CLUSTER ANALYSIS OF FOOD CROPS IN INDONESIA PROVINCE USING SELF ORGANIZING MAP (SOM) METHOD

Aji Bani Ismaun, Suci Nurul Insani, Muhammad Muhajir

Abstract


Indonesia is an agrarian country which most of the population is livelihood in the agricultural sector. There are many food crops that can be produced in every province in Indonesia, but there is problem, such imported food from oversea. Based on data from the Ministry of Agriculture website, it was show that the highest rate import is food crops. Several provinces in Indonesia have ability to develop production for minimizing the existance of imports. The characteristics of food crops in every province are various. It is
necessary to cluster the characteristics of food crops and mapping the potential of food crops in every province, to achieve these purposes used SOM analysis method (Self Organizing Map). SOM is a method for clustering data based on the ch aracteristics / data features (Shieh & Liao, 2012). Based on analysis obtained the result that there are 3 cluster groups based on WCSS approach. The results of clustering are: Cluster 1 has the dominant characteristic in the subsector of rice and corn crops; Cluster 2 has the dominant
characteristics in the cassava plant subsector; Cluster 3 has the dominant characteristic in the rice plant subsector


Keywords


SOM; Clustering; Food Crops;

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