DETERMINING ELECTRIC VEHICLE CHARGING STATION LOCATION (EVCS) : K-MEANS CLUSTERING AND ANALYTIC HIERARCHY PROCESS STUDY CASE PT NATARA ENERGY INDONESIA

The number of electric vehicles (EV) users is targeted by the Indonesian government in 2030 to reach 2 million users. PT Natara Energy, a company appointed by the Indonesian government to oversee the energy transition, targets the construction of Electric Vehicle Charging Stations (EVCS) infrastruct...

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Main Author: Rachmawati, Evi
Format: Theses
Language:Indonesia
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Online Access:https://digilib.itb.ac.id/gdl/view/71020
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:71020
spelling id-itb.:710202023-01-26T09:12:45ZDETERMINING ELECTRIC VEHICLE CHARGING STATION LOCATION (EVCS) : K-MEANS CLUSTERING AND ANALYTIC HIERARCHY PROCESS STUDY CASE PT NATARA ENERGY INDONESIA Rachmawati, Evi Manajemen umum Indonesia Theses Electric Charging Stations, Charging Locations, Electric Vehicles, SPKLU, EVCS, Clustering, AHP INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/71020 The number of electric vehicles (EV) users is targeted by the Indonesian government in 2030 to reach 2 million users. PT Natara Energy, a company appointed by the Indonesian government to oversee the energy transition, targets the construction of Electric Vehicle Charging Stations (EVCS) infrastructure in 2030 to reach 7,146 EVCS by ensuring that EV stations are spread according to the needs of the population segment. This paper describes determining the location of Electric Vehicle Charging Stations (EVCS) with the minimum number possible and can be reached by motorists or consumers within a certain distance using the Analytic Hierarchy Process (AHP) method. The first method is to determine the distance to the nearest centroid and the time it takes consumers to get to the EV charging station using the Clustering method by comparing two clustering algorithms: K-Means and Dbscan. Producing the output of the number of clusters based on EVCS demand from the highest demand, medium demand, and lowest demand. The output will be mapped according to the needs and conditions in the field so that the minimum number of EVCS that must be built in each area or cluster can be determined to cover the needs of EVCS in each city, especially in the province of West Java. The second method is to determine the weight of each evaluation criterion using the Analytic Hierarchy Process (AHP) method to show the priority order of the development of each EVCS. The determination of the minimum number of EVCS developments has a positive impact on saving infrastructure costs and the effectiveness of public services as well as on the company's financial performance. The results of this study are the determination of strategic locations and the minimum number of EVCS needed by each city, especially in West Java province, based on the main priorities in each area that can be used as a consideration for company management in making decisions on the location of EVCS development effectively and efficiently. 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
topic Manajemen umum
spellingShingle Manajemen umum
Rachmawati, Evi
DETERMINING ELECTRIC VEHICLE CHARGING STATION LOCATION (EVCS) : K-MEANS CLUSTERING AND ANALYTIC HIERARCHY PROCESS STUDY CASE PT NATARA ENERGY INDONESIA
description The number of electric vehicles (EV) users is targeted by the Indonesian government in 2030 to reach 2 million users. PT Natara Energy, a company appointed by the Indonesian government to oversee the energy transition, targets the construction of Electric Vehicle Charging Stations (EVCS) infrastructure in 2030 to reach 7,146 EVCS by ensuring that EV stations are spread according to the needs of the population segment. This paper describes determining the location of Electric Vehicle Charging Stations (EVCS) with the minimum number possible and can be reached by motorists or consumers within a certain distance using the Analytic Hierarchy Process (AHP) method. The first method is to determine the distance to the nearest centroid and the time it takes consumers to get to the EV charging station using the Clustering method by comparing two clustering algorithms: K-Means and Dbscan. Producing the output of the number of clusters based on EVCS demand from the highest demand, medium demand, and lowest demand. The output will be mapped according to the needs and conditions in the field so that the minimum number of EVCS that must be built in each area or cluster can be determined to cover the needs of EVCS in each city, especially in the province of West Java. The second method is to determine the weight of each evaluation criterion using the Analytic Hierarchy Process (AHP) method to show the priority order of the development of each EVCS. The determination of the minimum number of EVCS developments has a positive impact on saving infrastructure costs and the effectiveness of public services as well as on the company's financial performance. The results of this study are the determination of strategic locations and the minimum number of EVCS needed by each city, especially in West Java province, based on the main priorities in each area that can be used as a consideration for company management in making decisions on the location of EVCS development effectively and efficiently.
format Theses
author Rachmawati, Evi
author_facet Rachmawati, Evi
author_sort Rachmawati, Evi
title DETERMINING ELECTRIC VEHICLE CHARGING STATION LOCATION (EVCS) : K-MEANS CLUSTERING AND ANALYTIC HIERARCHY PROCESS STUDY CASE PT NATARA ENERGY INDONESIA
title_short DETERMINING ELECTRIC VEHICLE CHARGING STATION LOCATION (EVCS) : K-MEANS CLUSTERING AND ANALYTIC HIERARCHY PROCESS STUDY CASE PT NATARA ENERGY INDONESIA
title_full DETERMINING ELECTRIC VEHICLE CHARGING STATION LOCATION (EVCS) : K-MEANS CLUSTERING AND ANALYTIC HIERARCHY PROCESS STUDY CASE PT NATARA ENERGY INDONESIA
title_fullStr DETERMINING ELECTRIC VEHICLE CHARGING STATION LOCATION (EVCS) : K-MEANS CLUSTERING AND ANALYTIC HIERARCHY PROCESS STUDY CASE PT NATARA ENERGY INDONESIA
title_full_unstemmed DETERMINING ELECTRIC VEHICLE CHARGING STATION LOCATION (EVCS) : K-MEANS CLUSTERING AND ANALYTIC HIERARCHY PROCESS STUDY CASE PT NATARA ENERGY INDONESIA
title_sort determining electric vehicle charging station location (evcs) : k-means clustering and analytic hierarchy process study case pt natara energy indonesia
url https://digilib.itb.ac.id/gdl/view/71020
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