Article Per Year (5 Year)
p-Index From 2021 - 2026
6.155
P-Index
This Author published in this journals
All Journal International Journal of Advances in Applied Sciences JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Creative Information Technology Journal Techno Nusa Mandiri : Journal of Computing and Information Technology JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL ILMIAH INFORMATIKA JurTI (JURNAL TEKNOLOGI INFORMASI) Martabe : Jurnal Pengabdian Kepada Masyarakat Krea-TIF: Jurnal Teknik Informatika CSRID (Computer Science Research and Its Development Journal) Informasi Interaktif CCIT (Creative Communication and Innovative Technology) Journal Indonesian Journal of Business Intelligence (IJUBI) IJIIS: International Journal of Informatics and Information Systems Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Management and Sustainable Development Journal Journal of Applied Data Sciences International Journal of Computer and Information System (IJCIS) Jurnal Pengabdian Kepada Masyarakat Patikala Journal Computer Science and Informatic Systems : J-Cosys Jurnal Ilmiah Edutic : Pendidikan dan Informatika Jurnal Informatika: Jurnal Pengembangan IT ABDIKOM
Musthofa Galih Pradana
Universitas Pembangunan Nasional Veteran Jakarta
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Physics Social Sciences

Published : 53 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : journal of applied informatics and computing

 1 
Boosting CNN Accuracy for Sundanese Script Recognition through Feature Extraction Techniques Pradana, Musthofa Galih; Khoirunnisa, Hilda
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11332

Abstract

Sundanese script is included in the cultural heritage in Indonesia, especially the culture in West Java. As a society that appreciates and preserves Indonesian culture and art, active participation can be realized through efforts to strengthen and preserve this script, one of which is by utilizing digital media. One of the technology-based digital media that can be used to preserve culture is image detection to make it easier to recognize Sundanese script. One of the models that can be used is the Convolutional Neural Network (CNN) with the MobileNetV2 architecture, with limited resources this architecture is able to produce good detection. This study applies the Convolutional Neural Network (CNN) algorithm with the MobileNetV2 architecture which will be tested with two main test scenarios, namely by applying feature extraction and without using feature extraction. The focus of this study will explore the influence and significance of the influence of feature extraction on the final results of image detection using the Convolutional Neural Network (CNN). The two feature extraction models used are Local Binary Pattern and Gray-Level Co-occurrence Matrix. These two feature extraction models will be tested with Sundanese script image data with data of 2,300 Sundanese script images. The results of this study show that the best results were obtained in the Convolutional Neural Network (CNN) with Gray-Level Co-occurrence Matrix (GLCM) with the best accuracy results at 93.8%. This is because the addition of the Gray-Level Co-occurrence Matrix (GLCM) is able to capture spatial texture statistics such as contrast, homogeneity, entropy, and correlation between pixel pairs. With these results, it can be concluded that in this study feature extraction has an effect and is able to increase the detection accuracy of the Convolutional Neural Network (CNN) model with the MobileNetV2 architecture in Sundanese script image data.
Construction of a Dialect-Sensitive Javanese Semantic Lexicon to Support Machine Translation Systems Musthofa Galih Pradana; Ridwan Raafi'udin; Nurul Afifah Arifuddin; Mohammad Asaduzzaman Rasel
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13379

Abstract

The development of linguistic resources for natural language processing (NLP) in Javanese remains limited, especially regarding the representation of semantic relationships between different speech levels. This study aims to construct a Javanese semantic lexicon that integrates Indonesian lexical equivalents with three Javanese speech levels: ngoko, krama alus, and krama inggil. A research design based on lexical resource construction was employed, using a Javanese digital dictionary as the primary data source. The methodology included data extraction, preprocessing, semantic lexicon construction, analysis of speech level variation, and a preliminary exploration of polysemous lexical entries using automatic identification, followed by validation by native speakers. The resulting semantic lexicon successfully represents lexical relationships between levels in a structured manner. Analysis of speech-level variation revealed that partially distinct lexical patterns were the most dominant, with 733 entries, followed by fully distinct patterns (193 entries) and identical patterns (21 entries). These findings indicate that speech-level differences in Javanese are selectively realized and should be explicitly considered in the development of linguistic resources. Furthermore, preliminary exploration of polysemous candidates demonstrated that dictionary-based automatic identification can overestimate polysemy without linguistic validation. Only a limited number of lexical entries exhibited features consistent with genuine polysemous relationships. This study provides an initial basis for the development of Javanese semantic resources that are sensitive to speech-level variation and semantic complexity. The constructed semantic lexicon has the potential to support future research in NLP applications in Javanese, including politeness identification, lexical normalization, word sense disambiguation, and machine translation.
Co-Authors Adhien Kenya Anima Estetikha Andri Pramuntadi Anni Alvionita Simanjuntak Arbiati Faizah Ardhyansyah Mualo Bondan Wahyu Pamekas Budi, Ryan Setya Dema Mathias Lumban Tobing Dhina Puspasari Wijaya, Dhina Puspasari Dyah Listianing Tyas, Dyah Listianing Emha Taufiq Luthfi Fadhli Suko Wiryanto Fandli Supandi Gutama, Deden Hardan Ha, Hoang Thi Henki Bayu Seta Hoang Thi Ha I Wayan Rangga Pinastawa Izzety, Aurel Jayanta Kaharuddin Kharisma Wiati Gusti Khoironi, Khoironi Khoirunnisa, Hilda Kusrini MARTINI, NI PUTU DEVIRA AYU Mohammad Asaduzzaman Rasel Mu, Jesselyn Muhamad Ridwan Muhammad Adrezo Muthia Zahrah, Nada Nada Muthia Zahrah Neny Rosmawarni Nindy Irzavika Niqotaini, Zatin Nurcahyo, Azriel Christian Nurhajar Anugraha Nurhuda Maulana Nurul Afifah Arifuddin Nyamiati, Retno Dwi Prananto, Muhammad Teguh Pujo Hari Saputro Radinal Setyadinsa Rangga Pinastawa, I Wayan Rangga Saputra Ridlo Muttaqien Ridwan Raafi'udin Rifka Dwi Amalia Rifqi Hammad Rusiyono, Ruwet Ryan Setya Budi Salma Ashiila Rabbani Setiawan, Deandra Satriyo Shabrina, Husna Muizzati Syaila Ananta Karenina Wahit Desta Prastowo Wahyuni Fithratul Zalmi Wari, Valtrizt Khalifah Yulianto Mustaqim Yusuf Hendra Pratama