DETERMINING DISASTER LOGISTICS CENTER IN WEST JAVA PROVINCE USING VORONOI DIAGRAM AND K-MEANS ALGORITHM

Indonesia is an archipelago with a high vulnerability to various types of disasters, both natural and non-natural. The province of West Java, in particular, faces threats from hydrometeorological disasters such as floods, landslides, and earthquakes due to its location in an active tectonic zone....

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Main Author: Nafia, Isya
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/84596
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:84596
spelling id-itb.:845962024-08-16T09:34:14ZDETERMINING DISASTER LOGISTICS CENTER IN WEST JAVA PROVINCE USING VORONOI DIAGRAM AND K-MEANS ALGORITHM Nafia, Isya Indonesia Theses Distribution Center, Disaster Logistics, Voronoi, K-Means INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/84596 Indonesia is an archipelago with a high vulnerability to various types of disasters, both natural and non-natural. The province of West Java, in particular, faces threats from hydrometeorological disasters such as floods, landslides, and earthquakes due to its location in an active tectonic zone. Effective disaster management, especially in providing aid to victims, requires proper management, including a Logistics Center establishment. Where should the Logistics Center be located to monitor the districts and cities in West Java? To answer this question, research was conducted to determine the optimal locations for disaster logistics centers in West Java, aiming to optimize aid distribution. The methodology used includes the Voronoi Diagram model and the K-means algorithm. The Voronoi Diagram focuses on determining the coverage area of each disaster logistics center. This technique divides space into regions based on the closest distance to certain points known as sites or generators. Meanwhile, the K- means algorithm focuses on determining the optimal centroid locations of the clusters of disaster logistics centers, grouping data into K clusters based on similar attributes. The process begins with randomly selecting initial centroids and then iteratively refining their locations to obtain compact and well-separated clusters. This study evaluated 27 cities/districts in West Java using population data and disaster package requirements, including food, clothing, other logistics, and fatalities. Different aid distribution scenarios were designed, considering a combination of storage warehouses and Vendor management inventorys (VMI). The analysis results show that the scenario with five logistics centers located in Bandung City, Bogor Regency, Tasikmalaya Regency, Cirebon Regency, and Karawang Regency is the most effective. These logistics centers combine main warehouses, intermediate warehouses, and VMI at strategic locations. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Indonesia is an archipelago with a high vulnerability to various types of disasters, both natural and non-natural. The province of West Java, in particular, faces threats from hydrometeorological disasters such as floods, landslides, and earthquakes due to its location in an active tectonic zone. Effective disaster management, especially in providing aid to victims, requires proper management, including a Logistics Center establishment. Where should the Logistics Center be located to monitor the districts and cities in West Java? To answer this question, research was conducted to determine the optimal locations for disaster logistics centers in West Java, aiming to optimize aid distribution. The methodology used includes the Voronoi Diagram model and the K-means algorithm. The Voronoi Diagram focuses on determining the coverage area of each disaster logistics center. This technique divides space into regions based on the closest distance to certain points known as sites or generators. Meanwhile, the K- means algorithm focuses on determining the optimal centroid locations of the clusters of disaster logistics centers, grouping data into K clusters based on similar attributes. The process begins with randomly selecting initial centroids and then iteratively refining their locations to obtain compact and well-separated clusters. This study evaluated 27 cities/districts in West Java using population data and disaster package requirements, including food, clothing, other logistics, and fatalities. Different aid distribution scenarios were designed, considering a combination of storage warehouses and Vendor management inventorys (VMI). The analysis results show that the scenario with five logistics centers located in Bandung City, Bogor Regency, Tasikmalaya Regency, Cirebon Regency, and Karawang Regency is the most effective. These logistics centers combine main warehouses, intermediate warehouses, and VMI at strategic locations.
format Theses
author Nafia, Isya
spellingShingle Nafia, Isya
DETERMINING DISASTER LOGISTICS CENTER IN WEST JAVA PROVINCE USING VORONOI DIAGRAM AND K-MEANS ALGORITHM
author_facet Nafia, Isya
author_sort Nafia, Isya
title DETERMINING DISASTER LOGISTICS CENTER IN WEST JAVA PROVINCE USING VORONOI DIAGRAM AND K-MEANS ALGORITHM
title_short DETERMINING DISASTER LOGISTICS CENTER IN WEST JAVA PROVINCE USING VORONOI DIAGRAM AND K-MEANS ALGORITHM
title_full DETERMINING DISASTER LOGISTICS CENTER IN WEST JAVA PROVINCE USING VORONOI DIAGRAM AND K-MEANS ALGORITHM
title_fullStr DETERMINING DISASTER LOGISTICS CENTER IN WEST JAVA PROVINCE USING VORONOI DIAGRAM AND K-MEANS ALGORITHM
title_full_unstemmed DETERMINING DISASTER LOGISTICS CENTER IN WEST JAVA PROVINCE USING VORONOI DIAGRAM AND K-MEANS ALGORITHM
title_sort determining disaster logistics center in west java province using voronoi diagram and k-means algorithm
url https://digilib.itb.ac.id/gdl/view/84596
_version_ 1822010426006700032