Teknik Machine Learning dengan Metode SVM untuk Deteksi Anomali pada Kendala Jaringan FTTH
DOI:
https://doi.org/10.24843/MITE.205.v24i01.P07Kata Kunci:
Machine Learning, deteksi anomali, jaringan telekomunikasi FTTH, metode SVM, evaluasi kinerjaAbstrak
FTTH adalah teknologi yang penting dalam menyediakan layanan internet berkecepatan tinggi kepada pelanggan. Namun, gangguan atau anomali dalam jaringan FTTH dapat menyebabkan gangguan layanan yang berdampak pada pengalaman pengguna.
Data anomali dari jaringan telekomunikasi FTTH dikumpulkan dan diproses menggunakan teknik preprocessing untuk mempersiapkan data sebelum digunakan dalam pelatihan model SVM. Proses pelatihan dilakukan dengan menggunakan data pelatihan untuk mengklasifikasikan data menjadi normal atau anomali. Setelah pelatihan, dilakukan evaluasi kinerja model SVM menggunakan data pengujian yang belum pernah dilihat sebelumnya.
Hasil analisis menunjukkan kemampuan model SVM dalam mendeteksi anomali pada jaringan telekomunikasi FTTH dengan akurasi tinggi dan performa yang baik. Kesimpulan dari penelitian ini adalah bahwa teknik machine learning dengan metode SVM memiliki potensi besar dalam deteksi anomali pada jaringan telekomunikasi FTTH.
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Referensi
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