Penggerombolan Data Panel Emiten Sektor Pertambangan Selama Pandemi Covid-19
DOI:
https://doi.org/10.29244/xplore.v12i1.948Keywords:
clustering on longitudinal data, k-means, mining, stock, technical factorAbstract
The Covid-19 pandemic has made people start looking for new income, one of which
is stock investment. Mining Stock recorded the highest sectoral index increase in 2020.
The high increase in the mining sector index doesn’t indicate all of the stocks have a
good performance. Clustering data of mining stock can help to see which stock has the
best performance. Variables used in clustering are technical factors with details: return,
trading volume, transaction frequency, bid volume, and foreign buy. Data in this research
is longitudinal data from March 2020 until January 2022 and the clustering technique
used is k-means. Clustering on outliers data and non-outliers data is done separately.
Definition of outliers is exploratively with biplot analysis. Clustering on outliers data
results obtained are five clusters and clustering on non-outliers data results obtained are
two clusters. Best cluster is cluster who obtained ANTM because has highest value in
return, transaction frequency, and foreign buy.
