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Journal : Journal of Computer Science Artificial Intelligence and Communications

A Narrative Exploring the Potential of ChatGPT: How AI Models Are Changing the Way We Interact with Technology Eka, Muhammad; Asih, Munjiat Setiani; Damayanti, Fera; Saragih, Rusmin; Supiyandi, Supiyandi
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 1 (2024): May 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i1.5

Abstract

This study explores the perceptions, attitudes, and ethical considerations surrounding the use of ChatGPT among university students. By combining quantitative and qualitative research methods, including surveys and a review of existing literature, the study examines how ChatGPT is utilized in academic settings and its impact on learning outcomes, academic integrity, and scholarly achievements. The findings suggest that ChatGPT significantly enhances students' productivity, learning experiences, and writing abilities. However, concerns regarding its potential misuse, particularly about academic integrity, plagiarism, and over-reliance on AI tools, were also identified. The research highlights the importance of establishing clear ethical guidelines and policies to regulate the use of AI in educational settings. Future research should focus on the long-term effects of ChatGPT on students' academic development and investigate strategies for promoting responsible AI usage in higher education.
Identification of Book Cover Titles Using the Natural Language Processing (NLP) Method Gultom, Rianti Afifah; Setiani Asih, Munjiat; Zulkarnain Hasibuan, Ade
Journal of Computer Science, Artificial Intelligence and Communications Vol 2 No 2 (2025): November 2025
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v2i2.54

Abstract

In the digital era, the identification of book titles on covers has become a crucial requirement in digital library management, archiving systems, and book e-commerce platforms. The main challenges lie in the limitations of manual methods and traditional pattern-matching techniques, which are inefficient, as well as in the complexity of processing the Indonesian language, which exhibits diverse morphological variations and syntactic structures. To address these issues, this study proposes the integration of Optical Character Recognition (OCR) with the Natural Language Processing (NLP) method. OCR is utilized to extract textual information from book cover images, while NLP is applied to recognize and classify the extracted text to identify the main book title. The implementation results demonstrate that this approach significantly improves title identification accuracy compared to traditional methods, particularly through the application of Named Entity Recognition (NER) techniques and modern NLP models such as BERT and LSTM. The developed system proves effective in accelerating the book digitalization process, enhancing information management efficiency, and contributing to the advancement of Indonesian language processing technology.