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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. 6 No. 1 (2022): Data Science: Journal of Computing and Applied Informatics (JoCAI)" : 5 Documents clear
The Role of Social Media on Student Consumer Behavior in the City of Bandung Stephani Putri Kawidjaya; Fandi Ahmad; Ayudhini Azzahra Permatasari
Data Science: Journal of Computing and Applied Informatics Vol. 6 No. 1 (2022): 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.v6.i1-5081

Abstract

The Covid-19 pandemic, which has had a significant impact, is no exception in Indonesia. This pandemic affects human interactions with one another and changes the economy quite significantly. Then there was a change in how to transact from what was previously offline to online and impacted changes in business processes. This research was conducted to see the influence of social media on the behavior of this research using a descriptive qualitative approach in which the researcher made observations through interviews, then observed the field and distributed questionnaires as well as several previous research studies, based on the data obtained, it was reprocessed into rigid information, from the results. Research shows that 85% of consumers come from adolescents aged 18-25 years, where this consumer segmentation has a big role because they actively use social media as a means or media, especially in terms of transactions in E-Commerce, so it does not rule out that shopping and online transactions are currently. This is proliferating in all corners of the world, especially in one of the big cities in Indonesia, namely the City of Bandung.
Predicting the Oil Investment Decision through Data Mining Empirical Evidence in Indonesia Oil Exploration Sector Harry Patria
Data Science: Journal of Computing and Applied Informatics Vol. 6 No. 1 (2022): 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.v6.i1-7539

Abstract

Petroleum investment decision remains subject to economic and financial research for decades. Due to capital intensive and higher risk on oil exploration, the investment decision has become more important than ever before. This study aims to shed some light on this issue by conducting four machine learning algorithms to predict the decision applying the dataset from 2007-2019. This study includes the Decision Tree, Random Forest, Naïve Bayes, and Support Vector Machine. A comparative performance analysis is the illustrated using confusion matrix, Cohen’s Kappa value, and the accuracy of each model and Area under the ROC Curve. In this study, a machine learning approach was carried out on the oil exploration data. The findings demonstrate that Naïve Bayes has the most accurate performance for the classification (94.5%), followed by Decision Tree (92.9%), Random Forest (90.9%), and Support Vector Machine (89.6%). In practice, the selected Naïve Bayes model was applied to assess the decision using a new data test. The findings can diminish the subjective blindness and confirmation bias in the investment decision and bring about a reasonable and orderly exploration and development of petroleum reserves.
An Optimized Wireless Network Architecture for Department of Agriculture, Region 1 Goldara, Ruel; Patacsil, Joseph
Data Science: Journal of Computing and Applied Informatics Vol. 6 No. 1 (2022): 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.v6.i1-7873

Abstract

In the emergence of the highly connected Internet of Things (IoT) and the rise of wireless network technologies, organizations are confronting expanded wireless network capability, stability, and reliability. Each organization that aims to manage wireless network services that customers and employees request must be robust, secured, and easy to manage, henceforth; optimized wireless network architecture ought to be a top priority. This study developed the optimized wireless network architecture for the Department of Agriculture, Region 1 to further provide a robust, more secure, and reliable wireless network design using a Prepare, Plan, Design, Implement, Operate and Optimize Methodology. The comparative and evaluative research design was used in determining the wireless network status of the current wireless network design of the Department of Agriculture, Region 1 into other agencies' wireless network designs and standards as well as the testing and implementation of the optimized wireless network architecture. Wireless network simulation and results of the wireless network design are interpreted using the Received Signal Strength Level (RSSL) and service coverage area. The testing of the optimized wireless network architecture shows that it is reliable, stable, robust, and secured and it is applicable in the agency.
Design of Informatic Logic Teaching Meterial Appication Using Ideal Problem Solving Based on Android Case Study in Universitas Pamulang Tita Puspitasari
Data Science: Journal of Computing and Applied Informatics Vol. 6 No. 1 (2022): 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.v6.i1-7412

Abstract

Basic Physics is a part of physics that studies about objects in nature, the symptoms of natural events and the interactions of objects in nature. This symptom is initially what our senses experience. For example, sight finds optics or light, hearing finds learning about sound, heat can also be felt (felt). In defining a quantity in physics, there must be rules for calculating the quantity in question based on other measurable quantities. In Basic Physics, it is necessary to understand the flow of questions well to how to calculate and explain them. However, sometimes students do not understand this course due to weakness in calculations or lack of understanding of material concepts and the use of formulas. For this reason, it is necessary to have the latest learning methods through Android to improve student understanding. The purpose of this paper is to determine whether the use of the IDEAL problem solving model based on Android is effective, because based on several researches, iDEAL problem solving can improve students' process skills, increase motivation and improve problem solving abilities. The results of this research are in the form of an application that is used as one of the innovative and android-based learning media so that it is more practical to learn anywhere and anytime.
The Applied Aproach Impact Information Security For Government and Company (A Review) Febriana, Henny; Dewi Sartika Br Ginting; Fuzy Yustika Manik; Mahyuddin
Data Science: Journal of Computing and Applied Informatics Vol. 6 No. 1 (2022): 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.v6.i1-7935

Abstract

The Government and industry are currently using information and communication technology a lot. The Government and companies in Indonesia have regulations on operational standards and management procedures for information and communication systems security at Government regarding implementing information system security. Information security is essential because there are many threats to information security. Information security in this era of Information and Communication Technology (ICT) is fundamental. Information Exchange Environment (IEE) vulnerabilities have increased as threats become more widespread and complex; therefore, information security has become a fundamental problem for businesses, organizations, and governments. So, in this paper, we will explain the review of the impact of Information Security For Government and companies in terms of threats and types of information security. Some security system methods are analyzed, among others—application Security, cloud security, Cryptography, security infrastructure, Incident response, and vulnerability management. The results of this review analysis, it known threat has several solutions, each depending on the type of threat for both the Government and the Company. Furthermore, Information Security is considered very important, especially for data stored in Government and companies.

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