Classification of Fiber Optic Cable Attenuation Quality Based on Termination Using K-Means Algorithm
Klasifikasi Kualitas Redaman Kabel Fiber Optik Berdasarkan Terminasi Menggunakan Algoritma K-Means
DOI:
https://doi.org/10.21070/ups.8086Keywords:
K-Means, Classification, Data Mining, Attenuation Quality, Fiber OpticsAbstract
This study classifies the attenuation quality of fiber optic networks using the K-Means algorithm based on 400 field measurement data. The model is built to cluster data based on network parameters, using two approaches: all features and selected features. Evaluation is conducted using Sum of Squared Errors (SSE) and Silhouette Coefficient. Results show that feature selection improves clustering quality, with an SSE of 1935.5 and a Silhouette Coefficient of 0.3529, compared to an SSE of 3130.93 and a Silhouette Coefficient of 0.2616 when using all features. The data distribution is also more balanced (cluster 0: 197 data points, cluster 1: 203 data points). The model effectively distinguishes between high and low attenuation conditions, demonstrating that proper feature selection enhances clustering performance. Overall, K-Means proves effective in classifying attenuation quality and can support more efficient monitoring and maintenance of fiber optic networks.
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