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Perancangan Sistem Pengenalan Wajah Dengan Metode CNN Pada Sistem Keamanan Door Lock Pintu Kamar Hotel

Edu Elektrika Journal · Vol. 12 No. 2 (2025) · pp. 25–30

DOI
10.15294/0724xq71
ISSN
2723-5602, 2252-7095
Published
2025-01-15
Publisher
LPPM Universitas Negeri Semarang
Language
eng

Abstract

Room door lock security can be managed using conventional techniques or automated systems. Currently, most hotels in Indonesia, particularly in the Lombok area, utilize card keys for room access. This method is effective and convenient, as guests do not need to carry physical keys. However, there are instances when guests forget to take their card when leaving the room, which complicates re-entering their accommodations. One potential solution is to implement the Convolutional Neural Network (CNN) method for recognition. The CNN process involves four key stages: area detection, feature extraction, matching, and recognition. Tests conducted on this system indicate that the CNN method can accurately recognize provided input images. Out of 10 images tested, 90% were recognized successfully. The results suggest that the CNN method is a promising option for enhancing room lock security

Keywords

Collaboration network of the authors

29 authors · 99 co-authorship links

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Co-authorOrganisationJoint articles
. RinduwatiAffiliation unknown2
Hetty ManurungAffiliation unknown1
SamsuriantoAffiliation unknown1
Ratna KusumaAffiliation unknown1
Yanti Puspita SariAffiliation unknown1
Dwi SusantoAffiliation unknown1
Bodhi DharmaAffiliation unknown1
Eko KusumawatiAffiliation unknown1
JusmaldiAffiliation unknown1
Ervinda YuliatinAffiliation unknown1
Aloysia Sri PujiyantiAffiliation unknown1
Febry Rahmadhani HasibuanAffiliation unknown1
Amir YassiAffiliation unknown1
Ifayanti RidwanAffiliation unknown1
Syamsuddin NompoAffiliation unknown1
R IsnainiAffiliation unknown1
N SyamAffiliation unknown1
. IswantoAffiliation unknown1
Muh. Yusril LatifAffiliation unknown1
. SyamsuddinAffiliation unknown1
S. HasanAffiliation unknown1
A. AsrianieAffiliation unknown1
Dinda KhairunnisaAffiliation unknown1
MariyaniAffiliation unknown1
Zirlia AnggrainiAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/journals/eduel/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">Perancangan Sistem Pengenalan Wajah Dengan Metode CNN Pada Sistem Keamanan Door Lock Pintu Kamar Hotel</dc:title>
	<dc:creator xml:lang="en">Anwariyah, Komariyuli</dc:creator>
	<dc:creator xml:lang="en">Hariani, Yuni Sulpia</dc:creator>
	<dc:creator xml:lang="en">Budiman</dc:creator>
	<dc:creator xml:lang="en">MZ, Dedy Sofian</dc:creator>
	<dc:subject xml:lang="en">Face recognition, convolution neural network, door lock, Image Processing</dc:subject>
	<dc:description xml:lang="en">Room door lock security can be managed using conventional techniques or automated systems. Currently, most hotels in Indonesia, particularly in the Lombok area, utilize card keys for room access. This method is effective and convenient, as guests do not need to carry physical keys. However, there are instances when guests forget to take their card when leaving the room, which complicates re-entering their accommodations. One potential solution is to implement the Convolutional Neural Network (CNN) method for recognition. The CNN process involves four key stages: area detection, feature extraction, matching, and recognition. Tests conducted on this system indicate that the CNN method can accurately recognize provided input images. Out of 10 images tested, 90% were recognized successfully. The results suggest that the CNN method is a promising option for enhancing room lock security </dc:description>
	<dc:publisher xml:lang="en">LPPM Universitas Negeri Semarang</dc:publisher>
	<dc:date>2025-01-15</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unnes.ac.id/journals/eduel/article/view/10981</dc:identifier>
	<dc:identifier>10.15294/0724xq71</dc:identifier>
	<dc:source xml:lang="en">Edu Elektrika Journal; Vol. 12 No. 2 (2024); 25-30</dc:source>
	<dc:source>2723-5602</dc:source>
	<dc:source>2252-7095</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/journals/eduel/article/view/10981/2763</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2024 Edu Elektrika Journal</dc:rights>
</oai_dc:dc>