Optimasi Disaster Recovery Planning (DRP) pada Site Recovery Manager (SRM) Menggunakan Algoritma Genetika
DOI:
https://doi.org/10.31358/techne.v24i1.580Keywords:
Algoritma Genetika, DRP, Recovery Time Objective, Optimasi downtimeAbstract
Bencana IT yang tak terduga dapat mengganggu operasional bisnis, terutama jika tidak ada kesiapan yang memadai. Dampaknya mencakup kehilangan data dan informasi penting yang berpengaruh pada kontinuitas operasional. Salah satu langkah strategis dalam menghadapi gangguan ini adalah dengan menganalisis potensi bencana serta merancang Disaster Recovery Planning (DRP). Tantangan utama dalam DRP adalah menentukan prioritas pemulihan mesin virtual secara efisien dan mengelola Recovery Point Objective (RPO) secara optimal, mengingat keterbatasan waktu dalam proses pemulihan. Penelitian ini mengusulkan metode optimasi DRP berbasis algoritma genetika yang diterapkan pada VMware Site Recovery Manager (SRM). Algoritma genetika digunakan untuk menentukan prioritas pemulihan VM berdasarkan SLA dengan tahapan pembentukan kromosom, inisialisasi populasi, evaluasi fitness, seleksi, crossover, dan mutasi guna memperoleh solusi optimal. Evaluasi fitness mempertimbangkan pengurangan downtime dan minimisasi gangguan operasional. Hasil penelitian menunjukkan algoritma genetika mampu mengurangi downtime IT secara signifikan, dengan peningkatan efisiensi pemulihan hingga 50%. Model ini terbukti efektif dalam mengoptimalkan SRM dan dapat menjadi referensi bagi strategi pemulihan bencana IT di masa depan.
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