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Affective Drivers and Ethical Concerns Shaping AI Use Among University Students Nabilah Auliah Rahman; Melda Auliyah Zakina; Aprilianti Nirmala S; Saipul Abbas
Journal of Applied Artificial Intelligence in Education Vol 1, No 2 (2026): January 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/jaaie.v1i2.6

Abstract

The rapid growth of artificial intelligence (AI) use in higher education raises concerns about how students’ emotional states and the quality of their interactions with AI shape both affective engagement and ethical awareness in academic contexts. This study aims to examine the effects of emotional well-being, AI credibility, and AI interaction quality on students’ ethical awareness, with affective engagement positioned as a mediating mechanism. A quantitative cross-sectional survey was administered to higher education students who use AI tools for academic activities, and the proposed relationships were tested using PLS-based structural modeling with bootstrapping procedures. The findings indicate that emotional well-being (β = 0.549, p < 0.001) and AI interaction quality (β = 0.420, p < 0.001) significantly enhance affective engagement, whereas AI credibility shows no significant effect (β = –0.045, p = 0.342). Affective engagement has a significant positive influence on ethical awareness (β = 0.597, p < 0.001) and significantly mediates the effects of emotional well-being and interaction quality on ethical awareness, while no indirect effect is observed for AI credibility. Overall, these results imply that ethical awareness in student AI use is fostered more strongly through emotionally supportive experiences and high-quality human–AI interactions than through credibility perceptions alone, underscoring the need for human-centered AI integration and ethics-oriented guidance in higher education
Molecular identification of fungi and the types of toxins produced from contaminated corn grain in Satui, Tanah Bumbu, South Kalimantan, Indonesia Salamiah Salamiah; Mariana Mariana; Yusriadi Marsuni; Muhammad Pramudi Indar; Muslimin Sepe; Lyswiana Aphrodyanti; Saipul Abbas
Jurnal Hama dan Penyakit Tumbuhan Tropika Vol. 25 No. 2 (2025): SEPTEMBER, JURNAL HAMA DAN PENYAKIT TUMBUHAN TROPIKA: JOURNAL OF TROPICAL PLAN
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jhptt.225337-349

Abstract

Fungal contamination in stored corn grain not only reduces grain quality but alsoposes risks to animal and human health due to mycotoxin production. This study highlights the importance of early detection and identification of fungal pathogens in corn as a key aspect of plant protection and postharvest management, as well as the need to determine the types and concentrations of toxins produced. Corn samples were collected from a storage warehouse in Satui Village, Kota Baru Regency, South Kalimantan. Fungal isolation was conducted at the Phytopathology Laboratory, Department of Plant Pests and Diseases, Faculty of Agriculture, Universitas Lambung Mangkurat. PCR analysis and gene sequencing were performed at the Genetics Sciences Laboratory, Jakarta, while toxin type and content analyses were carried out at the Animal Husbandry Laboratory, Universitas Gadjah Mada, Yogyakarta. From 11 microbial isolates obtained from corn grain, only one fungal species was identified, namely Aspergillus flavus. This species was found to produce 8.00 ppb of aflatoxin, which remains below the established safety thresholds of 15 ppb for B1 and 20 ppb for total aflatoxins.