ORGANIZATION CLUSTERING AIRPORT USING K-MEANS CLUSTERING ALGORITHM
Dyah Lintang Trenggonowati1, Maria Ulfah2, Ratna Ekawati3, Vira Aleyda Yusuf4

Department of Industrial Engineering, Faculty of Engineering, University of Sultan Ageng Tirtayasa, Banten

Abstract

One of the right management of the number of resources is through the establishment of an efficient organizational structure in accordance with the conditions of the airport. PT. Angkasa Pura II (Persero) is one of the State-Owned Enterprises engaged in the business of airport services in the western region which currently has 16 airports. With the growing needs of air transportation, PT. Angkasa Pura II is projected by the Ministry of Transportation to become the manager of 21 airports. With an additional projection of 5 airports, PT. Angkasa Pura II (Persero) requires projections for the 21st clustering of airports to be managed in order to form the right organizational structure. Therefore, 5 cluster clusters are formed using the k-means algorithm. This k-means algorithm is used because it is one of the partitional clustering methods. Partitional clustering method was chosen because it was known that the company wanted to form 5 clusters. In this study, clustering was carried out based on variable aircraft movements, passenger movement, cargo, area, terminal area, runway, EBITDA and revenue. The result is obtained in cluster 1 there is 1 airport, cluster 2 there are 6 airports, cluster 3 there are 5 airports, cluster 4 there are 2 airports and cluster 5 there are 5 airports.

Keywords: Airport, Clustering, K-Means Algorithm

Topic: Industrial Engineering

Link: https://ifory.id/abstract-plain/EYwbfq26Z7RK

Web Format | Corresponding Author (Dyah Lintang Trenggonowati)