Perbedaan tingkat akurasi metode k-means dan hierarchical clustering di bidang peramalan dan klasifikasi

Abstract: K-Means is a non-hierarchical data clustering method that attempts to partition existing data into one or more clusters/groups. This method partitions data into clusters so that data with the same characteristics are grouped into the same cluster and data with different characteristics are grouped into other groups. Hierarchical methods are clustering techniques to form a hierarchy or based on a certain level so that it resembles a tree structure. Thus, the grouping process is carried out in stages or stages. This research was conducted by reviewing research in national journals with topics that match the different levels of accuracy of the k-means and hierarchical clustering methods in the field of forecasting and classification. The purpose of this study was to determine the significant difference in the level of accuracy in forecasting and classification results between using the K-Means clustering method or using the Hierarchical clustering method. This research method uses a meta-analysis method by reviewing several articles from 2012-2022 related to differences in the level of accuracy of the k-means method and hierarchical clustering in the field of forecasting and classification. Data is collected from indexer databases such as Scopus, DOAJ, WorldCat, and Google Scholar. The data used is the result of research that contains the value of the correlation (r), and the number of data subjects (N). From the search results obtained publication data that meets as many as 60 publications. Based on the results of the analysis using JASP software, it was obtained that the k means method, the summary effect value of the forest plot was 0.67, in other words, the effect of the k means forecasting model on the accuracy rate was 67% with a moderate category, while in the hierarchical method the summary effect value of the forest plot was 0.61. in other words, the influence of the hierarchical method of forecasting models on the level of accuracy is 61% in the medium category