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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Journal of Information Systems Engineering and Business Intelligence Indonesian Journal on Computing (Indo-JC) Al Ishlah Jurnal Pendidikan JITK (Jurnal Ilmu Pengetahuan dan Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Bubungan Tinggi: Jurnal Pengabdian Masyarakat Charity : Jurnal Pengabdian Masyarakat Jurnal Informatika Teknologi dan Sains (Jinteks) eProceedings of Engineering Proceeding of Community Service and Engagement
Arfive Gandhi
Universitas Telkom
Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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MNetNCR: MobileNet model for efficient traditional Nusantara script character recognition Wisesty, Untari Novia; Ihsan, Aditya Firman; Sulistiyo, Mahmud Dwi; Richasdy, Donni; Yunanto, Prasti Eko; Kosala, Gamma; Gandhi, Arfive; Sthevanie, Febryanti
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i2.pp1513-1528

Abstract

Preservation of traditional Nusantara scripts is very important because these traditional scripts are part of the cultural heritage that reflects the identity and history of the nation. This research proposed MobileNet for Nusantara character recognition (MNetNCR) model based on MobileNetV3 architecture to recognize traditional Nusantara scripts with lightweight, efficient architecture, and accurate recognition. The novel and comprehensive datasets for traditional Nusantara scripts have been curated in this research, that will later be stored digitally and can be used in further research. This novel dataset includes handwritten Balinese, Batak, Javanese, Lontara, and Sundanese scripts, each with unique visual characteristics. The proposed MNetNCR model is highly effective in recognizing characters, achieving F1-scores of 0.9934 for Balinese, 0.9450 for Batak, 0.9788 for Javanese, 0.9936 for Lontara, and 0.9961 for Sundanese scripts, according to the experimental results. The MNetNCR model built in this research has been proven to be effective and efficient in recognizing traditional scripts accurately. It also supports the preservation and promotion of the nation's cultural and historical heritage.
Co-Authors Aditya Firman Ihsan Agustinus David Alneta, Isyraqi Putra Amir, Fathuddin Ashari Angelina Prima Kurniati Arie Ardiyanti Suryani Ario Harry Prayogo Athallah S, Zahid Dana Sulistiyo Kusumo Dana Sulistyo Kusumo Danang Junaedi Donni Richasdy Eko Darwiyanto Fathan Hanif, Ahmad Fathuddin Ashari Amir Febryanti Sthevanie Gamma Kosala Gede Agung Peramerta Harnanti, Assyifa Hutari Gani, Prati Ibrahim, Reyhan Abby Wahyu Indra Lukmana Sardi Intan Nur Aini Johan Alibasa, Muhamad Koenta Adji Koerniawan Kusumo, Dana Sulistyo Laksitowening, Kusuma Ayu Madhani, Dzaki Mahmud Dwi Sulistiyo Maulyta Noer Fadilla Mira Kania Sabariah Muhammad Arkan, Zaidan Muhasibi, Zahid Al Muthi’ah Az Zahra Nafi, Nazzala Qinthara Nori Wilantika Nungki Selviandro Nurwahid, Bintang Padliwinata, Rama Prasti Eko Yunanto Pratama, Regy Arya Adhi Prati Hutari Gani Prayogo, Ariq Dary Putri Larasati Rahman Sudibyo, Arief Rahmat Rambe Rihan Arifin, Irfan Rimbawan, Awan Rosa Reska Riskiana Sabariah , Mira Kania Safa Salsabila Damara Steven Gerald Sulistyo, Dana Tirta Gumelar, Wahyu Aji Untari Novia Wisesty Veronikha Effendy Villy Satria Praditha Wilantika, Nori Yudhoyono, Adrian Senoaji Teguh Yuriza Mufidah Zahid Al Muhasibi Zaky Eryana, Muhammad Auzan