Batik is one of Indonesia's cultural heritages that has high economic value because it is a leading export product. In recent years, the value of batik exports has varied considerably each year. This study was conducted to analyze Indonesian batik export data using the X-Means algorithm as a development of previous studies that used forecasting methods. The difference in this study lies in the approach used. While forecasting emphasizes future predictions, the X-Means algorithm is used to see the clustering patterns of existing data. The data used comes from the 2010-2021 batik export dataset obtained from Kaggle and the Indonesian Batik and Handicraft Center. Data processing was carried out using the RapidMiner application with several cluster tests to determine the best results. The results showed that the test with 3 clusters produced a Davies Bouldin Index (DBI) value of 0.029. A low DBI value indicates that the clustering results are very good and there is a clear distance between clusters. From these results, the countries with the highest batik export values were the United States, Germany, and Japan, while the countries with the lowest exports included Slovenia and Portugal. These results prove that the X-Means algorithm can be used to analyze Indonesian batik export patterns effectively.
Copyrights © 2026