Analisis Klasterisasi Kualitas Udara Menggunakan Algoritma Fuzzy C-Means Berdasarkan Parameter NO2 dan SO2 di Provinsi Aceh - Muhammad Alfathan Harriz; Harlis Setiyowati; Edi Junaedi (Lembaga Pengembangan Kinerja Dosen, 2025)
The degradation of air quality in Indonesia, particularly in Aceh Province, requires advanced analytical approaches to capture the complexities of air pollution patterns. This study aims to apply the Fuzzy C-Means (FCM) algorithm to cluster regions based on NO2 and SO2 concentrations and to determine the optimal cluster configuration. Air quality index data from 2023–2024, totaling 365 entries, were analyzed using FCM with a fuzzifier parameter of m = 2.0. Performance evaluation was conducted using the Fuzzy Partition Coefficient, Silhouette Score, and Davies-Bouldin Index. The analysis produced two optimal clusters with an FPC of 1.00. Cluster 1 (228 entries) showed an average NO2 concentration of 4.68 μg/m³ and SO2 of 7.10 μg/m³. Cluster 2 (137 entries) exhibited NO2 at 8.74 μg/m³ and SO2 at 6.18 μg/m³. Cross-validation demonstrated consistency in distribution between the training data [0.63; 0.37] and testing data [0.6; 0.4]. FCM proved effective in identifying spatial patterns of air quality with high accuracy, providing a scientific basis for the development of targeted air pollution control policies in Aceh Province.