Data Mining Approach to Decision Support in Social Welfare

2014 ◽  
Vol 5 (2) ◽  
pp. 39-61 ◽  
Author(s):  
Ricardo Anderson ◽  
Gunjan Mansingh
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Social Welfare ◽  
Knowledge Discovery ◽  
Support System ◽  
Process Model ◽  
Use Of Data ◽  
Data Mining Approach

Knowledge discovery and data-mining techniques have the potential to provide insights into data that can improve decision making. This paper explores the use of data mining to extract patterns from data in the domain of social welfare. It discusses the application of the Integrated Knowledge Discovery and Data Mining process model (IKDDM) a social welfare programme in Jamaica. Further, it demonstrates how the knowledge acquired from the data is used to develop a knowledge driven decision support system (DSS) in the PATH CCT programme. This system was successfully tested in the domain showing over 94% accuracy in the comparative decisions produced.

Data Mining Approach to Decision Support in Social Welfare

2018 ◽  
pp. 1783-1802
Author(s):  
Ricardo Anderson ◽  
Gunjan Mansingh
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Social Welfare ◽  
Knowledge Discovery ◽  
Support System ◽  
Process Model ◽  
Data Mining Techniques ◽  
Use Of Data ◽  
Data Mining Approach

Knowledge discovery and data-mining techniques have the potential to provide insights into data that can improve decision making. This paper explores the use of data mining to extract patterns from data in the domain of social welfare. It discusses the application of the Integrated Knowledge Discovery and Data Mining process model (IKDDM) a social welfare programme in Jamaica. Further, it demonstrates how the knowledge acquired from the data is used to develop a knowledge driven decision support system (DSS) in the PATH CCT programme. This system was successfully tested in the domain showing over 94% accuracy in the comparative decisions produced.

Knowledge Discovery and Data Mining Applications in the Healthcare Industry

2015 ◽  
pp. 241-262
Author(s):  
Iman Barazandeh ◽  
Mohammad Reza Gholamian
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Decision Support System ◽  
Knowledge Discovery ◽  
Support System ◽  
Healthcare Industry ◽  
Actionable Knowledge ◽  
System View ◽  
Data Market

The healthcare industry is one of the most attractive domains to realize the actionable knowledge discovery objectives. This chapter studies recent researches on knowledge discovery and data mining applications in the healthcare industry and proposes a new classification of these applications. Studies show that knowledge discovery and data mining applications in the healthcare industry can be classified to three major classes, namely patient view, market view, and system view. Patient view includes papers that performed pure data mining on healthcare industry data. Market view includes papers that saw the patients as customers. System view includes papers that developed a decision support system. The goal of this classification is identifying research opportunities and gaps for researchers interested in this context.

The Impact of Using Data Warehouse on Manpower Employment Decision Support System

2011 ◽  
Vol 383-390 ◽  
pp. 4653-4659
Author(s):  
Amro F. Alasta ◽  
Muftah A. Enaba
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Data Warehouse ◽  
Support System ◽  
Employment Decision ◽  
Use Of Data ◽  
Using Data ◽  
The Impact

Since the use of computers in business world, data collection has become one of the most important issues due to the available knowledge in the data; such data has been stored in database. Database system was developed which led to the evolvement of hierarchical and relational database followed by Standard Query Language (SQL). As data size increases, the need for more control and information retrieval increase. These increases lead to the development of data mining systems and data warehouses. This paper focuses on the use of data warehouse as a supporting tool in decision making. We to study the effectiveness of data warehouse techniques in the sense of time and flexibility in our case study (Manpower Employment). The study will conclude with a comparison of traditional relational database and the use of data warehouse. The fundamental role of data warehouse is to provide data for supporting decision-making process. Data in data warehouse environment is multidimensional data store. We can simply say that data warehouse is a process not a product, for assembling and managing data from various sources for the purpose of gaining a single detailed view of part or all an establishment. The data warehouse concept has changed the nature of decision support system, by adding new benefits for improving and expanding the scope, accuracy, and accessibility of data. The warehouse is the link between the application and raw data, which is scattered in separate database but now is unified. The objectives of this work are to study the impact of using data warehouse on Manpower Employment Decision Support System, in the sense as far as the data quality concern. We will focus on the benefits gained from using data warehouse, and why it is more powerful than the use of traditional databases in decision making. The case study will be the Libyan national manpower employment agency. The data warehouse will collect database scattered from different sources in Libya in order to compare the performance and time.

Marketing Decision and Decision Support System Design Based on Web

2013 ◽  
Vol 850-851 ◽  
pp. 1048-1051
Author(s):  
Guang Yu Peng
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Data Warehouse ◽  
Support System ◽  
Logical Structure ◽  
The Internet ◽  
Marketing Decision ◽  
Online Analysis Processing

This paper analyzes the DSS characteristics about the marketing under the internet as well as the influencing factors of the market decisions, Studying the decision-making functions of marketing decision support system DSS. It proposed the marketing DSS design, logical structure and its implementation based on a data warehouse as the center, online analysis processing and data mining as a means.

