Implementasi Algoritma Fuzzy C-Means dalam Mengelompokkan Produktivitas Nauplius Vanammei di BBPBAP Jepara

Abstract

Balai Besar Perikanan Budidaya Air Payau often experiences changes in the number of vanammei shrimp production that is uncertain every day. This resulted in the scarcity of vanammei shrimp larvae seeds, unmet market demand and high selling prices. So that the BBPBAP experienced problems in monitoring the quality of the production of vanammei shrimp larvae. To overcome these problems, data mining is used as an alternative solution. The research method used is the Fuzzy C-Means algorithm. With the research stages starting from data collection, pre-processing data to clean data or attributes that are not suitable, clustering using the Fuzzy C-Means algorithm, testing using the MATLAB tool, and evaluating validation using the Davies Bouldin Index (DBI). Based on the results of the clustering that has been carried out from a total of 894 data, which are included in the good cluster, 569 data with the unfavorable category is 325. The results of the evaluation and validation obtained a value of 0.32 with the resulting cluster quality is optimum.