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Lampung Script Recognition Using Convolutional Neural Network

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 16 No. 1 (2022) · pp. 23–34

DOI
10.22146/ijccs.70041
ISSN
2460-7258, 1978-1520
Published
2022-01-31
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The Lampung script is often used in writing words in Lampung language. The Lampung language itself is used by native Lampung people and people who learn Lampung language. The Lampung script is difficult to learn because there are many combinations of parent characters and subletters. CNN is a method in the field of object recognition that has a specific layer, namely a convolution layer and a pooling layer that allows the feature learning process well. Handwriting recognition as in character recognition in MNIST, CNN produces better performance compared to other methods. From the advantages of CNN, the CNN method with DenseNet architecture was chosen as the best architecture to recognize each Lampung script. In this study, there are 2 main processes, namely preprocessing, and recognition. This study succeeded in applying the CNN method which can recognize Lampung script. The dataset is divided into 4 groups of characters that have different sounds. First, the parent character data get 98% accuracy. Second, the parent letter data with the above letters get 98% accuracy. Third, the parent character data with the sub-letters on the side get 98% accuracy. Fourth, the parent letter data with the lower letters get 97% accuracy.

Keywords

Collaboration network of the authors

40 authors · 52 co-authorship links · 15 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Gadjah Mada
  • Universitas Stikubank
  • University of Indonesia
  • State University of Semarang
  • Universitas Pendidikan Ganesha
  • State University of Medan
  • Duta Wacana Christian University
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Edi WinarkoUniversitas Gadjah Mada3
Retantyo WardoyoUniversitas Gadjah Mada2
Sri T. HartatiUniversitas Gadjah Mada2
Edy WinarnoUniversitas Stikubank2
Aniati Murni ArymurthyUniversity of Indonesia2
Kridalaksana Harsa AwangAffiliation unknown1
Zaenal AbidinState University of Semarang1
Yustina RetnoAffiliation unknown1
Abriyono AbriyonoAffiliation unknown1
I Gede Aris GunadiUniversitas Pendidikan Ganesha1
Rocky Yefrenes DillakUniversitas Gadjah Mada1
Ikhwan RusliantoUniversitas Gadjah Mada1
Rahmi HidayatiUniversitas Gadjah Mada1
Salman AliajiUniversitas Gadjah Mada1
Refta ListiaUniversitas Gadjah Mada1
Mahmuddin YunusAffiliation unknown1
Hermawan SyahputraState University of Medan1
Sri SuwarnoDuta Wacana Christian University1
Rajif Agung YunmarSumatera Institute of Technology1
Nurmiyati TamatjitaUniversitas Gadjah Mada1
La Ode Hasnuddin S. SagalaUniversitas Gadjah Mada1
Nicodemus Mardanus SetiohardjoPoliteknik Negeri Kupang1
I Putu Adi PratamaUniversitas Gadjah Mada1
Herman HermanUniversitas Gadjah Mada1
Dian Hafidh ZulfikarUniversitas Gadjah Mada1
Made Leo RadhityaInstitut Bisnis dan Teknologi Indonesia1
Kharis SyabanUniversitas Gadjah Mada1
Pawit RiantoAffiliation unknown1
Adri PriadanaUniversitas Gadjah Mada1
Ade NurhopipahUniversitas Amikom Purwokerto1
Aina MusdholifahUniversitas Gadjah Mada1
Nelson RumuiPoliteknik Negeri Ketapang1
Angga Maulana PurbaUniversitas Gadjah Mada1
Mohammad Edi WibowoAffiliation unknown1
Wahyono WahyonoUniversitas Gadjah Mada1
Abdul KholikUniversitas Gadjah Mada1
Anny Kartika SariUniversitas Gadjah Mada1
Alfian Abdul JalidUniversitas Gadjah Mada1

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.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">Lampung Script Recognition Using Convolutional Neural Network</dc:title>
	<dc:creator>Bintoro, Panji</dc:creator>
	<dc:creator>Harjoko, Agus</dc:creator>
	<dc:subject xml:lang="en-US">Computer Science</dc:subject>
	<dc:subject xml:lang="en-US">Lampung Script, Pattern Recognition, Deep Learning, Convolutional Neural Network, Densely Connected Convolutional Network</dc:subject>
	<dc:description xml:lang="en-US">The Lampung script is often used in writing words in Lampung language. The Lampung language itself is used by native Lampung people and people who learn Lampung language. The Lampung script is difficult to learn because there are many combinations of parent characters and subletters. CNN is a method in the field of object recognition that has a specific layer, namely a convolution layer and a pooling layer that allows the feature learning process well. Handwriting recognition as in character recognition in MNIST, CNN produces better performance compared to other methods. From the advantages of CNN, the CNN method with DenseNet architecture was chosen as the best architecture to recognize each Lampung script. In this study, there are 2 main processes, namely preprocessing, and recognition. This study succeeded in applying the CNN method which can recognize Lampung script. The dataset is divided into 4 groups of characters that have different sounds. First, the parent character data get 98% accuracy. Second, the parent letter data with the above letters get 98% accuracy. Third, the parent character data with the sub-letters on the side get 98% accuracy. Fourth, the parent letter data with the lower letters get 97% accuracy.</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>2022-01-31</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/70041</dc:identifier>
	<dc:identifier>10.22146/ijccs.70041</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 16, No 1 (2022): January; 23-34</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/70041/33160</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 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>
</oai_dc:dc>