Abstract
This paper presents the method of mining the data and which contains the information about the large information about the PR (Panchayat Raj Department)of Orissa.We have focused some of the techniques,approaches and different methodologies of the demand forecasting. Every organizations are operated in different places of the country. Each place of operation may generate a huge amount of data. In an organization, worker prediction is the difficult task of the manager. It is the complex process not only because its nature of feature prediction but also various approaches methodologies always makes user confused. This paper aims to deal with the problem selection process. In this paper we have used some of the approaches from literature are been introduced and analyzed to find its suitable organization and situation. Based on this we have designed with automatic selection function to help users make a prejudgment. This information about each approach will be showed to users with examples to help understanding. This system also provides calculation function to help users work out a predication result. Generally the new developed system has a more comprehensive functions compared with existing ones. It aims to improve the accuracy of demand forecasting by implementing the forecasting algorithm. While it is still a decision support system with no ability of make the final judgment.This type of huge amount of data are are available in the form of different ways which has drastically changed in the areas of science and engineering.To analyze, manage and make a decision of such type of huge amount of data we need techniques called the data mining which will transforming in many fields. We have implemented the algorithms in JAVA technology. This paper provides the prediction algorithm Linear Regression, result which will helpful in the further research.
Cite
CITATION STYLE
Padhy, N. (2012). Data Mining: A prediction Technique for the workers in the PR Department of Orissa (Block and Panchayat). International Journal of Computer Science, Engineering and Information Technology, 2(5), 197–36. https://doi.org/10.5121/ijcseit.2012.2503
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