www.ijemr.net ISSN (ONLINE): 2250-0758, ISSN (PRINT): 2394-6962 362 Copyright © 2011-15. Vandana Publications. All Rights Reserved. Volume-5, Issue-6, December-2015 International Journal of Engineering and Management Research Page Number: 362-365 An Approach for Classifying River Water Quality using Data Mining Technique Sanjeev Gour 1 , Dr.Anil Rajput 2 , Purushottam Sharma 3 1 Department of Computer Science, LBS College, Harda, INDIA 2 Department of Mathematics and Computer Science, Govt. P.G. College, Sehore, INDIA 3 Research Scholar, B.V.V, Bhopal, INDIA ABSTRACT Water is vital for life, as a water supply for people, for the diverse ecosystems on which we depend, for agriculture, industry and recreation. The amount of available fresh clean water of river Narmada is changing because of growing populations, changes in farming and the new needs of industry. Water quality determines the ‘goodness’ of water for particular purposes. In this paper, different water quality parameters are selected namely, Dissolved oxygen (DO), Nitrate (NO3), Biochemical oxygen demand (BOD),Hardness ,pH, TDS and Temperature etc. These parameters are calculated for the Narmada River and Analyzed through Classification and Prediction techniques of Data mining via Software Tool ESTARD Ver. 3.1.325. The results conclude that DO, NO3 and BOD conditions vary from good to worst for the River Narmada at Hoshangabad district. The worst conditions are registered for the NO3-N, where the quality status of Water is poor due to industries sewage and also The comparisons of these parameters are combined to provide a water quality ranking (good[A], fair[B], poor[C],very poor[D]) for River Water. Keyword--- Classification, Prediction techniques I. INTRODUCTION Water Quality is a major concern around the world. Water quality is affected by a wide range of natural and human influences. The effects of human activities on water quality are both widespread and varied in the degree to which they disrupt the ecosystem and/or restrict water use. Eutrophication results not only from point sources, such as wastewater discharges with high nutrient loads, but also from diffuse sources such as run-off from agricultural land fertilized with organic and inorganic fertilizers. The quality of water may be described in terms of the concentration and state (dissolved or particulate) of some or all the organic and inorganic material present in the water together with certain physical characteristics of the water. It is determined by examination of water samples on site. The main elements of water quality monitoring are, therefore, on-site measurements, the collection and analysis of water samples, the study and evaluation of the analytical results, and the reporting of the particular location and time at which that sample was taken. Our purpose of this study is, therefore, to gather sufficient data to assess spatial and/or temporal variations in water quality. In this paper various data mining techniques such as classification and prediction are used to analyze various water quality parameters of river Narmada [1]. II. DATA MINING Data mining includes the use of sophisticated data analysis tools to discover previously not known, valid patterns and relationships in large data sets. These tools can involve mathematical algorithms, statistical models and machine learning methods (such as neural networks or decision trees). As a result, data mining consists of more managing and collecting data, it also includes analysis and prediction. One of such Data mining tool ESTARD is used in this study. III. DATA SET In this study water quality data of river Narmada of district Hoshangabad of M.P is used. we have collected these valuable data from the Laboratory Level-II of Central Water Commission (CWC) State Baseline station whose state office is located at Narmada Basin, Block-3, G-Floor, Prayavas Bhavan, Mother Teresa Marg, Arera