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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknologi dan Bisnis Cerdas
Sattar, Usman
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Environmental Science

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Explainable rice yield from Sentinel-1 and Sentinel-2 satellite data for food security Tribuana, Dhimas; Sattar, Usman; Mide, Baharuddin; Dayanti, Dayanti
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp615-627

Abstract

Reliable, explainable crop-yield estimates are essential for food-security planning in data-sparse regions. We present a transparent pipeline for district-level (regency) rice yield prediction in Indonesia that fuses Sentinel-1 synthetic aperture radar (SAR), Sentinel-2 normalized difference vegetation index (NDVI), and weather/reanalysis features. The system standardizes inputs per province, fixes a 16-day temporal key, and uses a small, auditable ensemble of tree models (gradient boosting+light gradient-boosting machine (LightGBM)). Trained on ≤2023 data and evaluated on a 2024 temporal hold-out, a joint West Java ∪ South Sulawesi model achieves root mean square error (RMSE)≈0.80 t/ha, mean absolute error (MAE)≈0.48 t/ha, and R-squared (R²)≈0.33 at regency scale. Feature importances and Shapley additive explanations (SHAP) confirm that phenology (NDVI peak, integral, green-up/senescence), SAR backscatter (vertical transmit-vertical receive/vertical transmit-horizontal receive (VV/VH)), and wind/pressure are consistent drivers under monsoon conditions. The workflow supports routine, one-click provincial updates and produces parity maps and error bars for actionable diagnostics. These results demonstrate that combining Sentinel-1, Sentinel-2, and basic meteorology delivers accurate, interpretable, and operational yield signals suited to Indonesia’s food security needs, while providing a clear recipe for scaling to additional provinces.
Employee Wellbeing dan Kinerja Pegawai Berkelanjutan: Peran Mediasi Work Engagement Amin Noor, Herlina; Rusli, Muh.; Komara, Nandang; Sattar, Usman; Safira Rospitasari Harun Sally, Jihan; Lestari, Sulfaedah; Syahrul, Syahrul
Jurnal Teknologi dan Bisnis Cerdas Vol 1 No 3 (2025): Volume 1 Nomor 3 (Desember 2025)
Publisher : Plexi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64476/jtbc.v1i3.66

Abstract

Changes in work patterns and increasing performance demands require organizations to focus not only on targets but also on employees’ psychological conditions that support long-term performance. This study aims to examine the effect of employee wellbeing on employee performance, with employee engagement as a mediating variable. A quantitative approach with an explanatory research design was employed. Data were collected through questionnaires from 150 employees and analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). The results indicate that employee wellbeing has a positive effect on employee engagement and employee performance. Employee engagement also has a positive effect on employee performance. Furthermore, employee engagement partially mediates the relationship between employee wellbeing and employee performance. These findings highlight that employee wellbeing influences performance not only directly but also indirectly through enhanced work engagement as a key psychological mechanism. This study suggests that sustainable performance improvement strategies should emphasize the integrated management of employee wellbeing and engagement.
Co-Authors Amin Noor, Herlina Dayanti, Dayanti Dhimas Tribuana Komara, Nandang Lestari, Sulfaedah Mide, Baharuddin Muh. Rusli Safira Rospitasari Harun Sally, Jihan Syahrul Syahrul