Penggunaan Algoritma Fuzzy C-Means untuk Optimalisasi Pengelompokan Data Cuaca dalam Prediksi Curah Hujan di Indonesia - Safrina Hidayah; Rizki Muliono (INCODING: Journal of Informatics and Computer Science Engineering, 2025)
This study develops an information system to optimize rainfall data clustering in Indonesia using the Fuzzy C-Means method. Rainfall clustering aims to provide accurate information about climatic conditions by categorizing regions into three rainfall levels: high, medium, and low. The data used in this study were obtained from observations by the Meteorology, Climatology, and Geophysics Agency (BMKG) from 2011 to 2015 across various provinces. The Fuzzy C-Means method was selected due to its ability to handle uncertainty by assigning membership degrees to each cluster. The resulting clustering information is expected to assist the community and relevant sectors such as agriculture, fisheries, and regional planning in predicting rainfall and making informed decisions. The developed system can also be extended to process other weather data, including air quality and wind speed.