MENENTUKAN EFEKTIVITAS PEMBELAJARAN ONLINE MENGGUNAKAN ALGORITMA ANGGLOMERATIVE HIERARCHICAL CLUSTERING

Abstract

The clustering method is a method that can group to produce modeling processes, as well as analyze data with a partition system. In classifying student personalities, we use the Agglomerative Hierarchical Clustering (AHC) Algorithm. AHC is a data grouping technique that divides data into groups based on their similarity. This study aims to classify student personalities in lectures based on E-Learning with the AHC method. In this study, the score calculation was carried out in three processes following the hierarchical cluster process which was carried out in three processes. This process is carried out three times with the aim of observing the development of particle distribution during the hierarchical cluster process. It can be seen that the first score produced a value of 0.54, then the second score produced a value of 0.51, while the last one produced a value of 0.54. Then it takes the last value to determine how well it is spread. It can be seen from the last value that the resulting value is above 0 and close to 1 so that it can be said that the distribution of the particles is fairly good.
Keywords : AHC, Clustering, Optimization, Personality, PSO, Student.