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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 5 Documents
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Search results for , issue "Vol. 8 No. 2 (2024): Data Science: Journal of Computing and Applied Informatics (JoCAI)" : 5 Documents clear
Analysis of Employee Work Stress Using CRISP-DM to Reduce Work Stress on Reasons for Employee Resignation Emral Hakim; Ahmad Muklason
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.i2-14615

Abstract

Internal audit activities at EPC companies have found a trend of increasing work stress as a reason for employee resignation in the period Q4 2021 - Q1 2023. In implementing ISO 45001:2015 this must be controlled because it is a psychological occupational disease. For this reason, a work stress survey was carried out, the results of which were reviewed using Cross Industry Standard Process for Data Mining (CRISP-DM). Descriptive analysis found a maximum ratio of moderate stress of 66%, light stress of 39%, and severe stress of 9% with a risk matrix in Medium (yellow area). Descriptive analysis found a maximum ratio of moderate stress of 66%, light stress of 39%, and severe stress of 9% with a risk matrix in Medium (yellow area). Diagnostic analysis found a total of 19 questionnaires that affected severe stress and moderate stress. Cluster K-Modes shows 3 clusters being centroids with principal component values explaining around 4.92% of the original feature variance. The deployment of work stress control is carried out through focus group discussion to formulate Socialization, Externalization, Combination, Internalization (SECI) as a follow-up program for organization.
Deciphering the Key Drivers of Sustainability : Harnessing Artificial Intelligence in Data Analytics to Unravel the Dynamics of Decarbonisation in Pursuit of Sustainable Development Patria, Harry; Djuwita A. Rahim
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.i2-15005

Abstract

In the epoch where climate change poses an existential threat to humanity, understanding the intricate dynamics of CO2 emissions is more critical than ever. This study embarks on an ambitious journey to unravel the complex interplay of factors influencing carbon emissions, leveraging the prowess of Artificial Intelligence (AI) and the analytical capabilities of Power BI. Anchored in the context of the United Nations' Sustainable Development Goals (SDGs), this research transcends traditional analytical boundaries, offering a novel lens to view and interpret environmental data. At the heart of this exploration lies the UN SDG dataset, a rich tapestry of environmental, economic, and social indicators. The study's methodology is a fusion of advanced AI techniques with Power BI's visualization influencers, a combination that not only promises precision but also an unprecedented depth of insight. This dual approach enables a multifaceted analysis, capturing the nuances and subtleties often lost in conventional studies. The findings of this research are both revealing and transformative. They shed light on the significant yet varied factors that drive CO2 emissions across different geographical and socio-economic landscapes. The study unveils a striking correlation between increased access to electricity and GDP per capita with rising carbon emissions, a pattern particularly pronounced in developing regions. Conversely, in more developed contexts, the analysis reveals a complex interplay between emissions, literacy rates, and fertility rates, suggesting indirect yet potent pathways through which socio-economic development influences environmental outcomes. The insights gleaned offer a beacon for policymakers, illuminating the pathways to tailor environmental strategies that resonate with the unique needs of different regions. For developing nations, the study advocates for policies that intertwine educational and family planning initiatives with environmental objectives. In contrast, for developed countries, it underscores the need for technological innovation and efficiency improvements. The study's innovative use of AI and Power BI sets a new precedent in environmental research, demonstrating the immense potential of these tools in shaping sustainable futures.
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.

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