Data Centre Risk Analysis Using ISO 31000:2009 Framework

Andry, Johanes Fernandes; Liliana, Lydia; Tannady, Hendy; Arief, Abdul Samad

doi:10.1088/1742-6596/2394/1/012032

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…The time period "massive facts" has currently been applied to datasets that develop so huge that they end up awkward to paintings with the use of traditional database control structures. They may be records units whose length is beyond the capability of typically used software gear and garage structures to capture, save, control, in addition to manner the information inside a tolerable elapsed time [18].…”

Section: Big Data Analyticsmentioning

confidence: 99%

The Sustainable Logistics: Big Data Analytics and Internet of Things

Tannady¹,

Andry²,

Suriyanti³

2023

IJSDP

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The presence of IoT technology in Indonesia has made many industries grow rapidly, especially in data management in large companies. The aim of this journal is to discuss one of the 'smart' solutions that can be recognized as an innovative solution in both the technology and organizational fields presented by a telecommunications company in Indonesia. This solution can be implemented in the logistics industry, which in the era of globalization plays a very important role. But not only in the logistics industry, the smart logistic solutions discussed can also be used in several other industries such as retail, warehousing, transportation, manufacturing and mining. The feature of the smart logistic device already uses big data analysis which is known to process and use real time data. All of the features carried by the smart logistics are not only aimed at reducing distribution costs but also optimizing the distribution system of goods. The direct impact felt by user companies is that their productivity has increased dramatically because they can set delivery destinations that have been adjusted according to the zoning system, look for traffic-free paths, and so on. The pace of modern economic development encourages companies to introduce more new solutions, resulting in innovations that drive market progress. This research aim is to discuss about how to resolve the problem that was encountered by logistic companies by of implementing logistics IT solutions which consists of Big Data Analytic and Internet of Thing. So big data IoT like that requires an appropriate analytical framework to generate knowledge to measure operational efficiency, distribution, machine renovation, and so on inside the enterprise. The research method used in this article is library research or literature review, this research begins with the problem identification, hence looking source and information, data collection and information, analysis and processing the gathered information and create a conclusion. One of conclusions of this research is All the features of the Nextfleet application as well as the development of Advanced Driver Assisted System (ADAS) technology and Intelligent Telematics Surveillance enable the Nextfleet application to be applied not only to the logistics industry but also other industries such as retail, warehousing, transportation, manufacturing, and mining.

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Section: Big Data Analyticsmentioning

confidence: 99%

The Sustainable Logistics: Big Data Analytics and Internet of Things

Tannady¹,

Andry²,

Suriyanti³

2023

IJSDP

View full text Add to dashboard Cite

show abstract

“…Surpsingly, the result the models they proposed show a precise number of the case growth per day. From the small example from that have been done by other countries we can learn and propose a model that could fit with the Indonesia condition [25].…”

Section: Introductionmentioning

confidence: 99%

Big Data Analytics in Healthcare: COVID-19 Indonesia Clustering

2023

JPTCP

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The rapid growth of the Internet and Technology produced a massive amount of data that resulted a phenomenon called Big Data. To process such a complex kind of massive amount of data, an advanced approach and tool is needed that is able to quickly produce results. This approach to analyzing massive amount of data is known as Big Data Analytics. Big data analytics is widely used in various sectors, not to mention the health sector. In the healthcare sector, recently there has been a study that is often carried out in dealing with crisis situations, namely research on implementing big data analytics to provide technological solutions to help deal with pandemics. In this article, we analyze and visualize the data collected from Indonesia. The data analyzed starts from the first case of COVID-19 in Indonesia to present. The proposed solution is to classify the regional case data into a group that can represent the situation of the area. As a result, it is determined based on the data that there are three groups consisting of areas with low risk, moderate risk, and high risk. In addition, this article proposes combining big data analytics technology with cloud technology to facilitate the dissemination of information to citizens to increase awareness about the spread of the COVID-19 virus.

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Data Centre Risk Analysis Using ISO 31000:2009 Framework

Cited by 2 publications

References 9 publications

The Sustainable Logistics: Big Data Analytics and Internet of Things

The Sustainable Logistics: Big Data Analytics and Internet of Things

Big Data Analytics in Healthcare: COVID-19 Indonesia Clustering

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