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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Penelitian Pendidikan IPA (JPPIPA) Indonesian Journal of Artificial Intelligence and Data Mining Building of Informatics, Technology and Science Jurnal Teknik Informatika (JUTIF) Charity : Jurnal Pengabdian Masyarakat Indonesian Community Journal eProceedings of Engineering IJoICT (International Journal on Information and Communication Technology)
Donni Richasdy
Telkom University
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Physics Public Health Social Sciences Other

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Pengembangan Sistem Informasi Manajemen Pemakaman Berbasis Web untuk Pengelolaan Situs Pemakaman Bersejarah di Yayasan Sajarah Timbanganten Bandung Nungki Selviandro; Angel Metanosa Afinda; Fauzan Firdaus; Widia Febriyani; Donni Richasdy; Muhammad Maulana Yusuf; Indah Novitasari Dwi Saputro
I-Com: Indonesian Community Journal Vol 6 No 1 (2026): I-Com: Indonesian Community Journal (Maret 2026)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/i-com.v6i1.9087

Abstract

Pengelolaan pemakaman bersejarah di Yayasan Sajarah Timbanganten Bandung masih menghadapi permasalahan administrasi, inkonsistensi data, dan keterbatasan pengelolaan lahan makam. Kegiatan pengabdian kepada masyarakat ini bertujuan mengembangkan dan mengimplementasikan Sistem Informasi Manajemen Pemakaman TIMGRAVID sebagai solusi digital terintegrasi. Metode yang digunakan adalah Participatory Action Research (PAR) dan User-Centered Design (UCD) dengan keterlibatan aktif mitra. Sistem berbasis web dikembangkan secara modular dengan basis data terpusat untuk mendukung layanan publik, pengelolaan operasional, keuangan, serta pengawasan. Hasil evaluasi menunjukkan peningkatan akurasi dan transparansi pengelolaan serta tingkat kepuasan mitra yang sangat baik dengan nilai rerata di atas 4,5 (skala 1–5). Temuan ini menunjukkan bahwa sistem TIMGRAVID efektif mendukung efisiensi pengelolaan pemakaman sekaligus pelestarian warisan budaya melalui dokumentasi digital.
MNetNCR: MobileNet model for efficient traditional Nusantara script character recognition Untari Novia Wisesty; Aditya Firman Ihsan; Mahmud Dwi Sulistiyo; Donni Richasdy; Prasti Eko Yunanto; Gamma Kosala; Arfive Gandhi; Febryanti Sthevanie
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.
Text Classification Using Large Language Models to Detect AI and Human-Generated Sentences Arfan Rahman Yudiantoro; Prati Hutari Gani; Donni Richasdy
IJoICT (International Journal on Information and Communication Technology) Vol. 12 No. 1 (2026): Vol.12 No.1 Jun 2026
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v12i1.11223

Abstract

With the rapid development of the technology of Artificial Intelligence (AI), especially Large Language Models (LLMs) like ChatGPT, GPT-4 and Gemini, systems have become able to generate texts very similar to human writing. This similarity has been a boon to various sectors, but also poses fresh challenges of content authenticity and data integrity. A significant challenge is finding a way to automatically and accurately distinguish AI-generated sentences from human-written ones. This research focuses on building a text classification model that uses Large Language Models to distinguish between AI-generated and human-written sentences. This approach of research is based on recent research models that combine deep learning and classification using LLMs . The research process involves gathering human and AI-generated text data, pre-processing the text to normalize and tokenize it, feature extraction using the embeddings of large language models like IndoBERT, training the binary classification model, and assessing the model's performance using the metrics accuracy, precision, recall, and F1-score. Keywords: Text clustering, Large language models, AI text identification, Text authenticity.
Co-Authors Ade Romadhony Aditya Firman Ihsan Amala, Ihsan Ahsanu Angel Metanosa Afinda Arfan Rahman Yudiantoro Arfive Gandhi Arie Ardiyanti Suryani Aroman, Andika Djatnika Widia Nugraha Elsa Rachel Dementieva Erbina Selvia Br Perangin-Angin Fauzan Firdaus Febriyani, Widia Febryanti Sthevanie Firmansyah, Nanda Gamma Kosala H Hasmawati Hasmawati Hasmawati Indah Novitasari Dwi Saputro Irfan Budi Prakoso Jofardho Adlinnas Kemas Muslim Lhaksmana Mahendra Dwifebri Purbolaksono Mahmud Dwi Sulistiyo Meillano, Zico Fachreza Moch Arif Bijaksana Muhammad Alwi Nugraha Muhammad Daffa Regenta Sutrisno Muhammad Faris Abdussalam Muhammad Maulana Yusuf Nazar Azmi Nungki Selviandro Prasti Eko Yunanto Pratama, Reyhan Prati Hutari Gani Ramanti Dharayani Rendhy Al-Farrel Rendy Andrian Saputra Rheza Ramadhan Putra Ridho Akbar B41110063 Rimbawan, Awan Rinaldi Jasmi Saiful Akbar Salsabila Putri Adityani Sa’adah, Siti Sean Akbar Ryanto Septariken, Mohammad Fajra Silfi Nur Amalia Silvia Atika Anggrayni Sri Widowati Tandya Rizky Pratama Untari Novia Wisesty Widi Astuti Wijaya, Kurniadi Ahmad Winkie Setyono ZK Abdurahman Baizal