Penerapan Algoritma K-Means dan K-Medoids dalam Pengelompokan Provinsi di Indonesia Berdasarkan Indikator Perumahan Rumah Tangga Tahun 2020
Keywords:
Best Algorithm Selection, , Household Housing Indicators, k-means, k-medoidsAbstract
Statistics Indonesia explained that the percentage of households in Indonesia that had access to decent, safe and affordable housing during the 2019-2020 period was still below 60 percent. Of course, this is a big job for the government to be able to achieve the target in the RPJMN 2020-2024, which is up to 70 percent in providing decent, safe, and affordable housing for the community by 2024. This study aims to group provinces in Indonesia based on indicators. household housing by applying and choosing the best algorithm among k-means and k-medoids. Based on the selection of the best algorithm, k-means is the best algorithm in classifying provinces in Indonesia compared to k-medoids with three clusters. The results of the grouping of provinces in Indonesia are expected to assist the government in dealing with problems related to household housing indicators so that the government's target of increasing the percentage of households occupying decent, safe, and affordable housing can be achieved.
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