NDLI: Organization clustering airports using K-Means clustering algorithm

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Organization clustering airports using K-Means clustering algorithm

Content Provider	Scilit
Author	Trenggonowati, D. L. Ulfah, M. Ekawati, R. Yusuf, V. A.
Copyright Year	2019
Description	Journal: Iop Conference Series: Materials Science and Engineering One of the right management quantity of human 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 clustering for all 21 airports to be managed in order to form the right organizational structure. Therefore, 5 clusters are formed using the k-means algorithm. This method 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.
Related Links	https://iopscience.iop.org/article/10.1088/1757-899X/673/1/012081/pdf
ISSN	17578981
e-ISSN	1757899X
DOI	10.1088/1757-899x/673/1/012081
Journal	Iop Conference Series: Materials Science and Engineering
Issue Number	1
Volume Number	673
Language	English
Publisher	IOP Publishing
Publisher Date	2019-12-01
Access Restriction	Open
Subject Keyword	Journal: Iop Conference Series: Materials Science and Engineering Hardware and Architecture
Content Type	Text
Resource Type	Article

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