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Abdul Hafid Hasim
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International Journal of Environment, Engineering, and Education
Published by Three E Science Institute
ISSN : -     EISSN : 26568039     DOI : https://doi.org/10.55151/ijeedu
Core Subject : Science, Education, Social, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Electrical & Electronics Engineering Engineering Environmental Science
The International Journal of Environment, Engineering, and Education [e-ISSN: 2656-8039] is a peer-reviewed, open-access journal that is published three times a year [in April, August, and December]; this journal provides the right platform for authors to update their knowledge, information, and share their research results with the more significant scientific community publishing research articles explaining the ecological, technical, and educational impact of research from various disciplines publishing research articles explaining the environmental, technical, and educational implications of research from multiple disciplines publishing research As an interdisciplinary scientific publication, this journal encourages collaboration between researchers, academics, practitioners, and policymakers in various sectors to develop sustainable solutions to address environmental, engineering, and educational problems and promote sustainable development.
Arjuna Subject : Umum - Umum
Articles 127 Documents
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Map-Derived Agreement Assessment of Landsat-9 OLI-2 for Island-Scale Lithological Discrimination in a Humid Tropical Setting from Langkawi Island, Malaysia Yaokai Du; Ying Jia Teoh; Nur Azwin Ismail; Ismail Ahmad Abir; Haylay Tsegab Gebretsadik
International Journal of Environment, Engineering and Education Vol. 8 No. 2 (2026)
Publisher : Three E Science Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55151/ijeedu.v8i2.512

Abstract

Lithological discrimination in humid tropical islands remains constrained by dense vegetation, deep weathering, regolith cover, mixed pixels, and discontinuous bedrock exposure, which collectively weaken diagnostic spectral responses. This study evaluates the capability and limitations of Landsat-9 OLI-2 for island-scale lithological discrimination in Langkawi Island, Malaysia, using an interpretable optical-only workflow. Atmospherically corrected Landsat-9 imagery was processed through false-color composites, Optimum Index Factor (OIF)-based band selection, band-ratio enhancement, Principal Component Analysis (PCA), Normalized Difference Vegetation Index (NDVI), Jeffries–Matusita separability analysis, and Maximum Likelihood Classification (MLC). The resulting MLC lithological map was assessed pixel-by-pixel against a published geological map; consequently, the reported statistics represent map-derived agreement rather than independent field-validated lithological accuracy. Results show that the OIF-selected RGB 6-5-2 composite, selected band-ratio combinations, and PCA enhanced broad contrasts among Quaternary Alluvium, granitic terrain, and carbonate-bearing formations. The MLC classification achieved an overall map-derived agreement of 51.72% and a kappa coefficient of 0.4177. Qal, Cm-SS/Sh/Md, and OS-Ls/SS showed relatively stronger agreement, whereas PT-Ls/Mb, DP-St/Md, and Tr-Gr were more affected by spectral overlap and class confusion. NDVI-stratified assessment further confirmed that vegetation cover influences classification performance, with low-vegetation areas producing higher agreement than moderate-vegetation areas. This study establishes a reproducible full-island baseline for evaluating optical multispectral lithological mapping under humid tropical conditions. These findings demonstrate that Landsat-9 OLI-2 can support reconnaissance-level lithological discrimination in humid tropical islands but remains insufficient for precise formation-level mapping without field validation and integration with SAR, DEM-derived, or higher-resolution spectral datasets.
The Interplay of Soft Skills, Digital Literacy, and Self-Efficacy in Shaping Work Readiness: A Structural Equation Modeling Study of Vocational High School Students Anas Arfandi; Musdalifah Musdalifah; Sudjani Sudjani; Abdul Haris Setiawan
International Journal of Environment, Engineering and Education Vol. 8 No. 2 (2026)
Publisher : Three E Science Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55151/ijeedu.v8i2.418

Abstract

Work readiness in vocational education is increasingly shaped by transferable competencies and students’ confidence in applying them in technology-rich workplaces. Although soft skills and digital literacy are widely promoted, evidence remains limited in Indonesian VET contexts regarding how these competencies translate into work readiness through self-efficacy. This study tested a structural mediation model in which soft skills and digital literacy predict work readiness both directly and indirectly via self-efficacy among vocational students who participated in MOOC-based upskilling. A cross-sectional survey was administered to 225 students from the Construction and Housing Engineering program across 22 vocational high schools in 16 districts/cities in South Sulawesi, Indonesia. All constructs were measured using five-point Likert scales, and covariance-based SEM was estimated in AMOS using Maximum Likelihood. The model demonstrated excellent fit (CMIN/DF=1.248, RMSEA=0.001, SRMR=0.005, GFI=0.921, CFI=0.996, TLI=0.989, PNFI=0.762). Soft skills positively predicted self-efficacy (β=0.574; p<0.001) and work readiness (β=0.652, p<0.05), while digital literacy also predicted self-efficacy (β=0.274, p<0.05) and work readiness (β = 0.663, p<0.001). Self-efficacy exhibited the strongest direct effect on work readiness (β=0.778, p<0.05) and partially mediated the effects of soft skills (indirect β=0.447, p<0.05) and digital literacy (indirect β=0.213, p<0.001). Overall, these findings propose an integrated competency–belief model for Indonesian vocational students in a MOOC participation context, highlighting self-efficacy as a key mechanism through which competencies contribute to work readiness. This contribution extends SEM-based evidence on vocational competency development by underscoring the importance of confidence-building alongside skills and digital capability training.
Smart Composter for Experiential Learning in Sustainable Agriculture: System Design and Application for a Small-Scale Farm Setting Catherine Molloseau; Ira Woodring; Amy McFarland; Isak Davis; Yunju Lee
International Journal of Environment, Engineering and Education Vol. 8 No. 2 (2026)
Publisher : Three E Science Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55151/ijeedu.v8i2.486

