Analisa Clustering untuk Mengelompokan Data Penayangan Film Bioskop Menggunakan Algoritma K-Means

Abstract

The purpose of this study is one of the analyzes to obtain film screening data, the approach used in this study is the K-means algorithm using the parameter measure type Numerical Measure with Numerical Measure Euclidean Distance to get the best Davies Bouldin Index (DBI), with the intention of getting helps grouping datasets of film screenings at the Ramayana Cirebon XXI Cinema. Results from the evaluation of the Davies Bouldin Index (DBI) obtained is (K-2) with a Davies Bouldin Index (DBI) value of 0.864, because the value obtained is the smaller the Davies Bouldin Index (DBI) value, it shows the optimum performance of the resulting cluster.