Fuzzy Clustering Method in Gold Price

Clustering in statistics and fuzzy properties has many methods. One of the clustering types that is commonly used is unsupervised learning. This paper uses fuzzy clustering with the type of clustering is unsupervised learning. There are fuzzy subtractive clustering, fuzzy k-means clustering, and fuzzy c-means clustering. This paper aims to find the best method for clustering the price of gold. Based on existing data that used the initial principal component analysis, this paper uses multivariate data on gold prices from October 2020 to March 2021. The initial analysis can reduce the dimension of data. This paper shows that fuzzy k-means clustering is the best method for this case, with the optimal clustering result indicated by the smaller Davies-Bouldin index value of 0.99075.