Abstract

Composting offers a practical pathway for recycling organic waste, yet maintaining favorable process conditions and translating composting into structured experiential learning remain challenging. This study designed and conducted a preliminary field evaluation of an automated, sensor-enabled composting system intended to process vegetative waste from a small-scale farm while supporting sustainability education. The prototype combined an aerated static-pile configuration with forced aeration, humidity-triggered irrigation, three vertically distributed temperature and relative-humidity sensors, oxygen and fill-level monitoring, a touchscreen interface, transparent viewing panels, multiple access points, and remote data logging. A 29-day trial was conducted in an unheated tunnel greenhouse using approximately 1 m³ of vegetative waste and wood chips mixed at a reported 1:1 mass ratio. Sensor data were recorded at 10-minute intervals and analyzed descriptively to examine temporal patterns, vertical variation, system performance, and data completeness. Temperatures showed recurrent diurnal fluctuations and clear vertical stratification, reaching maximum values of 54.39°C, 45.83°C, and 35.67°C in the upper, middle, and lower zones, respectively. Lower-zone measurements were incomplete because of a connection failure, while middle-zone relative humidity remained near sensor saturation, limiting interpretation. The observed temperature increases, absence of malodor, and visible material changes were consistent with ongoing aerobic decomposition, although compost maturity and educational outcomes were not directly assessed. These findings demonstrate the feasibility of integrating monitoring, user interaction, visual access, and real-time data communication in a smart composter. Future work should validate sensor placement, quantify actuator performance, assess compost quality, and evaluate learning outcomes aligned with the United Nations Sustainable Development Goals.
The Persistence Architecture of E-Learning: Linking Quality, Acceptance, and Student Satisfaction Fitria Fitria; Muhammad Yahya; Muh. Ichsan Ali
International Journal of Environment, Engineering and Education Vol. 8 No. 3 (2026)
Publisher : Three E Science Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55151/ijeedu.v8i3.485

Abstract

E-learning sustainability depends on students’ post-adoption evaluations of platform performance, information quality, usefulness, satisfaction, and continued use. This study examines students’ continuance intention toward institutional e-learning systems by integrating the Technology Acceptance Model and the Information Systems Success Model. A quantitative explanatory survey was conducted with 470 students from five Indonesian universities. Data were analyzed using covariance-based structural equation modeling with IBM SPSS and AMOS. The final model showed excellent fit (CMIN/DF = 1.036, CFI = 0.999, TLI = 0.999, RMSEA = 0.009). The results reveal that information quality was the dominant driver of perceived usefulness (β = 0.824, p < 0.001) and also significantly improved perceived ease of use (β = 0.321, p < 0.001). User satisfaction strongly predicted continuance intention (β = 0.612, p < 0.001), while perceived usefulness substantially increased satisfaction (β = 0.475, p < 0.001). By contrast, system quality had only weak effects on perceived ease of use (β = 0.164) and perceived usefulness (β = 0.072), and perceived ease of use had a negligible effect on satisfaction (β = 0.019). These findings show that sustained e-learning use is shaped primarily by the quality and academic value of information rather than by technical functionality alone. The study refines TAM–ISSM integration by identifying a clear information quality–usefulness–satisfaction–continuance pathway in post-adoption settings. Universities should therefore prioritize relevant, accurate, well-organized, and timely learning content, while maintaining reliable system performance, to strengthen student satisfaction and long-term engagement.
Machine-Learning Classification of Archived Employability-Readiness Ratings: Performance, Calibration, and Internal Validation Tonglu Men; Premsuree Chaumthong
International Journal of Environment, Engineering and Education Vol. 8 No. 3 (2026)
Publisher : Three E Science Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55151/ijeedu.v8i3.503

