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Advance Sustainable Science, Environmental Engineering and Technology (ASSET) Jl. Sidodadi Timur No.24, Karangtempel, Kec. Semarang Tim., Kota Semarang, Jawa Tengah 50232
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Advance Sustainable Science, Engineering and Technology (ASSET)
Published by Universitas PGRI Semarang
ISSN : -     EISSN : 27154211     DOI : https://doi.org/10.26877/asset
Core Subject : Science, Engineering,
Chemistry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering
Advance Sustainable Science, Engineering and Technology (ASSET) is a peer-reviewed open-access international scientific journal dedicated to the latest advancements in sciences, applied sciences and engineering, as well as relating sustainable technology. This journal aims to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in different areas of sciences, engineering, and technology. The Scope of ASSET Journal is: Biology and Application Chemistry and Application Mechanical Engineering Physics and Application Information Technology Electrical Engineering Mathematics Pharmacy Statistics
Arjuna Subject : Teknik Kimia (semua kategori) - Teknik Kimia (Lain-Lain)
Articles 409 Documents
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Design and Evaluation of a BERT- and T5-Based Automated Essay Scoring and Feedback Framework Hendi Triatmoko; Sani Muhamad Isa
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.2924

Abstract

Manual essay assessment is often time-consuming, subjective, and difficult to implement consistently in large-scale educational settings. Therefore, this study aims to develop and evaluate an integrated AES framework that combines essay scoring, spelling error detection, semantic relevance analysis, and automated feedback generation. The proposed framework integrates BERT for essay score prediction, pyspellchecker for spelling error detection, SBERT for semantic relevance analysis, and T5 for automated feedback generation. Experiments were conducted using a publicly available dataset consisting of 1,785 essays for model development and 592 essays for testing. The BERT model achieved strong predictive performance with an MAE of 0.2381, RMSE of 0.2847, and R² of 0.9513 on the test dataset, indicating high agreement with human scoring. The spelling detection module successfully identified linguistic errors, while the SBERT model produced relevance scores ranging from 0.58 to 0.95. The T5 model generated feedback that was consistent with essay scores, spelling quality, and semantic relevance. These findings demonstrate that integrating multiple NLP components can extend AES functionality beyond score prediction by providing comprehensive writing evaluation and formative feedback. Practically, the proposed framework supports scalable essay assessment and automated feedback generation. However, its generalizability is limited on a single-topic dataset and synthetic feedback data.
Toward Durable Prosthetic Feet: Mechanical and Tribological Evaluation of Polyurethane Elastomers Muhammad Khafidh; Putra Bagas Veryanto; Donny Suryawan; Rifky Ismail; Alfiana Fitri Istiqomah; Budi Setiyana; Deni Fajar Fitriyana; Jayatin
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.2981

Abstract

Elastomeric materials play a crucial role in determining the durability, comfort, and service life of prosthetic feet. Although various elastomers have been explored for this application, systematic evaluation of polyurethane formulations that integrate mechanical and tribological performance remains limited. This study investigates two types of polyurethane elastomers (A70 and A80) with different polyol–isocyanate ratios to identify an optimal formulation for prosthetic foot applications. Mechanical properties were evaluated through tensile, tear, hardness, and density tests, while friction and wear behavior were assessed using a pin-on-disk tribometer. A commercial prosthetic foot elastomer available in the Indonesian market was used as a benchmark. The results show that A80-based formulations generally provide superior tensile and tear strength compared to A70 variants. Among all specimens, A80-3 exhibits the lowest wear volume and stable friction performance, while maintaining hardness comparable to the commercial product. Although its density remains higher than the benchmark, the improved wear resistance indicates potential for extended service life. These findings offer practical guidance for durability-oriented material selection in the development of cost-efficient prosthetic feet.
Electronic Structure–Property Relationships in Ketohexoses: Implications for Crystal Engineering and Functional Rare Sugar Materials Ryunosuke Takata; Tomoko Takashita; Mizuki Aoe; Kei Takeshita; Tomohiko Ishii
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.2990

