Data Mining Pada Jumlah Penumpang Menggunakan Metode Clustering - Koko Handoko; Lido Sabda Lesmana (LPPM Universitas Putera Batam, 2018)
Currently, the concept of Data Mining is increasingly recognized as an important tool in information management because of the increasing amount of information. This study aims to classify the number of passengers at the airport Hang Nadim Batam. A very large sum of these huge amounts of data wants data for the new knowledge of the data. Data drilling is a process that uses statistical, mathematical, artificial intelligence, and machine learning techniques to extract and identify relevant information and large databases. One technique known in data mining is grouping, which is the process of grouping a number of data or objects into a cluster (group). Each of these clusters will contain data that is as similar as possible and different from the objects in the other clusters. In this case we can select the price data as the initial cluster center, then calculate the distance between each data in the cluster center and determine the nearest cluster, then average averages of all groups, so that the existing process is not the same. After the process is done quickly by using RapidMiner, create clusters in grouping the number of passengers. Where the variable used is the first variable, namely: the number of passengers coming, the number of passengers departing, the number of transits that transit. Where will present data on the number of passengers a lot, medium and small.