Rancang Bangun Aplikasi K-Means untuk Klasifikasi Kelulusan Siswa Sekolah Kepolisian Negara Daerah Kalimantan Selatan - Kartini, Dwi; ., Muliadi (ProTekInfo(Pengembangan Riset dan Observasi Teknik Informatika), 2016)
Student data and recapitulation data passing grade school students Regional State Police South Kalimantan each year increases, resulting in data that is very abundant in the form of the profile data of graduates and academic value data. The rapid growth of data accumulation has created conditions data-rich but minimal information. Data mining is a mining or the discovery of new information by looking for certain rules of a number of large amounts of data are expected to tackle the condition. By utilizing the students master data and data recapitulation of the value of the State Police School students Regional South Kalimantan in 2014, is expected to yield information on the classification of students passing through data mining techniques. The algorithm used within the classification graduation is K-Mean algorithm. The clustering of the results of the analysis carried out in the form of graduate classification based on the group. Group 1 with a recapitulation of the value of graduates being, group 2 with a recapitulation of the value of high graduates and group 3 with a recapitulation of the value of graduates is low. Group 1 with a value of clusters in the data center intellect 72.93 value, the value of personality 71.52, and 62.63 value physical health as much as 45%. Group 2 with a value of clusters in the data center intellect 73.33 value, the value of personality 73.79, and 70.80 value physical health as much as 35%. Group 3 with the center of the cluster in the data value 72.92 intellect, personality value of 69.95 and 53.64 value physical health as much as 20%.