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Optimization of Electric Vehicle Charging Stations Recommendation for Intercity Travel in Bali Using K-NN Algorithm

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 20 No. 2 (2026) · pp. 223–234

DOI
10.22146/ijccs.113372
ISSN
2460-7258, 1978-1520
Published
2026-04-30
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The problem of range anxiety among electric vehicle (EV) users is caused by the uneven distribution of Public Charging Stations (Indonesian: Stasiun Pengisian Kendaraan Listrik Umum, or SPKLU) in the Bali region often occurs. Currently, existing navigation applications provide SPKLU locations, but still lack route-based, battery-aware and vehicle connector type recommendations.To address this limitation, an SPKLU recommendation system was developed using the K-Nearest Neighbors (KNN) algorithm, specifically designed for intercity travel across Bali Island. The proposed method applies a two-stage filtering mechanism: Geodesic Distance for initial candidate selection, followed by the Google Maps Directions API for route-accurate distance validation. The research data were obtained through manual collection from the PLN Mobile application, containing geographic coordinate locations and connector type information. User inputs parameters include origin, destination, current EV range, maximum travel capacity, and vehicle connector type.Experimental results show that the system can provide accurate SPKLU suggestions aligned with planned routes and optimal charging intervals. The findings indicate that the proposed model is lightweight, adaptive, and effective in supporting EV users, thereby reducing range anxiety while contributing to the promotion of sustainable transportation in Indonesia.

Keywords

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Metadata source: OAI-PMH (metadata jurnal) https://journal.ugm.ac.id/ijccs/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Optimization of Electric Vehicle Charging Stations Recommendation for Intercity Travel in Bali Using K-NN Algorithm</dc:title>
	<dc:creator>Theijer, Jessica</dc:creator>
	<dc:creator>Tanamal, Rinabi</dc:creator>
	<dc:subject xml:lang="en-US">Information System</dc:subject>
	<dc:subject xml:lang="en-US">K-Nearest Neighbors, Geodesic Distance, electric vehicle, range anxiety, Bali Island</dc:subject>
	<dc:description xml:lang="en-US">The problem of range anxiety among electric vehicle (EV) users is caused by the uneven distribution of Public Charging Stations (Indonesian: Stasiun Pengisian Kendaraan Listrik Umum, or SPKLU) in the Bali region often occurs. Currently, existing navigation applications provide SPKLU locations, but still lack route-based, battery-aware and vehicle connector type recommendations.To address this limitation, an SPKLU recommendation system was developed using the K-Nearest Neighbors (KNN) algorithm, specifically designed for intercity travel across Bali Island. The proposed method applies a two-stage filtering mechanism: Geodesic Distance for initial candidate selection, followed by the Google Maps Directions API for route-accurate distance validation. The research data were obtained through manual collection from the PLN Mobile application, containing geographic coordinate locations and connector type information. User inputs parameters include origin, destination, current EV range, maximum travel capacity, and vehicle connector type.Experimental results show that the system can provide accurate SPKLU suggestions aligned with planned routes and optimal charging intervals. The findings indicate that the proposed model is lightweight, adaptive, and effective in supporting EV users, thereby reducing range anxiety while contributing to the promotion of sustainable transportation in Indonesia.</dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2026-04-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/113372</dc:identifier>
	<dc:identifier>10.22146/ijccs.113372</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 20, No 2 (2026): April; 223-234</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/113372/43998</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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