Clustering Of Polri Bintara Placement In North Sumatera Regional Police Using K-Means Algorithm: Clustering Of Polri Bintara Placement In North Sumatera Regional Police Using K-Means Algorithm - Ririn Pebrina Br. Marpaung; Hengki Tamando Sihotang (Institute of Computer Science (IOCS), 2019)
Data mining on process carried out to obtain information from a database or data that can be used to help solve the latest problems or solutions, data mining that is used in this paper is the process of merging by using K-Means solutions. K-Means is one of the techniques used to group non-hierarchical (bulk) data which is supported to provide existing data partition in the form of two or more groups. This method partitioned the data in groups so that the different characteristic data was grouped into other groups. The purpose of grouping this data is to support the objective functions arranged in the grouping process, which generally support variations between groups and take advantage of variations between groups. The agreed clustering was the grouping of non-commissioned police officers in the North Sumatra regional police, with the data collection used was the placement data within the North Sumater Regional Police HR. The procedure that is carried out in this research is the problem process to the design and testing of the program. The knowledge gained from the grouping of the Bintara Police of the National Police in the North Sumatra Regional Police HR is the 5th data Placement based on data collected related to the position of the Brig Ro Sarpras of the North Sumatra Regional Police, as well as related to the data analysis with the K-Intended Algorithm in the North Sumatra Police Brigade. Based on the analysis of the latest number of changes based on the calculation of the K-mean algorithm ie the value 79-100 Being the range for the First cluster, the range 70-78 becomes the second cluster and 60-69 is categorized as the Third cluster. To produce a new pattern, a data mining process is carried out with different data..