PENERAPAN METODE ALGORITMA K-MEANS DALAM PEMETAAN PESERTA DIKLAT KETERAMPILAN PELAUT DI SMKN 1 MUNDU

Abstract

Abstract Smkn 1 Mundu Cirebon Sailor Skills Training is the only training organizer who is in vocational high school that can conduct BST (Basic Safety Training) training for sailors of IMO (International Maritime Organization) standards. This research aims to identify the origin of the participants of the training, to apply when the time of the training is held, to find out the needs of the certificate of the participants of the training. This research sample was obtained from the data sheet of Smkn 1 Mundu Cirebon Sailor Skills Training where everyone who will work at sea must have a BST (Basic Safety Training) certificate. The research method done by machine learning using the K-Means Algorithm is the simplest and most common clustering method. This is because K-Means has the ability to group large amounts of data with relatively fast and efficient computing times. With the research can be useful for the Institute of Seafaring Skills Training SMKN 1 Mundu Cirebon So that it can be to identify the Origin of The Training Participants from the cirebon, Indramayu, Majalengka, Kuningan, Brebes, Tegal Pemalang, Purwokerto which dominates the participants of the training, as well as the implementation of the most widely carried out training in the period of August, September and December after students are declared first of school and most certificates are taken to work abroad especially on fishing vessels, commercial vessels and cruise ships as well as at offshore drilling refineries. The result of the application of this k-means clustering algorithm results in k = 3 with DBi = 0.547 model clusters produced cluster 0 = 465 items, cluster 1 = 608 items and cluster 2 = 462 items Keywords of at least 3-5 keywords: Sailor Skills Training, BST (Basic Safety Training), K-Means Algorithm