PENERAPAN ALGORITMA K-MEDOIDS UNTUK MENGELOMPOKKAN PENDUDUK 15 TAHUN KEATAS MENURUT LAPANGAN PEKERJAAN UTAMA
DOI:
https://doi.org/10.30865/komik.v3i1.1609Abstract
The main occupations in 15 years and above are on average not suitable for their age, which is done by adults but is done by people 15 years and older. Therefore, I do grouping data on population 15 years and above so that we know what their main jobs are. Here I use data mining with the K-Medoids method to classify the population of 15 years according to the main occupation, this research was conducted in Indonesia. The K-Medoids method is a method of collecting data with the classic clustering partitioning technique that groups datasets from n objects into K groups known a priori. A useful tool for determining k is a silhouette. It is stronger to be agreed upon and bigger than K-Means because it must add to the difference in the difference in the square of the euclidean distance. Attractions that can be determined as cluster objects are average differences for all objects in the cluster are minimal. That is the easiest point in the cluster. K-Medoids uses objects in a collection of objects to represent a cluster. The object chosen to represent a cluster is called medoid. Clusters are built by calculating the proximity they have between a medoid and non-medoid objects.
Keywords: Data mining, K-Medoid, Main Job Fields 15 years and aboveReferences
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