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Dwi Agus Kurniawan
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Jurnal Ilmiah Ilmu Terapan Universitas Jambi
Published by Universitas Jambi
ISSN : 25802240     EISSN : 25802259     DOI : https://doi.org/10.22437/jiituj.v6i2
Core Subject : Education, Engineering,
Education Engineering Industrial & Manufacturing Engineering
JIITUJ publish the result of research on applied science and education (Research of applied science and education) such as: the research result on applied science and education such as curriculum development and learning, character education, technology and instructional innovation, and learning evaluation. the research result on applied science and technology such as the development of applied technology and applied arts, appropriate technology, designing information systems, the research result on applied science and economic development the research result on applied science and public health. JIITUJ is a double-blind peer-reviewed journal, published three (3) times a year by Research Institutions and Community Service (LPPM), Universitas Jambi, Indonesia. JIITUJ is open to academic circles and university researchers, research institutes, librarians, graduate and postgraduate students to share information on research results.
Arjuna Subject : Kimia(semua kategori) - Kimia (Lain-Lain)
Articles 392 Documents
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SUSTAINABLE COFFEE PRODUCTION: THE EFFECT OF SOCIAL NORMS, TRUSTS AND NETWORKS ON COFFEE FARMERS’ADOPTION BEHAVIOR IN LAMPUNG PROVINCE, INDONESIA Ali, Suprihatin; Wulandari, Christine; Endaryanto, Teguh; Budiono, Pitojo; Tugiono, Tugiono
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 10 No. 2 (2026): Volume 10, Nomor 2, April 2026
Publisher : LPPM Universitas Jambi

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Abstract

Sustainable coffee production is critical for ecological balance and livelihood resilience, yet adoption rates among smallholders remain variable. Although social capital is acknowledged as a key driver of agricultural sustainability, the distinct impacts of its constituent dimensions, norms, networks, and trust are insufficiently understood. This study aims to elucidate the differential influence of these social capital dimensions on sustainable production behavior among coffee farmers in Lampung Province, Indonesia. Employing a cross-sectional, quantitative, explanatory design, data were collected via structured surveys from 250 coffee farmers selected through purposive sampling over a two-month period. Measurement instruments adapted from established scales underwent rigorous validation. The structural model was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with bootstrapping to ensure robustness. Findings demonstrate that social norms and social networks exert significant positive effects on farmers' adoption of sustainable coffee practices. Conversely, social trust exhibits no direct statistical influence on behavior. The structural model explains a substantial proportion of behavioral variance and demonstrates adequate predictive relevance. This research offers a novelty empirical disentangling of the multidimensional nature of social capital in agricultural contexts, challenging the prevailing assumption that all dimensions uniformly drive sustainability outcomes. Theoretically, it advances social capital literature by validating dimension-specific effects within agrarian settings. Practically, implications suggest that extension programs and policymakers should prioritize norm activation through respected community figures and strengthen peer-to-peer knowledge exchange networks. These levers prove more effective for behavioral change than generalized trust-building alone.
INTEGRATING AN LLM-BASED CYBERSECURITY CONSULTATION LAYER INTO A NATIONAL AWARENESS BENCHMARKING SYSTEM Hadiprakoso, Raden Budiarto; Dramaga, Rakhmat; Qomariasih, Nurul
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 10 No. 2 (2026): Volume 10, Nomor 2, April 2026
Publisher : LPPM Universitas Jambi

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Abstract

This study integrates a large language model (LLM) consultation service into Indonesia’s national Cyber Security Awareness Survey (“Survei Kesadaran Keamanan Siber”/SKKS) to convert survey benchmarking into immediate, personalized cybersecurity remediation and evaluate its safety, usability, and potential short-term proximal intention shift among Generation Z respondents. Using a two-phase, multi-method design, Phase I conducted a model-centric expert evaluation of LLM-generated recommendations across 20 standardized synthetic SKKS profiles, assessing relevance, accuracy, completeness, clarity, and safety. Phase II implemented a single-session within- subject study (N = 104) that measured post-interaction user experience and pre–post changes in security behavior intentions using an adapted Security Behavior Intentions Scale (SeBIS). Expert results showed consistently high ratings across dimensions (all means > 4.0/5) with no safety veto triggers and strong inter-rater reliability (ICC[2,k] = 0.82–1.00). Users reported a positive experience (means ≈ 3.84–3.96/5), sustained engagement, and a significant increase in SeBIS total score (dz = 0.42), with the largest gains in password-management intentions. Novelty lies in embedding LLM-based, profile-driven consultation within a national-scale awareness survey and validating it through both expert human review and behavioral-intention measurement. Beyond cybersecurity, this work contributes to the broader literature on AI- mediated educational systems in safety-critical domains by demonstrating how adaptive dialogue systems can operationalize assessment-to-action loops and support scalable, human-centered personalization.

Page 40 of 40 | Total Record : 392

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