Application of Length of Study and Degree of Excellence Prediction For Informatics Department Students of UMS Using Naive Bayes Method

Nurrohmat, Muh Amin (2015) Application of Length of Study and Degree of Excellence Prediction For Informatics Department Students of UMS Using Naive Bayes Method. Skripsi thesis, Universitas Muhammadiyah Surakarta.

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Abstract

Informatics department of Muhammadiyah University of Surakarta has large data. The data are active students and graduate students. Every year, the data becomes larger. On the other hand, the department cannot manage the data well, thus it means that if the data is larger, then the information is smaller. The solution to solve the problem is that the data must be converted into information. This research discusses how to maximize the data into information using data mining technique. This research uses Naïve Bayes method. It is used to analyze the data, especially in the process of pattern recognition, predicting length of study, and predicting the degree of excellence. After processing the data, the application will display the report, the summary report, and suggestion. Based on the results, the application helps Informatics department to find a solution and take a decision to determine the policy. It is in order to decide where Informatics department will promote its department. Moreover, if Informatics department can recruit good student, it can improve the quality of Informatics department.

Item Type: Karya ilmiah (Skripsi)
Uncontrolled Keywords: Data Mining, Degree of Excellence, Length of Study, Naïve Bayes Method
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Ilmu Komunikasi dan Informatika > Teknik Informatika
Depositing User: Muh Amin Nurrohmat
Date Deposited: 14 Jul 2015 05:29
Last Modified: 14 Jul 2015 06:12
URI: http://eprints.ums.ac.id/id/eprint/34715

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