transformasi digital yang bertanggung jawab dan berkelanjutan serta untuk mengisi kesenjangan di mana undang-undang masih kabur. Kata Kunci: Etika Komputer, Bisnis Teknologi dan Informasi, Transformasi Digital, Dilema Etika, ICT, Ambiguitas atas Legalitas, Transformasi Digital Berkelanjutan.
Analysis Sentiment Of Users Internet Service Providers In Indonesia On Social Media X Using Support Vector Machine Fachrurrozy Nurqoulby; Amalia Anjani Arifiyanti; Dhian Satria Yudha Kartika
Data Science: Journal of Computing and Applied Informatics Vol. 8 No. 2 (2024): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v8.i2-16317

Abstract

Various internet service providers are starting to appear in Indonesia, they are competing to provide attractive offers to attract customers. Through social media, someone can find out opinions about whether internet service providers provide services as offered. X, formerly known as Twitter, is a social media platform where people can give their opinions in the form of posts. Various opinions were expressed by the public, ranging from positive, neutral, to negative. This research aims to create a post classification model regarding users of internet service providers into three sentiment classes, namely positive, neutral and negative. The model is created through several stages, such as data retrieval, data labeling, data preprocessing, data division, term weighting, and creating a classification model using the Support Vector Machine algorithm. The results of this research show that the SVM model with a Linear kernel obtained the highest accuracy of 83% compared to the RBF kernel SVM and Polynomial kernel SVM, with an F1-score of 90% for the negative class, 66% for the neutral class, and 65% for the positive class.
Implementing 6G via Non-Terrestrial Networks (NTN): Considerations for High Altitude Platform Stations (HAPS) Anicho, Ogbonnaya
Data Science: Journal of Computing and Applied Informatics Vol. 8 No. 2 (2024): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v8.i2-16765

Abstract

Non-terrestrial networks (NTN) covering space-based and airborne network assets will be crucial for 6G delivery. Satellite constellations constitute a significant part of the NTN infrastructure but have certain limitations like long latency and Doppler shifts. High Altitude Platform Stations (HAPS) will complement the role of satellite systems and add significant value to the 6G NTN offering. This article draws the attention of the 6G development ecosystem to the need to prioritise HAPS studies and specifications. HAPS NTN will address three main factors relevant to 6G NTN deployments: Technology limitations of satellites, complexities of operations, automation and maintenance (OAM) and futureproofing 6G NTN. Wireless technologies change in 10-year cycles on average. However, intra-cycle changes (evolutions) also occur, further shortening the actual spans of the technology cycles. HAPS NTN can future-proof 6G NTN since it is retrievable for upgrades, retooling or redesign. Satellite systems will be highly exposed if these intra-cycle evolutions need hardware upgrades. Softwarisation and virtualisation would be helpful but do not eliminate the risk. This paper addresses the need to elevate the consideration for HAPS in 6G studies as it may serve as the ultimate technology guarantee for the success of 6G NTN.
Fuzzy Approach For Determining Statistical Process Control (Spc) Tools Location On Production Floor Ishola, Christie Y.; Olabode, Adewoye S.
Data Science: Journal of Computing and Applied Informatics Vol. 8 No. 1 (2024): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v8.i1-17137

Abstract

Statistical Process Control (SPC) is a technical tool that is used to control and to improve almost any kind of process. However, because of cost consideration, management need to decide which process should apply SPC. In this paper, we propose the use of probability and fuzzy membership function to determine SPC allocation. Conditional probability is used to analyse process failure rate and process repair rate. Then, using Markov Matrix, we calculate the probability of out-of-control process (PO). Nevertheless, in a production line that consists of many parts, the probability value is not adequate to be used as a reference to determine SPC allocation. There are cases for instance, where the value of PO in one part does not mean the same as in other parts since each part may have different sensitivity degree to the final product. For example 0.25 of PO in part 1 may have higher influence to the final product compare to 0.25 of PO in part 2 or part 3. Furthermore, we cannot randomly choose one of those parts to apply SPC or even decide to apply SPC in all parts of the production line. To overcome this problem we propose fuzzy membership function that uses linguistic terms and degree of memberships to analyse PO instead of the probability values. By this mean, the SPC allocation could be determined without ambiguity. For this purpose, the membership function is classified into three categories, namely LOW, MEDIUM and HIGH. Any part with PO fall into the “HIGH” category and high degree of membership is prioritized to apply SPC.
A Review on Metaheuristic Approaches for Job-Shop Scheduling Problems Abdolrazzagh-Nezhad, Majid; Abdullah, Salwani
Data Science: Journal of Computing and Applied Informatics Vol. 8 No. 1 (2024): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v8.i1-17138

