Analysis of Big Data Survey Results and Research on System Construction of Computer Specialty System

2021 ◽  
pp. 34-42
Author(s):  
Xueyan Wang
Keyword(s):  
Big Data ◽  
System Construction ◽  
Data Survey ◽  
Survey Results

scholarly journals Big Data Survey on Employee Exercise in New HighTech Photovoltaic Enterprises Highlights on StartUp Photovoltaic Companies

2018 ◽  
pp. 174-180
Author(s):  
Zewen WANG
Keyword(s):  
Big Data ◽  
Human Health ◽  
Exercise Prescription ◽  
Requirement Analysis ◽  
Ant Colony Optimization Algorithm ◽  
Data Survey ◽  
Analysis Design ◽  
Scientific Strategy ◽  
Health Model ◽  
Model Algorithm

Numerous studies show that scientific and reasonable physical exercise can promote human health. Reasonable exercise prescriptions based on an individual’s physical condition is important in improving one’s health. On this basis and through the investigation on the big data of emerging hightech photovoltaic enterprises, the development and design of a human health model and science in sports are developed based on ant colony optimization algorithm. Finally, the requirement analysis, design, specific application, and model algorithm testing of the physical fitness exercise prescription model can provide a scientific strategy for human health and scientific movement.

scholarly journals Smart Culture in Smart City Policies: A Case of Yogyakarta City

JASSP ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 87-92
Author(s):  
Muhammad Iqbal
Keyword(s):  
Smart City ◽  
Smart Cities ◽  
Data Survey ◽  
Survey Results ◽  
Smart Education ◽  
Tangible Culture ◽  
Culture Development ◽  
The City ◽  
Smart Tourism ◽  
Yogyakarta City

The concept of developing Smart Cities in Yogyakarta is different from the development of Smart Cities in other cities. The Smart City of Yogyakarta is under the big idea of Smart Culture, divided into two fields, namely Smart Education and Smart Tourism. This big concept was taken because Yogyakarta is very thick with its Culture and is known as an education city and tourism city. The idea of Smart Culture is expected to touch all aspects of the lives of the citizens of Yogyakarta that are inseparable from the six basic principles of developing Smart Cities. This study uses a quantitative approach. Data survey was conducted using a questionnaire to the civil servant in Yogyakarta City. The survey results will be analyzed using SmartPLS 3.0 software. The results of this study are divided into two components, namely Tangible and Intangible Culture. This Smart Culture's primary purpose is to make Tangible and Intangible Culture in Yogyakarta City survive and excel. Smart Culture in the city of Yogyakarta acts as an umbrella that underlies the development and other intelligent programs such as smart education and smart Culture. These two components are revealed to be critical projects that can be included in short and medium-term programs on smart education or smart tourism related to Culture. Other findings show that tangible Culture and intangible Culture have a significant influence on smart Culture development.

Study of Onega lake Petrozavodsk bay sub-bottom sediments using complex geophysical and geological data analysis

2019 ◽  
pp. 98-104
Author(s):  
M. I. Aleshin ◽  
V. G. Gaynanov ◽  
M. Yu. Tokarev ◽  
A. E. Rybalko ◽  
D. A. Subetto
Keyword(s):  
Seismic Data ◽  
Quaternary Sediments ◽  
Geological Interpretation ◽  
Onega Lake ◽  
Engineering Data ◽  
Seismic Acquisition ◽  
Data Survey ◽  
Survey Results ◽  
Marine Engineering ◽  
Marine Seismic

This article examines the results of geological interpretation of marine engineering data acquired in Onega lake. The survey included marine seismic acquisition and geological sampling. Seismo-stratigrafic units were picked according to processed seismic data. Survey results allowed to make a seismo-stratigrafic column of quaternary sediments of Onega lake. The column could be used to analyze the structure of open part of the lake as well.

scholarly journals THE MODELING OF "MUSTAHIQ" DATA USING K-MEANS CLUSTERING ALGORITHM AND BIG DATA ANALYSIS (CASE STUDY: LAZ)

