English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Grouping of Large data has been carried out in various fields. One method for grouping is cluster analysis where this method consists of hierarchy and non-hierarchy method. The aim of this study was to compare the use of cluster analysis on aspects of the causes of poverty data. The method used is agglomerative hierarchical clustering, that is, the average linkage, centroid methods and ward methods. The results obtained are compared with the RMSSTD value and the smallest value is the ward method with a value of 2.0937. So the ward method is good for this case.

Comparison of hierarchical clustering methods (case study: data on poverty influence in North Sulawesi)