Knowledge-based model to support decision-making when choosing between two association data mining techniques

China's commercial magazine faces of increasingly fierce competition in the customer, so it must improve its management and marketing method to enhance competitiveness. It is the key point to strengthening customer relationship management. The study in this paper uses data mining techniques to enhance the management of the customer to explore new customers, maintain overall customers and accelerate the development of the magazine. Through the establishment of large database and data mining, we find useful data and the relevance to support decision-making and better improve the competitiveness of the magazine.

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IMPLEMENTASI METODE VIKOR DALAM PENERIMAAN JURNALIS PADA KORAN WASPADA MEDAN

KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) ◽

10.30865/komik.v2i1.905 ◽

2018 ◽

Vol 2 (1) ◽

Author(s):

Soraya Rahma Hayati ◽

Mesran Mesran ◽

Taronisokhi Zebua ◽

Heri Nurdiyanto ◽

Khasanah Khasanah

Keyword(s):

Decision Making ◽

Decision Support ◽

Decision Support System ◽

Decision Support Systems ◽

Support System ◽

Support Systems ◽

Knowledge Based ◽

Computer Based ◽

Support Decision Making ◽

Made In

The reception of journalists at the Waspada Daily Medan always went through several rigorous selections before being determined to be accepted as journalists at the Waspada Medan Daily. There are several criteria that must be possessed by each participant as a condition for becoming a journalist in the Daily Alert Medan. To get the best participants, the Waspada Medan Daily needed a decision support system. Decision Support Systems (SPK) are part of computer-based information systems (including knowledge-based systems (knowledge management)) that are used to support decision making within an organization or company. Decision support systems provide a semitructured decision, where no one knows exactly how the decision should be made. In this study the authors applied the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) as the method to be applied in the decision support system application. The VIKOR method is part of the Multi-Attibut Decision Making (MADM) Concept, which requires normalization in its calculations. The expected results in this study can obtain maximum decisions.Keywords: Journalist Acceptance, Decision Support System, VIKOR

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Failure Analysis in University and Computer Science Contexts With Data Mining

10.5753/wei.2020.11132 ◽

2020 ◽

Author(s):

Daniela De Souza Gomes ◽

Marcos Henrique Fonseca Ribeiro ◽

Giovanni Ventorim Comarela ◽

Gabriel Philippe Pereira

Keyword(s):

Data Mining ◽

Decision Making ◽

Failure Analysis ◽

Computer Science ◽

Educational Administration ◽

Intelligent Systems ◽

Data Set ◽

Data Mining Techniques ◽

Study Case ◽

Support Students

High failure rates are a worrying and relevant problem in Brazilian universities. From a data set of student transcripts, we performed a study case for both general and Computer Science contexts, in which Data Mining Techniques were used to find patterns concerning failures. The knowledge acquired can be used for better educational administration and also build intelligent systems to support students’ decision making.

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ANGEL Mining

Higher Education Institutions and Learning Management Systems ◽

10.4018/978-1-60960-884-2.ch005 ◽

2012 ◽

pp. 94-115 ◽

Cited By ~ 2

Author(s):

Tyler Swanger ◽

Kaitlyn Whitlock ◽

Anthony Scime ◽

Brendan P. Post

Keyword(s):

Data Mining ◽

Decision Making ◽

Feature Selection ◽

Decision Tree ◽

Management System ◽

Association Mining ◽

Data Mining Techniques ◽

Usage Patterns ◽

Design Selection ◽

Comprehensive College

This chapter data mines the usage patterns of the ANGEL Learning Management System (LMS) at a comprehensive college. The data includes counts of all the features ANGEL offers its users for the Fall and Spring semesters of the academic years beginning in 2007 and 2008. Data mining techniques are applied to evaluate which LMS features are used most commonly and most effectively by instructors and students. Classification produces a decision tree which predicts the courses that will use the ANGEL system based on course specific attributes. The dataset undergoes association mining to discover the usage of one feature’s effect on the usage of another set of features. Finally, clustering the data identifies messages and files as the features most commonly used. These results can be used by this institution, as well as similar institutions, for decision making concerning feature selection and overall usefulness of LMS design, selection and implementation.

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Improved Privacy

Intelligent Information Technologies and Applications - Advances in Intelligent Information Technologies ◽

10.4018/978-1-59904-958-8.ch014 ◽

2011 ◽

pp. 295-316

Author(s):

K. Abumani ◽

R. Nedunchezhian

Keyword(s):

Data Mining ◽

Decision Making ◽

Empirical Analysis ◽

Time Complexity ◽

Strategic Decision ◽

Strategic Decision Making ◽

Sensitive Information ◽

Data Mining Techniques ◽

Novel Method ◽

Mining Tools

Data mining techniques have been widely used for extracting non-trivial information from massive amounts of data. They help in strategic decision-making as well as many more applications. However, data mining also has a few demerits apart from its usefulness. Sensitive information contained in the database may be brought out by the data mining tools. Different approaches are being utilized to hide the sensitive information. The proposed work in this article applies a novel method to access the generating transactions with minimum effort from the transactional database. It helps in reducing the time complexity of any hiding algorithm. The theoretical and empirical analysis of the algorithm shows that hiding of data using this proposed work performs association rule hiding quicker than other algorithms.

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Knowledge-based semantic discretisation using data mining techniques

International Journal of Advanced Intelligence Paradigms ◽

10.1504/ijaip.2020.109510 ◽

2020 ◽

Vol 17 (3/4) ◽

pp. 267

Author(s):

Omprakash Chandrakar ◽

Jatinderkumar R. Saini

Keyword(s):

Data Mining ◽

Data Mining Techniques ◽

Knowledge Based ◽

Using Data

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A Hybrid Method for Prediction and Assessment Efficiency of Decision Making Units

International Journal of Decision Support System Technology ◽

10.4018/jdsst.2013010104 ◽

2013 ◽

Vol 5 (1) ◽

pp. 66-83 ◽

Cited By ~ 1

Author(s):

Iman Rahimi ◽

Reza Behmanesh ◽

Rosnah Mohd. Yusuff

Keyword(s):

Data Mining ◽

Decision Making ◽

Decision Rules ◽

Large Data ◽

Poultry Meat ◽

Small Data ◽

Data Set ◽

Data Mining Techniques ◽

Decision Making Units

The objective of this article is an evaluation and assessment efficiency of the poultry meat farm as a case study with the new method. As it is clear poultry farm industry is one of the most important sub- sectors in comparison to other ones. The purpose of this study is the prediction and assessment efficiency of poultry farms as decision making units (DMUs). Although, several methods have been proposed for solving this problem, the authors strongly need a methodology to discriminate performance powerfully. Their methodology is comprised of data envelopment analysis and some data mining techniques same as artificial neural network (ANN), decision tree (DT), and cluster analysis (CA). As a case study, data for the analysis were collected from 22 poultry companies in Iran. Moreover, due to a small data set and because of the fact that the authors must use large data set for applying data mining techniques, they employed k-fold cross validation method to validate the authors’ model. After assessing efficiency for each DMU and clustering them, followed by applied model and after presenting decision rules, results in precise and accurate optimizing technique.

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