MODEL PENDUGA INDEKS PRESTASI KUMULATIF MAHASISWA TEKNIK INFORMATIKA BERDASARKAN PENDEKATAN STATISTIK: STUDI KASUS DATA MINING PADA SISTEM INFORMASI UNIVERSITAS INDRAPRASTA PGRI - Achmad Sarwandianto (Faktor Exacta, 2011)
Informatics Engineering Student UNINDRA have diverse backgrounds, both from the initial educational background, ability to use computers, diversity values IPS, GPA, years of study and working parents. With the statistical approach and data mining UNINDRA information system is expected to predict the value of student grade point average based on the parameters of the right gender, school background, study groups in college, student status, home school, home province of school, parents work and semester grade point 1 to semester 8. The research method used in this study is a survey method, with sample student UNINDRA informatics engineering graduates. While the data used are primary data obtained from a database or data mining, information systems UNINDRA. After the data is made, then the data were analyzed with statistical approach with the aid of application SPSS 17.0. and Microsoft Office Excel. The results showed than 14 variables or data source, only 3 data supporting the prediction of cumulative GPA informatics engineering students, namely the 2nd semester GPA, semester GPA semester grade 4 and 5. Keywords: Grade Point Average, GPA Semester and Technical Information