Building a Data Warehouse to Support Active Student Management: Analysis and Design

Sutedja, Indrajani; Yudha, Pandi; Khotimah, Nurul; Vasthi, Claresta

doi:10.1109/icimtech.2018.8528196

Cited by 9 publications

(6 citation statements)

References 17 publications

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“…ey explain the principles of data warehouses, as well as the reason for open data. Sutedja et al [12] examined and construct a data warehouse for integrating multiple operational databases required to offer data on XYZ University's active students. According to Garg [13], digital approaches were used to connect physical objects and depict their current status.…”

Section: Literature Workmentioning

confidence: 99%

Application of Data Warehouse Technology Based on Neural Network in Physical Education Quality Management

Zhao

Liu

2022

Mathematical Problems in Engineering

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Data warehouse technology has been created because of China’s technological advancement and the increasing requirements of the educational sector. Physical assessments are treated as tests by many students. Institutions spend plenty of time every year through physical tests, yet the results are rarely shared with students. Teachers are impeded by the size and complexity of physical test data, finding it challenging to support experiments or judge individual students’ development. Students have trouble following up and delivering test-based feedback after instruction. In recent years, various researchers have offered insightful advice on how to build multidimensional database structures for such trouble. However, quality requirements alone are not adequate to guarantee quality in reality. So, this paper presents a novel Hypertuned wide polynet convolutional neural network (HWPCNN) framework in the data warehouse technology to attain the greatest performance in physical education quality management. In this paper, we first apply HWPCNNs for physical education quality management to analyze the accuracy and recall of the model. It is no secret that HWPCNN is now one of the most widely used deep learning techniques. When it comes to managing the quality of physical education, the HWPCNN’s local perception feature in the data warehouse technology allows it to achieve the best possible results. To validate the model’s performance, it is compared to other models and then improved further to increase its accuracy. The physical education resources are gathered as a raw dataset for this inquiry. The raw dataset is cleaned using the Z-score approach to get it ready for further data processing. Then, a sparse matrix approach is employed to build a data cube, while the proposed method is used to index multidimensional databases. To demonstrate that our work is of the best quality in managing physical education, performance metrics of the suggested method are also evaluated and compared with other traditional methods.

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Section: Literature Workmentioning

confidence: 99%

Application of Data Warehouse Technology Based on Neural Network in Physical Education Quality Management

Zhao

Liu

2022

Mathematical Problems in Engineering

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“…Notably, analyzing data in separate applications consumes much time. At this stage, to perform some manufacturing routines, transaction processing systems are used, and these are updated in a timely manner [15]- [17]. In this section, the most important issues related to ETL are addressed in terms of construction, design and stages.…”

Section: Dw's Applicationsmentioning

confidence: 99%

Design and implementation of the web (extract, transform, load) process in data warehouse application

Al-Rahman

Hasan²,

Sagheer³

2023

IJ-AI

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<p>Recently, due to an increase size and complexity of data in addition to the management issues, data storage is required a great deal of attention to employ it in realistic applications, so the requirement for designing and implementing a data warehouse system has become an urgent necessity, ETL represents a vital side of data warehouse architecture. This paper, designed data warehouse application contains a web ETL process that divides its work between the input device and server. This system proposed to solve the problem lack of partition of the work between the input device and server. The proposed and designed system can be used and applied in many branches and disciplines for its high performance in adding data, analyzing data using a web server and building queries. The analysis of the results has been proven that a faster time is achieved in cleaning data and transferring it between the remote parts of the system connected to the Internet. Where ETL without Missing for any data took 0.00582 seconds.</p>

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“…In the study [6] entitled "Business and Data Understanding in the context of establishing an Emerging Partner Implementation on Covid-19 data in DKI Jakarta", it was explained that the stage of data understanding begins with collecting initial data and the results of activities to familiarize themselves with the data to identify data problems. To determine first insights into the data or detect subsets of interest to form hypotheses for hidden information.…”

Section: Data Understandingmentioning

confidence: 99%

Analysis of Covid 19 Data in Indonesia Using Supervised Emerging Patterns

Rahardja

Dewanto²,

Djajadi³

et al. 2022

ATM

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This research method uses CRISP-DM with emerging pattern supervision modeling and EPM Algorithm. The contribution of the research is to assist the Government in overcoming the problem of the spread of the COVID-19 cluster in several regions in Indonesia. The research aims to implement information on the COVID-19 data mining pattern in the DKI Jakarta area. The problems faced are the difficulty of identifying the pattern of COVID-19 data in one area, it is difficult to dig up data on the http://corona.jakarta.go.id website. It is not easy to decide on the handling of COVID-19. The output of the research results in a cluster of information on COVID-19 in the DKI Jakarta area based on Significance level depends on the Covid Map In terms of Region, Status, Gender, & age And Signification can be the basis for determining covid OTG, DTG, and Positive. The theoretical and practical implications can be stated as follows: The use of supervised emerging pattern methods can affect the processing of COVID-19 data. For 5 Regions in DKI Jakarta and distribution to determine covid OTG, DTG, and Positive. The result of the development of this data mining system is to produce pattern reports to produce Supervised Emerging Patterns technology for decision making at the COVID-19 Task Force in DKI Jakarta.

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Building a Data Warehouse to Support Active Student Management: Analysis and Design

Cited by 9 publications

References 17 publications

Application of Data Warehouse Technology Based on Neural Network in Physical Education Quality Management

Application of Data Warehouse Technology Based on Neural Network in Physical Education Quality Management

Design and implementation of the web (extract, transform, load) process in data warehouse application

Analysis of Covid 19 Data in Indonesia Using Supervised Emerging Patterns

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