PENGGUNAAN SELF ORGANIZING MAP DALAM PENGELOMPOKAN TINGKAT KESEJAHTERAAN MASYARAKAT

IRWAN IRWAN, ASTRI YUNI HASHARI, HISYAM IHSAN, AHMAD ZAKI

Abstract


Self Organizing Map (SOM) is one of the topology forms of Unsupervised Neural Network where in the learning process does not require output target. Clusters in this research consist of one or more regency/city areas that have certain characteristics based on the variables. Each cluster had to be validated by using the Davies Bouldin Index value to get the best cluster formation from the SOM algorithm learning process. The best cluster model is the cluster model that has the smallest Davies Bouldin Index value. This research used 30 variables that refer to the key statistics of South Sulawesi Province People's Prosperity in 2018 by BPS of South Sulawesi Province. In this research, four cluster formation models were formed which began by forming 2 cluster model to form 5 cluster. Based on the Davies Bouldin Index value, it was found that the  5 cluster model have minimum value of 0.17.

Keywords


Self Organizing Map; Unsupervised Artificial Neural Network; Davies Bouldin Index; people’s Prosperity

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References


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DOI: https://doi.org/10.34312/jjps.v1i2.7266

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