Klasifikasi Profesi Berdasarkan Hobi Dengan Metode Minimum Spanning Tree

Leonardo Josua, Dyah Erny Herwindiati, Tri Sutrisno


Application to classify the hobbies of final year students in determining their profession with the Minimum Spanning Tree is a method for classification. Tests carried out are to collect weighted data on hobbies obtained from users and later will be grouped based on the specified assessment table. There are 2 programming languages used to create this application, namely PHP and Python. PHP for user interface and python for calculations. Based on the tests carried out, it can be seen that the results of clustering testing of 21 sample data values for hobbies given by users who will be in the 7th cluster of intellectual intelligence can be concluded that the results of the cluster distance value are determined by referring to the 14 iterations carried out. After calculating the distance from each centroid, the cluster determination is carried out using the Minimum Spanning Tree which is represented by a graph, where the data points or vertices are taken from the minimum cluster distance in each iteration. Determination of clusters with the Minimum Spanning Tree is represented by a graph.


Hobbies, Classification, Profession, Minimum Spanning Tree, PHP, Python.

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