Salt Commodity Data Clustering Using Fuzzy C-Means

Abstract

Indonesia has a sea area of about 96,079.15 km2 rich in natural resources. The advantage is in the form of abundant natural resources in the sea including fish and salt. Several regions such as Cirebon, Indramayu, Rembang, and Madura contribute to the salt pond commodity which is extremely valuable for Indonesia. These resources need to be monitored and inventoried appropriately. Local people are difficult and increasingly cornered to compete in the salt trade. For the strategic commodity group, by maintaining the stability of the salt commodity in the community with its irreplaceable function, the salt trade system is regulated. The purpose of this research is to use the Fuzzy C-Means Clustering method for grouping national salt commodities. This study used a test with 10 clusters for the distribution of training and testing data purposes. The research trials were carried out using the mean imputation method and grouping using the Fuzzy C-Means Clustering method. The test results of the Fuzzy C-Means Clustering method using the Silhouette Coefficient method show that the Fuzzy C-Means Clustering method with the calculation of the closest distance using Manhattan Distance is the best choice in research with the results obtained in the Silhouette Coefficient assessment is at a value of 0.274880 with a value of k = 2.