Data Mining Menggunakan Algoritma Na�ve Bayes Untuk Klasifikasi Kelulusan Mahasiswa Universitas Dian Nuswantoro. ( Studi Kasus: Fakultas Ilmu Komputer Angkatan 2009 ).

NUGROHO, YUDA SEPTIAN (2014) Data Mining Menggunakan Algoritma Na�ve Bayes Untuk Klasifikasi Kelulusan Mahasiswa Universitas Dian Nuswantoro. ( Studi Kasus: Fakultas Ilmu Komputer Angkatan 2009 ). Skripsi, Fakultas Ilmu Komputer.

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Abstract

Student data and data Dian Nuswantoro University student graduation produce data that is very abundant in the form of student profile data and academic data. This happens repeatedly and cause a build up of the student data that affect information retrieval to the data. This study aims to perform the classification of student data Dian Nuswantoro University of Computer Science faculty class of 2009 tiered Diploma and S1 by using data mining process using classification techniques. The method used is the CRISP-DM with a through understanding of business processes, understanding data, the data preparation, modeling, evaluation and deployment. The algorithm used for graduation classification is Naive Bayes algorithm. Naïve Bayes is a simple probabilistic based prediction technique on the application of Bayes theorem or rule with a strong independence assumption on feature, meaning that a feature is not data relating to the presence or absence of other features in the same data. Implementation using RapidMiner 5.3 is used to help find an accurate value. Attributes used is NIM, Name, Qualification, courses, Province of Origin, Gender, credits, GPA, and Graduation Year. The results of this study are used as one basis for determining policy decisions by the computer sciene faculty.

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