Penerapan Metode Clustering Pada Kasus Kecelakaan Kerja

Prisa Abela; Relita Buaton; Magdalena Simanjuntak

doi:10.61132/merkurius.v2i5.298

Authors

Prisa Abela STMIK Kaputama
Relita Buaton STMIK Kaputama
Magdalena Simanjuntak STMIK Kaputama

DOI:

https://doi.org/10.61132/merkurius.v2i5.298

Keywords:

Work Accident, BPJS Employment, Clustering, K-Means

Abstract

Work accidents are one of the problems that often occur in companies/agencies where accidents happen to employees/workers and cause serious physical injuries. BPJS Employment is an insurance program that is trusted by agencies/companies by claiming Work Accident Insurance (JKK) which can help in easing the financial burden on families as well as initial efforts to handle cases of work accidents that occur. The main aim of this research is to assist companies in handling work accident cases that occur. The data used in this research includes work accident reports collected from the Bpjs Ketenagakerjaan Stabat office. The method used is the clustering method with the K-means algorithm, which was chosen because of its ability to group fairly large amounts of data with fast and efficient computing time. By using the clustering method that has been used to process work accident case data at Bpjs Ketenagakerjaan in Stabat, we can produce new information from the 672 data that have been tested. From 672 work accident case data at Bpjs Employment in Stabat, 3 clusters were obtained with the results of Cluster 1 having 2 work accident case data, Cluster 2 having 9 work accident case data and Cluster 3 having 9 work accident case data.

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