Study on Data Mining with Decision Tree Algorithm in the Student Information Management System

2014 ◽  
Vol 543-547 ◽  
pp. 3602-3605
Author(s):  
Liang Li ◽  
Ying Zheng ◽  
Xiao Hua Sun ◽  
Fu Shun Wang

With the advance of education informationization in china, information technology and data mining technology has been widely used in the field of education. The decision tree method is one of the data mining methods; it does not require any assumption, can intelligent classification to a large amount of data directly. According to certain rules to find hidden and valuable information.Use the idea of learners as the center as guiding principle, using decision tree algorithm of data mining technology to build student information management system, selects typical C4.5 algorithm among the decision tree methods, Take mass information about employment of graduation in university students' information management system as an example to generate the decision tree, collect potential rules and factors in favor of graduat employment, so as to guide the education and management.

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
XueHong Yin

Data mining is a new technology developed in recent years. Through data mining, people can discover the valuable and potential knowledge hidden behind the data and provide strong support for scientifically making various business decisions. This paper applies data mining technology to the college student information management system, mines student evaluation information data, uses data mining technology to design student evaluation information modules, and digs out the factors that affect student development and the various relationships between these factors. Predictive assessment of knowledge and personalized teaching decision-making provide the basis. First, the general situation of genetic algorithm and fuzzy genetic algorithm is introduced, and then, an improved genetic fuzzy clustering algorithm is proposed. Compared with traditional clustering algorithm and improved genetic fuzzy clustering algorithm, the effectiveness of the algorithm proposed in this paper is proved. Based on the analysis system development related tools and methods, in response to the needs of the student information management system, a simple student information management system is designed and implemented, which provides a platform and data source for the next application of clustering algorithm for performance analysis. Finally, clustering the students’ scores with a clustering algorithm based on fuzzy genetic algorithm, the experimental results show that this method can better analyze the students’ scores and help relevant teachers and departments make decisions.


Author(s):  
Gbenga Femi Asere ◽  
Dung Emmanuel Botson

Wide spread use of information system in the delivery of managed healthcare system and the challenges of identifying and disseminating relevant healthcare information, complex and diverse data and knowledge forms and tasks coupled with the prevalence of legacy systems require automated approaches for effective and efficient utilization of massive amount of data to support in strategic planning and decision-making and assist the strategic management mechanisms. Despite the fact that data mining is progressively used in information systems as a technology to support analytical decision making, it is however still barely used in hospital information system to support analytical decision making process. Hence, this paper presents the usefulness of data mining technology in Hospital Information Management System (HIMS). Data mining technology offered capabilities to increase the productivity of medical personnel, analyze care outcomes, lower healthcare costs, improve healthcare quality by using fast and better clinical decision making and generally assist the strategic management mechanisms.


2014 ◽  
Vol 687-691 ◽  
pp. 1141-1144
Author(s):  
Mei Bai

This paper introduces the concept of database and data mining, combined with management system of quality assessment system and method of data mining technology. In this paper, applying the data mining skill to the field of remote open management system, introduces the development of data mining in China and the necessity and importance of data mining in remote open information management system. This thesis analyzes the main problems in the remote open management system. On the basis of the relevant researches both at home and abroad, it presents the significance of the application of data mining in remote open management system. It analyzes the needs of the system based on data mining and presents a detailed design and implication of such a system.


2016 ◽  
Vol 2 (3) ◽  
pp. 515
Author(s):  
Luay Idrees Sarhan ◽  
Akeela M. Atroshi ◽  
Nawzat S. Ahmed

The strategic planning of developing any information system is the key factor of progress any organization. Hence, SWOT (Strength, weakness, opportunities and threats) analysis for the strategic planning of developing information system has proved to be a good analysis tool for further development and progress of the universities/organization. Further, the implementation of computerized student information management system has become an important issue within the university campus to exchange such information between students and staff. Many studies have developed student information system through the converting of paper-based system to computer-based system in order to facilitate the work of staff. However, none of these studies focused on the development of such systems based on the strategic planning using SWOT technique. Therefore, this research focuses on the requirements needed to develop student information system based on the aforementioned strategic planning technique. Some universities located in the Kurdistan Region, Iraq have been tacking to do the investigation. Moreover, SWOT technique was selected to find strengths, weaknesses, opportunities and threats of developing such system. The findings of this research were processed as matching strengths with opportunities and converting weaknesses or threats to strengths or opportunities. Based on the results, it has been found that the need to address student information systems is of utmost importance now more than ever in order to survive and continue in the competition environment.            


2014 ◽  
Vol 538 ◽  
pp. 460-464
Author(s):  
Xue Li

Based on inter-correlation and permeability among disciplines, the author makes an attempt to apply the information science to cognitive linguistics to provide a new perspective for the study of foreign languages. The correlation between self-efficacy and such four factors as anxiety, learning strategies, motivation and learners’ past achievement is analyzed by means of data mining and the extent to which the above factors affect self-efficacy in language learning is explored in this paper. The paper employs the decision tree algorithm in SPSS Clementine. C5.0 decision tree algorithm is adopted to analyze data in the study. The results are elicited from the researches carried out in this paper. The increased anxiety is bound to weaken learners’ motivation over time. It is obvious that learners have low self-efficacy. It is very important to employ strategies in foreign language learning. Ignorance of using learning strategies may result in unplanned learning with unsatisfactory achievements in spite of more efforts involved. Self-efficacy in foreign language learning may be weakened accordingly. Learners’ past achievement is a reference dimension in measuring self-efficacy with weaker influence.


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