Knowledge Discovery and Data Mining Applications in the Healthcare Industry

2016 ◽  
pp. 1097-1118 ◽  
Author(s):  
Iman Barazandeh ◽  
Mohammad Reza Gholamian
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Decision Support System ◽  
Knowledge Discovery ◽  
Support System ◽  
Healthcare Industry ◽  
Actionable Knowledge ◽  
System View ◽  
Data Market

The healthcare industry is one of the most attractive domains to realize the actionable knowledge discovery objectives. This chapter studies recent researches on knowledge discovery and data mining applications in the healthcare industry and proposes a new classification of these applications. Studies show that knowledge discovery and data mining applications in the healthcare industry can be classified to three major classes, namely patient view, market view, and system view. Patient view includes papers that performed pure data mining on healthcare industry data. Market view includes papers that saw the patients as customers. System view includes papers that developed a decision support system. The goal of this classification is identifying research opportunities and gaps for researchers interested in this context.

Data Mining in Designing an Agent-Based DSS

Data Mining ◽  
2011 ◽  
pp. 421-436
Author(s):  
Christian Bohm ◽  
Maria R. Galli ◽  
Omar Chiotti
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Software Engineering ◽  
Decision Support System ◽  
Support System ◽  
Knowledge Bases ◽  
Case Based Reasoning ◽  
Agent Based ◽  
Use Of Data ◽  
Using Data

The aim of this work is to present a data-mining application to software engineering. Particularly, we describe the use of data mining in different parts of the design process of an agent-based architecture for a dynamic decision-support system. The work is organized as follows: An introduction section defines the characteristics of a dynamic decision-support system and gives a brief background about the use of data mining and case-based reasoning in software engineering. A second section describes the use of data mining in designing the system knowledge bases. A third section presents the use of data mining in designing the learning process of the dynamic decision-support system. Finally, a fourth section describes the agent-based architecture we propose for the dynamic decision support system. It implements the mechanisms designed by using data mining to satisfy the system functionality.

Knowledge Discovery and Data Mining Applications in the Healthcare Industry

2018 ◽  
pp. 2161-2182
Author(s):  
Iman Barazandeh ◽  
Mohammad Reza Gholamian
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Decision Support System ◽  
Knowledge Discovery ◽  
Support System ◽  
Healthcare Industry ◽  
Actionable Knowledge ◽  
System View ◽  
Data Market

The healthcare industry is one of the most attractive domains to realize the actionable knowledge discovery objectives. This chapter studies recent researches on knowledge discovery and data mining applications in the healthcare industry and proposes a new classification of these applications. Studies show that knowledge discovery and data mining applications in the healthcare industry can be classified to three major classes, namely patient view, market view, and system view. Patient view includes papers that performed pure data mining on healthcare industry data. Market view includes papers that saw the patients as customers. System view includes papers that developed a decision support system. The goal of this classification is identifying research opportunities and gaps for researchers interested in this context.

scholarly journals Data Mining Based Marketing Decision Support System Using Hybrid Machine Learning Algorithm

2020 ◽  
Vol 2 (3) ◽  
pp. 185-193
Author(s):  
Dr. T. Senthil Kumar
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Learning Algorithm ◽  
Research Work ◽  
Hybrid Approach ◽  
Marketing Strategies ◽  
Data Mining Approach ◽  
Marketing Decision

Data mining is widely used in engineering and science, On the contrary, it is used in finance and marketing applications to resolve the challenges in the respective fields. Data mining based decision support system enhances the organization performance by analysing the ground reality. Turbulent economy is common for every organization due to the competition, cost, tax pressures, etc., Privatization, Globalization and liberalization drags the organization more into a competitive environment. In order to balance the competition and withstand to achieve desired gain proper marketing strategies are need to planned and executed. Marketing decision support system helps to reduce the organization burdens in analysing and strategical planning through its efficient data mining approach. This research work proposed a data mining based decision support system using decision tree and artificial neural network as a hybrid approach to estimate the marketing strategies for an organization.

scholarly journals Sistem Pendukung Keputusan Pemilihan Peserta Jaminan Kesehatan Masyarakat (Jamkesmas) Menerapkan Metode MOORA

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Mesran Mesran ◽  
Swandi Dedi Arnold Pardede ◽  
Arahman Harahap ◽  
Andysah Putera Utama Siahaan
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Processing System ◽  
Knowledge Systems ◽  
Decision Models ◽  
Use Of Data ◽  
Computer Based ◽  
Moora Method

Decision support system as a computer-based system consisting of components, among other components of the language system (language), components of knowledge systems (knowledge) and components of the problem processing system (problem processing) which interact with each other, which helps decision making through the use of data and decision models to solve problems that are semi-structured and unstructured. This study uses the MOORA Method in determining who is entitled to become participants Jamkesmas based on criteria by using a formula that results more accurate and targeted.

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