Using Big Data Analytics for Decision Making: Analyzing Customer Behavior using Association Rule Mining in a Gold, Silver, and Precious Metal Trading Company in Indonesia

Yudhistyra, Wecka Imam; Risal, Evri Marta; Raungratanaamporn, I-soon; Ratanavaraha, Vatanavongs

doi:10.18517/ijods.1.2.57-71.2020

Cited by 10 publications

(9 citation statements)

References 22 publications

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“…As the development of industry in the second decade of the new millennium progressed, analytics’ next-generation also started improving. The first step toward progress was increased device complexity, which needed revolutions in manufacturing procedures; e.g., we design 3D devices now rather than 2D, and new devices such as FinFET [ 14 ] were conceived [ 15 , 16 ]. The second step was lead by the new market drivers, which were toward lower power but faster and smaller devices.…”

Section: Related Workmentioning

confidence: 99%

Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing

Shahbazi

Byun

2021

Sensors

110

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Smart manufacturing systems are growing based on the various requests for predicting the reliability and quality of equipment. Many machine learning techniques are being examined to that end. Another issue which considers an important part of industry is data security and management. To overcome the problems mentioned above, we applied the integrated methods of blockchain and machine learning to secure system transactions and handle a dataset to overcome the fake dataset. To manage and analyze the collected dataset, big data techniques were used. The blockchain system was implemented in the private Hyperledger Fabric platform. Similarly, the fault diagnosis prediction aspect was evaluated based on the hybrid prediction technique. The system’s quality control was evaluated based on non-linear machine learning techniques, which modeled that complex environment and found the true positive rate of the system’s quality control approach.

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Section: Related Workmentioning

confidence: 99%

Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing

Shahbazi

Byun

2021

Sensors

110

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“…Another report by Gartner [10] guesses that about 2017, almost half of the users would need to utilize their devices for purposes of work. BYOD does increase productivity and helps get things done virtually from anywhere, but a certain solution is needed to compensate the risk factors involved [32].…”

Section: ) Bring Your Own Device (Byod)mentioning

confidence: 99%

“…Users must have flexibility to protect specific documents they want. A complete system-level security hampers the performance and is very user intrusive which may lead to users finding a way around and defeating the purpose of information protection [32].…”

Section: Cloud Security Solution Requirementmentioning

confidence: 99%

Cloud Computing Issues, Challenges, and Needs: A Survey

Aljanabi

Abd-Alwahab

Saedudin

et al. 2021

JOIV : Int. J. Inform. Visualization

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Cloud computing represents a kind of computing that is based on the sharing of computing resources instead of possessing personal devices or local servers for handling several applications and tasks. This kind of computing includes three distinguished kinds of services provided remotely for clients that can be accessed by using the Internet. Typically, clients work on paying annual or monthly service fees for suppliers, in order to gain access to systems that work on delivering infrastructure as a service, platforms as a service, and software as a service for any subscriber. In this paper, the usefulness and the abuse of the cloud computing are briefly discussed and presented by highlighting the influences of cloud computing in different areas. Moreover, this paper also presents the kinds and services of cloud. In addition, the security issues that cover the cloud security solution requirements, and the cloud security issues, which is one of the biggest issues in recent years in cloud computing were presented in this paper. The security requirement that needs by the cloud computing covers privacy, lack of user control, unauthorized secondary usage, and finally data proliferation and data flow. Meanwhile, the security issues cover including ownership of device, the trust issue and legel aspects. To overcome the security issues, this paper also presents the solution at the end of this paper.

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“…This is due, primarily, to the faster and lower cost hardware, [1] [2,3] the emergence of new paradigms that thrive on user-generated data such as social networks, and the recognition of the importance of utilizing raw data (which was previously useless) in obtaining new information that are vital to deal with a variety of real-life issues. Distributed flow computing [4][5][6] is now an inevitable processing paradigm [7][8][9][10]. It allows to obtain continuous and real-time results from huge amounts of recent data.…”

Section: Introductionmentioning

confidence: 99%

A Review on Big Data Stream Processing Applications: Contributions, Benefits, and Limitations

Alwaisi

Abbood²,

Jalil

et al. 2021

JOIV : Int. J. Inform. Visualization

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The amount of data in our world has been rapidly keep growing from time to time. In the era of big data, the efficient processing and analysis of big data using machine learning algorithm is highly required, especially when the data comes in form of streams. There is no doubt that big data has become an important source of information and knowledge in making decision process. Nevertheless, dealing with this kind of data comes with great difficulties; thus, several techniques have been used in analyzing the data in the form of streams. Many techniques have been proposed and studied to handle big data and give decisions based on off-line batch analysis. Today, we need to make a constructive decision based on online streaming data analysis. Many researchers in recent years proposed some different kind of frameworks for processing the big data streaming. In this work, we explore and present in detail some of the recent achievements in big data streaming in term of contributions, benefits, and limitations. As well as some of recent platforms suitable to be used for big data streaming analytics. Moreover, we also highlight several issues that will be faced in big data stream processing. In conclusion, it is hoped that this study will assist the researchers in choosing the best and suitable framework for big data streaming projects.

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Using Big Data Analytics for Decision Making: Analyzing Customer Behavior using Association Rule Mining in a Gold, Silver, and Precious Metal Trading Company in Indonesia

Cited by 10 publications

References 22 publications

Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing

Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing

Cloud Computing Issues, Challenges, and Needs: A Survey

A Review on Big Data Stream Processing Applications: Contributions, Benefits, and Limitations

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