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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Muthia Maharani
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Pengelompokkan Kondisi Komputer pada Bank X di Seluruh Indonesia Menggunakan Metode K-Medoids Clustering Muthia Maharani; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 5 (2021): Mei 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Bank X is one of the largest public banks in Indonesia. With the banking process running up to the operational process of Bank X which run every day for 24 hours, a very good quality computer is needed. So the process of upgrading computer must always be done. The large number of computers at Bank X makes the process of upgrading computers is one of Bank X's biggest expenses. Other than that, in several work units at Bank X, the process of upgrading computer is still not effective. From these problems, the research will be conducted in the form of grouping computer conditions at Bank X all over Indonesia using the K-Medoids Clustering method. This research was conducted to classify which computers are really need, need enough, and which computers do not need to upgrade. The results of this grouping are that there are 237 computer in cluster 0 no need to upgrade, 126 computer are in cluster 1 with a very need to upgrade, and 769 computer are in cluster 2 with condition good enough but need to be reviewed because it is quite necessary to do a computer upgrade. For testing using the Silhouette Coefficient, clustering with 2 clusters is the best because it has the highest silhouette score, which is 0.624684967. And also the test for amount of data which showed that 90% of the original data was the minimum presentation for data amount for accurate results. The results of the research will be given to Bank X as a recommendation to find out which computers need to be upgraded so that they can be followed up more quickly.
Co-Authors Bayu Rahayudi Dian Eka Ratnawati