2021 ◽  
Vol 13 (2) ◽  
pp. 213-230
Author(s):  
Nurhayati Buslim ◽  
Rayi Pradono Iswara ◽  
Fajar Agustian
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Clustering Algorithm ◽  
System Modeling ◽  
Big Data Analysis ◽  
Graphical Form ◽  
Data Types ◽  
Online Data ◽  
Combining Data ◽  
Data Survey

There are a lot of Mustahiq data in LAZ (Lembaga Amil Zakat) which is spread in many locations today. Each LAZ has Mustahiq data that is different in type from other LAZ. There are differences in Mustahiq data types so that data that is so large cannot be used together even though the purpose of the data is the same to determine Mustahiq data. And to find out whether the Mustahiq data is still up to date (renewable), of course it will be very difficult due to the types of data types that are not uniform or different, long time span, and the large amount of data. To give zakat to Mustahiq certainly requires speed of information. So, in giving zakat to Mustahiq, LAZ will find it difficult to monitor the progress of the Mustahiq. It is possible that a Mustahiq will change his condition to become a Muzaki. This is the reason for the researcher to take this theme in order to help the existing LAZ to make it easier to cluster Mustahiq data. Furthermore, the data already in the cluster can be used by LAZ managers to develop the organization. This can also be a reference for determining the zakat recipient cluster to those who are entitled later. The research is "Modeling using K-Means Algorithm and Big Data analysis in determine Mustahiq data ". We got data Mustahiq with random sample from online and offline survey. Online data survey with Google form and Offline Data survey we got from BAZNAS (National Amil Zakat Agency) in Indonesia and another zakat agency (LAZ) in Jakarta. We conducted by combining data to analyzed using Big Data and K-Means Algorithm. K-Means algorithm is an algorithm for cluster n objects based on attributes into k partitions according to criteria that will be determined from large and diverse Mustahiq data. This research focuses on modeling that applies K-Means Algorithms and Big Data Analysis. The first we made tools for grouping simulation test data. We do several experimental and simulation scenarios to find a model in mapping Mustahiq data to developed best model for processing the data. The results of this study are displayed in tabular and graphical form, namely the proposed Mustahiq data processing model at Zakat Agency (LAZ). The simulation result from a total of 1109 correspondents, 300 correspondents are included in the Mustahiq cluster and 809 correspondents are included in the Non-Mustahiq cluster and have an accuracy rate of 83.40%. That means accuracy of the system modeling able to determine data Mustahiq. Result filtering based on Gender is “Male” accuracy 83.93%, based on Age is ”30-39” accuracy 71,03%, based on Job is “PNS” accuracy 83.39%, based on Education is “S1” accuracy 83.79%. The advantaged of research expected to be able to determine quickly whether the person meets the criteria as a mustahik or Muzaki for LAZ (Amil Zakat Agency). The result of modeling is K-Means clustering algorithm application program can be used if UIN Syarif Hidayatullah Jakarta want to develop LAZ (Amil Zakat Agency) too.

scholarly journals Big Data Analytics With Reference To Wide Variety of Domains

2019 ◽  
Vol 8 (10) ◽  
pp. 1100-1104
Keyword(s):  
Health Care ◽  
Social Networks ◽  
Big Data ◽  
Data Analytics ◽  
High Speed ◽  
Big Data Analytics ◽  
Huge Amount ◽  
Government Sector ◽  
Big Data Technologies ◽  
Survey Results

In the current day scenario, a huge amount of data is been generated from various heterogeneous sources like social networks, business apps, government sector, marketing, health care system, sensors, machine log data which is created at such a high speed and other sources. Big Data is chosen as one among the upcoming area of research by several industries. In this paper, the author presents wide collection of literature that has been reviewed and analyzed. This paper emphasizes on Big Data Technologies, Application & Challenges, a comparative study on architectures, methodologies, tools, and survey results proposed by various researchers are presented

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