Informatics Publishing Limited

Akazue Maureen ¹, Ojeme Blessing ¹

Affiliations
1 Mathematics and Computer Science Department, Delta State University, Abraka, NG

Abstract

Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. A framework to guide a phone business is discussed using data mining tools (decision Tree) to predict future trends and behaviors of their customers, thus, allowing their businesses to make proactive, knowledge-driven decisions. The impact of integrating data mining with acquisition marketing campaign management is also explained.

Keywords

Data Warehouses, Database Marketing, Data Mining, Attrition (Churn), Campaign Management, Customer Segment.

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B. O. Ojeme ¹, Akazue Maureen ²

Affiliations
1 Department of Mathematics and Computer Science, Delta State University, Abraka, Delta State, NG
2 Department of Mathematics and Computer Science, Delta State University, Abraka, Delta State, IN

Abstract

The world is at a crucial point in its development of effective strategies on the prevention, care and control of HIV/AIDS at the national and provincial levels. Given the necessary resources and expertise, it may be possible to keep the epidemic at bay in most parts of the World, and to considerably reduce the negative impacts of the disease on individuals and society. Early detection of HIV has the potential to reduce mortality and morbidity. There are many diagnostic technologies and tests to diagnose HIV. However many of these tests are extremely complex and subjective and depend heavily on the experience of the clinician. This paper made significant contribution to the ongoing worldwide research on the lasting solution to this enemy of man-HIV. It uses a synergistic combination of neural network (NN) and fuzzy inference systems (Neuro-Fuzzy) to generate a model for the detection of the risk level of patients with HIV. The user friendliness and accuracy rate of HIV diagnosis using neuro-fuzzy system makes its output an interesting one. using neuro-fuzzy system is one of the best ways to deal with the vagueness and imprecision of data in the health care sector, and no doubt will exploit tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness, low solution cost and better report with reality in medical diagnosis.

Keywords

Neural Network, Fuzzy Logic, Hiv/Aids, Neuro-Fuzzy and Inference System.

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Akazue Maureen ¹, Ojeme Blessing ¹, Daniel Anidibia ¹

Affiliations
1 Mathematics & Computer Science Department, Delta State University, Abraka, NG

Abstract

Computers are changing our language, our habits, our environment and generally our world. Solving mathematics is more interesting when it is carried out via a computer. So also is statistics which can be broadly classified into descriptive and inferential classes. Statistical inference varies when a sample data that is a subject of the population is well used to make statements about a population. This research is focused on the development of a software program to solve problems on hypothesis testing of population mean and population variance. It showed that solving statistical inference is easier, interactive and interesting when it’s carried out in a computerized system.

Keywords

Statistical Inference, Hardware, Software, Hypothesis Testing, Population Mean, Population Variance.

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