ANALISIS GEROMBOL PADA DATA DERET WAKTU PENDERITA COVID-19 PROVINSI JAWA BARAT

Sarah Fadhlia (Universitas Indraprasta PGRI Jakarta)

Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika
Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik

This study aims to apply clustering techniques to time series data. Time series models can be formed for all research data objects, so many research objects need to be grouped so that the resulting model becomes more efficient. The object used in this study was data on Covid-19 sufferers from 27 regencies and cities in West Java Province. All objects were analyzed by time series to produce 27 models. All objects' data patterns and models have many similarities, so clustering can be done. Clustering models using the Ward method and the Piccolo dissimilarity measure. The optimum cluster uses the Hartigan and Ball indices to obtain 3 clusters