Student’s Performance Measuring using Assistant Algorithm
N. Venkatesan1, N. Chandru2
1Dr. N. Venkatesan, Professor Bharathiyar college of Engineering and Technology India.
2N. Chandru,  Sri Venkateswaraa College Of Technology India.

Manuscript received on October 24, 2013. | Revised Manuscript received on November 01, 2013. | Manuscript published on November 05, 2013. | PP: 216-222 | Volume-3 Issue-5, November 2013 . | Retrieval Number: E1941113513 /2013©BEIESP
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Abstract: The main theme of school education management is always willing to impart quality education to its students. In this paper we focused higher level to apply Data Mining techniques for implementing and give a quality in technical education. Many ways to achieve to the highest level of quality in technical education as well as increase the student’s academic performance and predict that performed and underperformed of the student’s for providing training and placement. In our work the data set can be prepared from student’s academic’s (technical training or higher education) like a student’s roll no., student’s name, student’s date of birth, student’s10th, student’s 12th, academic percentage upto 7th semester student’s database have to take. In this paper we propose to create a data set for five departments , we have taken (CSE, IT, ECE, EEE, MECH) each department 10 students were taken in preparing the data set , after preprocessing the data set final data can be obtained for training and placement from performing and underperformed student’s from each department . In Educational Data Mining knowledge is hidden we can retrieve the knowledge through data mining techniques. By this process we extract knowledge that measure student’s performance at the end of the semester examination. It helps earlier in identifying performed and underperformed student’s who needs a special attention in academic wise and based on that we give training and placement for the student’s. Classification method , decision tree , ASSISTANT algorithm were used In future this study will be assisted to develop new concepts of data mining techniques in technical education.
Keywords: Data Mining, discover knowledge, Technical Education, Knowledge Discovery in Databases.