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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Teknologi Informasi dan Ilmu Komputer JOIN (Jurnal Online Informatika) International Journal of Artificial Intelligence Research Technomedia Journal Journal of Education Technology Aptisi Transactions on Management JTP - Jurnal Teknologi Pendidikan Aptisi Transactions on Technopreneurship (ATT) CCIT (Creative Communication and Innovative Technology) Journal ADI Journal on Recent Innovation (AJRI) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics ADI Bisnis Digital Interdisiplin (ABDI Jurnal) IAIC Transactions on Sustainable Digital Innovation (ITSDI) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi International Transactions on Artificial Intelligence (ITALIC)
Santoso, Nuke Puji Lestari
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Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Social Sciences Other

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Journal : International Transactions on Artificial Intelligence (ITALIC)

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Transformation of Indonesian Language in Social Media Using AI Expert Systems and Machine Learning Santoso, Nuke Puji Lestari; Rawat, Bhupesh; Ratri, Sanda Ramadhan; Danang, Danang; Kumoro, Dwi Ferdiyatmoko Cahya; Supriati, Ruli; Natalia, Elisa Ananda
International Transactions on Artificial Intelligence Vol. 3 No. 2 (2025): May
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v3i2.806

Abstract

This study explores the transformation of the Indonesian language on social media platforms by integrating advanced artificial intelligence techniques, including expert systems and machine learning algorithms. The rapid evolution of communication on platforms such as TikTok, Twitter, and Instagram has led to a dynamic shift in language use, characterized by increased creativity in slang, abbreviations, and code-mixing, alongside challenges in maintaining compliance with standard language norms. By applying intelligent systems capable of analyzing large volumes of social media data, this research aims to identify patterns of linguistic innovation and deviations from conventional language rules. The expert system framework supports automated detection and classification of language variations, while machine learning models enhance the accuracy and adaptability of language analysis over time. Findings indicate that AI-driven approaches can effectively balance the dual needs of fostering linguistic creativity and preserving language standards, providing valuable insights for language educators, policymakers, and digital content developers. The study underscores the potential of intelligent technologies to facilitate language monitoring and support efforts in maintaining the cultural identity of the Indonesian language amid the fast-paced digital communication landscape.
Reliability Assessment of Attendance Systems Based on Face Recognition Under Varying Lighting Conditions Afiyanto, Rafid; Astuti, Eka Dian; Kamal, Abdullah Arif; Santoso, Nuke Puji Lestari
International Transactions on Artificial Intelligence Vol. 4 No. 1 (2025): November
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v4i1.924

Abstract

The rapid adoption of face recognition technology for attendance systems has raised concerns about its reliability under varying lighting conditions, which often affect real world deployment. This study aims to analyze the reliability of a face recognition based attendance system under diverse lighting scenarios, addressing challenges in accuracy and robustness. The research employs a deep learning approach, utilizing a Convolutional Neural Network (CNN) trained on a dataset of facial images captured under controlled and uncontrolled lighting conditions, ranging from low to high illumination levels. The methodology includes preprocessing techniques for illumination normalization and feature extraction, followed by performance evaluation using metrics such as accuracy, precision, and false acceptance rate. Experimental results demonstrate that the proposed system achieves an accuracy of 92% in optimal lighting but drops to 78% under low light conditions, highlighting the impact of illumination on recognition performance. The integration of adaptive preprocessing techniques improves reliability by 12% in challenging scenarios. This study concludes that while face recognition based attendance systems are highly effective, their reliability in diverse lighting conditions can be significantly enhanced through advanced preprocessing and robust algorithm design, offering practical implications for real time biometric applications in dynamic educational and workplace settings.
Co-Authors Abbas, Maulana Afiyanto, Rafid Anggy Giri Prawiyogi Anwar, Aang Solahudin Apriliasari, Dwi Astriyani, Erna Astuti, Eka Dian Bennet, Daniel Bist, Ankur Singh Cesna, Galih Putra Danang, Danang Danny Manongga Desy Apriani Dwi Andayani, Dwi Eko Sediyono Elmanda, Vonda Farail, Maulana Faqih Faturahman, Adam Fitra Putri Oganda Fitriani, Anandha Friandi, Sendy Zul Harahap, Eka Purnama Irwan Sembiring Juniar, Hega Lutfilah Juniar Kamal, Abdullah Arif Khoirunisa, Alfiah Kumoro, Dwi Ferdiyatmoko Cahya Marviola Hardini Maulana, Sabda Millah, Shofiyul Muhammad Iqbal Mulyati Mustofa Kamil, Mustofa Mustofa, Kenny Ilyas Natalia, Elisa Ananda Ninda Lutfiani Nur Azizah Nurhaeni, Tuti Nurmala, Risma Pangaribuan, Kelvin Po Abas Sunarya Qurotul Aini Rangi, Noah Ratri, Sanda Ramadhan Rawat, Bhupesh Rizki Galang Rahmadani Ruli Supriati, Ruli Salam, Rahmat Sandy Kosasi siti Nurindah Sari Siti Ria Zuliana, Siti Ria Sri Yulianto Joko Prasetyo Sulistiawati Sulistiawati Suryari Purnama Sutisna, Felix Tangkaw, Melani Rapina Untung Rahardja Vaher, Kristina Wahid, Syahrul Mu'Arif Xolani, Zanele