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All Journal Jurnal Teknik Informatika (JUTIF) Lensa: Jurnal Kependidikan Fisika
Grendis, Nuraqilla Waidha Bintang
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Astronomy Chemistry Computer Science & IT Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Physics

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Utilizing AI for Physics Problem Solving: A Literature Review and ChatGPT Experience Mustofa, Hisbulloh Als; Bilad, Muhammad Roil; Grendis, Nuraqilla Waidha Bintang
Lensa: Jurnal Kependidikan Fisika Vol 12, No 1: June 2024
Publisher : Universitas Pendidikan Mandalika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/j-lkf.v12i1.11748

Abstract

The integration of artificial intelligence (AI) tools in physics education is gaining traction, driven by their potential to enhance learning experiences and outcomes. This study aims to investigate the use of AI tools, particularly ChatGPT, in solving physics problems and enhancing educational practices. Utilizing a systematic literature review following PRISMA guidelines, the research identifies current trends and practical applications of AI in physics education. The results indicate that AI tools effectively support lesson planning, introduce innovative teaching methodologies, and assist in solving complex physics problems, significantly enhancing problem-solving skills and personalized learning experiences. However, challenges such as inaccuracies in handling advanced content, the lack of useful visual aids, and the need for human intervention to ensure the completeness and accuracy of AI-generated content were noted. Personal experiences, supplemented by an interview with a thermodynamics lecturer, revealed that while ChatGPT can simplify complex concepts and improve comprehension, it could not replace the mentorship and nuanced feedback provided by human educators. The study concludes with recommendations for integrating AI tools into physics education, emphasizing the need for balanced integration with traditional teaching methods, improved AI literacy among educators and students, and future developments focusing on personalized learning and enhanced visualization capabilities. The findings demonstrate the transformative potential of AI in physics education and highlight the importance of addressing its limitations to maximize educational outcomes.
IMPROVING SHOPPING EXPERIENCES AT NTB MALL THROUGH PERSONALIZED PRODUCT RECOMMENDATIONS USING CONTENT-BASED FILTERING Husodo, Ario Yudo; Bimantoro, Fitri; Agitha, Nadiyasari; Grendis, Nuraqilla Waidha Bintang
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.4194

Abstract

NTB MALL, an e-commerce platform specializing in unique products from micro, small, and medium enterprises (MSMEs) in West Nusa Tenggara, faces challenges in providing personalized product recommendations due to the diversity of its product categories and consumer preferences. To address this, this study implements a content-based filtering (CBF) approach utilizing Term Frequency-Inverse Document Frequency (TF-IDF) and cosine similarity to enhance recommendation accuracy. The system analyzes product attributes and user interaction history to generate tailored suggestions. Experimental results indicate that cosine similarity outperforms Euclidean distance in recommendation precision, achieving an accuracy of 89% and a Mean Reciprocal Rank (MRR) of 95%. Furthermore, user feedback reveals that 93% of users found the recommendations highly relevant, 89% reported increased engagement, and 96% expressed satisfaction with the personalized shopping experience. This research provides a novel application of AI-driven recommendation systems in regional e-commerce marketplaces, demonstrating their potential to improve user experience and foster stronger connections between consumers and local producers.
Utilizing AI for Physics Problem Solving: A Literature Review and ChatGPT Experience Mustofa, Hisbulloh Als; Bilad, Muhammad Roil; Grendis, Nuraqilla Waidha Bintang
Lensa: Jurnal Kependidikan Fisika Vol. 12 No. 1: June 2024
Publisher : Universitas Pendidikan Mandalika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/j-lkf.v12i1.11748

Abstract

The integration of artificial intelligence (AI) tools in physics education is gaining traction, driven by their potential to enhance learning experiences and outcomes. This study aims to investigate the use of AI tools, particularly ChatGPT, in solving physics problems and enhancing educational practices. Utilizing a systematic literature review following PRISMA guidelines, the research identifies current trends and practical applications of AI in physics education. The results indicate that AI tools effectively support lesson planning, introduce innovative teaching methodologies, and assist in solving complex physics problems, significantly enhancing problem-solving skills and personalized learning experiences. However, challenges such as inaccuracies in handling advanced content, the lack of useful visual aids, and the need for human intervention to ensure the completeness and accuracy of AI-generated content were noted. Personal experiences, supplemented by an interview with a thermodynamics lecturer, revealed that while ChatGPT can simplify complex concepts and improve comprehension, it could not replace the mentorship and nuanced feedback provided by human educators. The study concludes with recommendations for integrating AI tools into physics education, emphasizing the need for balanced integration with traditional teaching methods, improved AI literacy among educators and students, and future developments focusing on personalized learning and enhanced visualization capabilities. The findings demonstrate the transformative potential of AI in physics education and highlight the importance of addressing its limitations to maximize educational outcomes.
Co-Authors Agitha, Nadiyasari Ario Yudo Husodo, Ario Yudo Bilad, Muhammad Roil Fitri Bimantoro Mustofa, Hisbulloh Als