Abstract

Over the past several decades, interest in metaheuristic approaches to address job-shop scheduling problems (JSSPs) has increased due to the ability of these approaches to generate solutions which are better than those generated from heuristics alone. This article provides a significant attention on reviewing state-of-the-art metaheuristic approaches that have been developed to solve JSSPs. These approaches are analysed with respect to three steps: (i) preprocessing, (ii) initialization procedures and (iii) improvement algorithms. Through this review, the paper highlights the gaps in the literature and potential avenues for further research.
Simulation of Vehicle Distance Detection for Traffic Order Baldemor, Milagros Racacho
Data Science: Journal of Computing and Applied Informatics Vol. 8 No. 1 (2024): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v8.i1-17139

Abstract

The use of ultrasonic sensors, especially HC-SR04, in microcontroller projects is expanding thanks to its ability to accurately detect distance. In this final project, the HC- SR04 is connected to an ESP32 to measure the distance of an object and provide feedback in the form of sound when the object approaches the sensor within a certain distance. The HC-SR04 sensor works by emitting ultrasonic waves and measuring the time it takes for the waves to reflect back to the sensor. The ESP32, as the microcontroller connected to the sensor, processes this time data to calculate the object's distance from the sensor. When the distance of the object is below a predetermined threshold, the ESP32 will activate the buzzer as a sound signal. This implementation can be applied in various systems, for this test we used it on the zebra crossing system automatically. The test results show that this system is able to detect distance with sufficient accuracy and provide a fast and consistent sound response according to changes in object distance.
A Hybrid Cryptosystem Using Rprime RSA And Extended Tiny Encryption (XTEA) For Securing Message Santoso, Zikri Akmal; Budiman, Mohammad Andri; Efendi, Syahril
Data Science: Journal of Computing and Applied Informatics Vol. 9 No. 1 (2025): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v9.i1-16574

Abstract

Abstract. Ensuring the security of messages in sending message publicly is very important, we must ensure the security of messages with one of security method called cryptography. Focusing solely on security can affect the speed of message delivery processes. Therefore, this research is conducted to provide solutions to both of these issues. Thus, this research will discuss the Analysis of Hybrid Cryptography Scheme in the combination of RPrime RSA and XTEA (Extended Tiny Encryption) in securing instant messages. Hybrid cryptography is one of the methods in cryptography that allows to enhance speed of message delivery with messages encrypted by symmetric algorithms and the symmetric algorithm keys will be encrypted using asymmetric algorithms, public keys. RPrime RSA is an asymmetric public key algorithm and one variant of RSA, which is a combination of Rebalanced RSA and MPrime RSA algorithms. XTEA is a symmetric key algorithm and improved version of the TEA algorithm. This research tested by using strings with uppercase letter, numeric, and punctuation characters with the value of k in RPrime RSA from 2 to 6 with unconstrained modulus digits. The result of the test indicate that the required time for encryption and decryption is proportional, the time processing for factorization to get d is proportional to the value of k.
Towards Automated Motor Impulsivity Monitoring in Real-world Scenarios: A Multiple Object Tracking Approach Dalimarta, Fahmy; Andono, Pulung Nurtantio; Soeleman, Moch. Arief; Hasibuan, Zainal Arifin
Data Science: Journal of Computing and Applied Informatics Vol. 9 No. 1 (2025): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v9.i1-16686