Abstract

This study examined the explanatory structure and predictive reproducibility of an end-of-program administrative score used to assess graduate preparedness in vocational education. A cross-sectional secondary analysis was conducted using 450 de-identified learner records collected from four anonymized polytechnic-style institutions during the 2023–2024 academic year. The outcome was a 0–100 composite score analyzed continuously and as three prespecified categories: low (<60), moderate (60–79), and high (≥80). Candidate predictors comprised practical skills, digital competence, soft skills, internship intensity, project performance, and an industry–education integration index treated as an institution-linked contextual proxy. Pearson correlations, heteroskedasticity-consistent ordinary least-squares regression, criterion-overlap sensitivity analysis, and leakage-controlled model development were applied. Six algorithms were compared against a majority-class baseline using a stratified 70:30 development-test split. Bootstrap intervals, ordinal-error measures, and probability-calibration indices were used to quantify uncertainty and performance. The full regression model explained 76% of outcome variance (adjusted R² = 0.75), whereas the reduced model retained an adjusted R² of 0.58 after removal of predictors susceptible to shared rubric content. In the untouched test partition (n = 135), the back-propagation neural network achieved an accuracy of 0.904 and a macro-F1 of 0.903; all 13 errors occurred between adjacent categories. These findings indicate a coherent within-system scoring structure and strong reproducibility across analytical approaches. However, they do not establish causal effects, transportability across institutions, fairness, operational utility, or prediction of subsequent labor-market outcomes. The model should therefore be restricted to low-stakes auditing, data-quality review, and identification of borderline records pending prospective multi-institutional evaluation.
Educational Position and Moral–Civic Values among Tertiary-Educated Young Adults: A Bayesian Mundlak Analysis across 66 World Values Survey Samples Wenxin Zu; Jie Yang; Li Yin; Zhyldyz Takenova
International Journal of Environment, Engineering and Education Vol. 8 No. 3 (2026)
Publisher : Three E Science Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55151/ijeedu.v8i3.509

Abstract

Higher education institutions have a dual purpose: to educate and to socialise moral and civic citizens. While this mandate is widely acknowledged, empirical studies of value formation are often limited to single-case studies or use concepts that are difficult to compare across national contexts. In this study, we propose and test a data-based model of moral and civic value formation using the World Values Survey (WVS) Wave 7. A sample of 9,589 tertiary-educated individuals aged from 18 to 30 in 66 countries was used for the analyses. We used a systematic pre-processing protocol to recode WVS special missing categories, exclude completely missing variables, and build six theoretically-informed, normalized indicators of prosocial values, achievement-responsibility values, moral rejection, institutional trust, gender-equitable education values and social trust. These were then combined into a formative Moral-Civic Value Formation Index (MCVFI). HC3 robust standard error regression models were estimated at the individual level and with country fixed effects. The individual-level model identified education level (β = 0.099, p < 0.001), female gender (β = 0.046, p < 0.001), and family-religious socialization (β = 0.267, p < 0.001) as significant positive predictors. Country fixed effects substantially improved model fit, raising adjusted R² from 0.084 to 0.306. This confirms that moral and civic value formation is context-sensitive and embedded in wider cultural-national environments. The study contributes a reproducible, open-data framework for integrating cross-national public values data into educational research on civic and moral development.
Electrode-Level EEG Assessment of Sequential Taste and Packaging Exposure in Processed Foods: An Exploratory Study Harish Velingkar; Roopa R. Kulkarni; Prashant P. Patavardhan
International Journal of Environment, Engineering and Education Vol. 8 No. 3 (2026)
Publisher : Three E Science Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55151/ijeedu.v8i3.557

Abstract

This study examined whether sustained electrode-level neural signals differentiate successive stages of a commercial food encounter and whether response patterns vary by gender. Fifty adults (25 male, 25 female; 20–40 years) completed a fixed protocol comprising a composite baseline, post-ingestive viewing of a branded product while residual flavor remained, later viewing of the same product under a recall instruction, and viewing of an unrelated snack product. Signals were acquired from eight scalp channels using a portable system, filtered at 0.5–45 Hz, notch-filtered at 50 Hz, common-average referenced, and aggregated into participant-level mean device-native amplitudes. Electrode-specific 4 × 2 mixed-design repeated-measures ANOVAs tested Condition, Gender, and their interaction; Greenhouse–Geisser correction addressed sphericity violations, and Benjamini–Hochberg adjustment controlled the false discovery rate. Condition effects were significant at all eight electrodes (all q ≤ 0.028), with partial ηp² ranging from 0.073 at O1 to 0.523 at C3 and the largest effects at C3, C4, and F4. Baseline-to-post-ingestive viewing yielded the broadest adjusted paired differences. Neither the Gender main effect nor the Condition × Gender interaction remained significant after correction, while individual trajectories showed marked heterogeneity. Portable low-density recordings therefore detected sequence-associated sensor-level differentiation across the protocol. Because condition was confounded with serial position, the baseline combined eye states, package stimuli were unmatched, amplitudes were uncalibrated, and behavioral validation was absent, the findings do not establish causal effects of flavor, product identity, recall, preference, cortical source, or consumer choice. Randomized, counterbalanced, behaviorally validated, and higher-density replication is required.

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