Pengembangan Model Jaringan Kapal Penanggulangan Bencana Dalam Tata Kelola Penanggulangan Kebencanaan Secara Terintegrasi Di Indonesia

Rasyid, Erwin (2025) Pengembangan Model Jaringan Kapal Penanggulangan Bencana Dalam Tata Kelola Penanggulangan Kebencanaan Secara Terintegrasi Di Indonesia. Doctoral thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Indonesia terletak di pertemuan tiga lempeng tektonik utama yaitu Indo-Australia, Eurasia, dan Pasifik yang menyebabkan tingginya potensi bencana alam seperti gempa bumi, tsunami, letusan gunung berapi, tanah longsor, dan banjir. Kondisi ini menempatkan Indonesia dalam kawasan Cincin Api Pasifik dan menjadikannya salah satu negara paling rawan bencana di dunia. Saat ini, penanggulangan bencana di wilayah maritim sangat bergantung pada kapal milik TNI Angkatan Laut. Namun, distribusi kapal-kapal ini sering kali tidak sesuai dengan wilayah rawan bencana, sehingga menimbulkan keterlambatan respons dan tingginya biaya operasional. Selain itu, kapal milik Basarnas dan Bakamla juga tersedia, tetapi belum dimanfaatkan secara optimal. Tidak semua kapal cocok untuk semua jenis bencana atau wilayah, yang mengurangi efektivitas penanganan darurat. Penelitian ini bertujuan mengevaluasi kesesuaian distribusi kapal dengan peta risiko bencana nasional. Data yang dikaji mencakup jenis bencana, wilayah rawan, serta ketersediaan dan sebaran kapal. Algoritma Genetika digunakan untuk menentukan konfigurasi distribusi kapal yang optimal, kemudian dievaluasi menggunakan metode AHP agar mempertimbangkan aspek non-teknis. Hasil penelitian menunjukkan bahwa distribusi kapal saat ini belum optimal. Model GA-AHP yang diusulkan mampu mempercepat waktu respons darurat hingga 66 83 jam untuk skenario tsunami di Aceh, dan 71–85 jam untuk skenario gempa dan tsunami di Sulawesi Tengah, sekaligus menurunkan biaya operasional secara signifikan.
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Indonesia is situated at the convergence of three major tectonic plates—Indo Australian, Eurasian, and Pacific—resulting in a high potential for natural disasters such as earthquakes, tsunamis, volcanic eruptions, landslides, and floods. This geographical condition places Indonesia within the Pacific Ring of Fire, making it one of the most disaster-prone countries in the world. Currently, disaster response in maritime areas largely depends on the fleet owned by the Indonesian Navy (TNI AL), whose distribution often does not align with disaster-prone locations. This mismatch leads to delayed emergency response and increased operational costs. In addition to the Navy’s vessels, ships operated by Basarnas (National Search and Rescue Agency) and Bakamla (Indonesian Maritime Security Agency) are also available and potentially useful. However, not all vessels are suitable for every region or type of disaster, resulting in ineffective response and a higher risk of casualties. This study aims to evaluate the alignment between the distribution of disaster response vessels and the national disaster risk map. Data were collected on disaster types, high-risk areas, and the availability and distribution of relevant ships. A Genetic Algorithm (GA) was employed to identify the optimal vessel distribution, and the results were further evaluated using the Analytic Hierarchy Process (AHP) to incorporate non-technical factors. The findings reveal that the current vessel distribution is suboptimal. The proposed GA-AHP model demonstrates improved emergency response times and reduced operational costs. Simulations based on major disaster scenarios in Aceh and Central Sulawesi show that for the Aceh tsunami case, the emergency response time could be reduced by 66 to 83 hours, while for the Central Sulawesi earthquake and tsunami, the response time could be shortened by 71 to 85 hours.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	Tata kelola Kebencanaan; Genetic Algorithm; Indeks Risiko Bencana; Optimasi Jaringan, Disaster Management; Genetics Algorithm; Disaster Risk Index Networking Optimization
Subjects:	V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
Divisions:	Interdisciplinary School of Management and Technology (SIMT) > 66105-Doctor of Technology Management (DMT)
Depositing User:	- Davi Wah
Date Deposited:	04 Aug 2025 11:23
Last Modified:	04 Aug 2025 11:23
URI:	http://repository.its.ac.id/id/eprint/127278

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