Abstract

Assessment of motor impulsivity often faces several challenges. Conventional assessments that rely on controlled settings often fail to capture impulsive behaviors in real-world contexts. This study proposes an automated approach using Multiple Object Tracking (MOT) technology to assess motor impulsivity. The aim was to develop a system for detecting and quantifying motor impulsivity in naturalistic, multi-person environments. By employing cutting-edge MOT algorithms, the solution tracks multiple individuals concurrently, enabling movement and interaction analyses. This methodology integrates MOT with behavioral models to identify motor impulsivity patterns such as abrupt trajectory changes or impulsive gesturing. Trained on real-world annotated datasets, the system ensures adaptability across settings. Our approach successfully distinguished impulsive movements from typical behavioral patterns, with an accuracy of 95.43%. This approach could revolutionize assessments by providing objective and quantitative measurements and facilitating enhanced diagnostics and personalized interventions. Extensive evaluations are required to assess real-time capabilities, robustness in occluded environments, and accurate impulsive pattern identification. These findings could enable broader clinical, research, and behavioral monitoring applications, advancing our understanding of the implications of motor impulsivity.
Phishing Detection Techniques: A review Abdolrazzagh-Nezhad, Majid; Langarib, Nafise
Data Science: Journal of Computing and Applied Informatics Vol. 9 No. 1 (2025): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v9.i1-19904

Abstract

Phishing remains one of the most pervasive and sophisticated threats to cybersecurity, exploiting human and system vulnerabilities to compromise sensitive information. This study systematically reviews and categorizes phishing detection techniques into four groups: anti-phishing tools, heuristic approaches, machine learning-based techniques, and metaheuristic algorithms. Each method is critically analyzed for its effectiveness, highlighting their strengths and limitations. The review identifies significant advancements in phishing detection, such as the adoption of hybrid techniques and real-time detection algorithms, while also addressing gaps, including handling zero-day phishing attacks and scalability in large datasets. The findings provide a roadmap for future research, encouraging the development of more robust, adaptive, and efficient solutions. This comprehensive analysis not only synthesizes the state-of-the-art in phishing detection but also lays the groundwork for designing next-generation defense mechanisms.
Economy and banking sector performance: Spillover effect of Uncertainty of Covid-19 on Non-performing loans of Turkish Agricultural sector Olorogun, Lukman Ayinde; Kamil, Anton Abdulbasah
Data Science: Journal of Computing and Applied Informatics Vol. 9 No. 1 (2025): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v9.i1-19905

Abstract

This spillover index research paper tries to find connectedness between Non-performing loans (NPL) and Covid-19 global pandemic specifically in the Turkish agricultural sector. The research covers variables of NPL, Geopolitical risk index (GPR), Fishing, Agriculture, Non-performing loans to total assets (NPL_TCL), Return on assets (ROA), Return on equity (ROE). The data for this research includes a monthly time series dataset covering between Dec. 2004–April 2020. To perform the statistical analysis descriptive statistics, correlation matrix with its T-statistics and probabilities, and Dielbold and Yilmaz index were adopted to uncover the level of connectedness among the group. The descriptive statistics results of the group reveal that all variables understudy were contributing factors to the increase of NPL of the banking sector in general. Specifically, the agricultural sector’s NPL has a significant effect on the banking sector’s aggregate NPLs. The correlation analysis indicated that there is a higher correlation between NPL and agriculture, Fishing, Timber, and a moderate average correlation between NPL and Hunting. Similarly, a moderate high correlation amongst individual agricultural sectors i.e. Hunting, Fishing, Agriculture, Timber and as well as higher correlation between ROA and ROE that are under consideration. This shows that there is somehow acceptable interconnectedness among the group. The results of the spillover index effects through Dielbold and Yilmaz procedure revealed a total spillover effect 57.3%. Whereas, another unexplained effect in this study is 43.7% which might be as a result random noise in the dataset due to impact of Covid-19 pandemic. This research is significant as it is first of its kind on a proof of spillover from the empirical viewpoints as it related to Turkey on level of spillover and its impacts on the NPLs of the banking sector measuring the agricultural sector’s contribution.

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