Abstract

Rare sugars have garnered significant attention owing to their beneficial biological activities and their potential applications in sustainable materials, agriculture, and medicine. However, despite extensive crystallographic and hydrogen-bonding studies, the electronic factors governing their molecular stability and crystal packing are still not fully understood. In this study, the DV-Xα molecular orbital method was employed  to systematically analyze intramolecular charge distribution in ketohexoses, comparing D-chiral and D,L-racemic forms. The results reveal a clear distinction between two types of electronic behavior: (i) electronically stable sites (C2 and C5), where charge variation remains minimal (typically < 1 %), and (ii) adaptive sites (C3, C4, and C6), where charge distribution exhibits significant responsiveness to molecular environment. This finding provides a new electronic-structure-based framework that explains how localized charge stability and flexibility cooperatively govern crystal packing and intermolecular interactions, particularly hydrogen bonding. Even subtle variations in charge (< 1 %) were found to be chemically meaningful, as they systematically influence interaction patterns across different ketohexoses. These insights go beyond conventional structural analyses by establishing a direct link between intramolecular electronic structure and macroscopic material behavior. The present approach offers a foundation for rational design and functionalization of rare sugars in applications such as crystal engineering, pharmaceuticals, and sustainable agrochemical materials.
Electronic Structure–Driven Hydrogen-Bond Site Selectivity in Ketohexose Crystals: DV-Xα Calculations and Full Interaction Maps Mizuki Aoe; Tomoko Takasita; Ryunosuke Takata; Kei Takeshita; Tomohiko Ishii
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.2994

Abstract

Rare sugars are monosaccharides and their derivatives that are found in very small amounts in nature. Single crystals of sugars selectively adopt specific hydrogen-bonding motifs from the vast number of possible patterns derived from their molecular structures. However, the principles governing this selection remain unresolved crystallography. In this study, we investigate the origin of site selectivity in ketohexose crystals using molecular orbital calculations (DV-Xα method) combined with Full Interaction Maps (FIMs) analysis. Bond overlap population values (~10⁻²) were used to quantify hydrogen-bond strength. The results show that dominant hydrogen-bonding sites are consistently identified as O2 in fructose- and allulose-type compounds, O3 in sorbose-type compounds, O3–O4 in D-tagatose, and O2–O5 in 1-deoxy-D-tagatose. These sites correspond to regions predicted by FIMs as favorable for hydrogen bonding.　These findings demonstrate that hydrogen-bond site selectivity is governed by intrinsic electronic structure and provide a framework for predicting intermolecular interactions in molecular crystals.
AHP–TOPSIS–PROMETHEE Hybrid Decision Support Framework for Sustainable Pharmaceutical Cold Chain Vendor Selection Marthaleina Ruminda Sitorus; Edhie Budi Setiawan; Sekar Widyastuti Pratiwi; Apsada Juhri
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.3041

Abstract

Selecting pharmaceutical suppliers is a crucial process to ensure effective procurement, availability of medicines, compliance with regulations, and sustainable operation of the distribution system. This study proposes a combined Multicriteria Decision Support System (DSS) to prioritize vendors in pharmaceutical cold chain logistics. This study uses Likert AHP, TOPSIS, and PROMETHEE with 5 vendors, 4 characteristics of which are Price, Capacity, Service, and Time, supported by 20 supporting sub-characteristics. There are 10 experts related to procurement and logistics, accompanied by original operational performance data from the institution. AHP analysis shows that delivery time has an importance level of 0.534, while price is 0.200, Capacity is 0.161, and service is 0.105. In the consistency test with Hamming, Euclidean, and Spearman similarities, accompanied by sensitivity tests for each variable. The results obtained by vendor V obtained a high position with AHP and PROMETHEE, while continued with TOPSIS which is on two paths in each path. However, other vendors showed slightly different results, with Euclidean having an average of 59%. The results shown are those that have static changes due to various expert opinions. Thus, a more transparent framework is provided.
Interpretation of Geophysical Well Logging and the Relationship between the Density Log and the Calorific Value of Coal Martadi; Setyo Pambudi; Okki Verdiansyah
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.3592

Abstract

Geophysical well logging is widely used in coal exploration to characterize subsurface lithology and coal seams; however, its application for rapid coal quality prediction remains limited in operational mining workflows. This study investigates the quantitative relationship between density log measurements and coal calorific value to develop a predictive approach for coal quality assessment based on geophysical logging data in the Lati and Labanan Formations within the Berau Sub Basin, which is part of the Tarakan Basin. The research uses geophysical well-logging data from 113 exploration boreholes. Bivariate geostatistical analysis and linear regression were applied to evaluate the correlation between density log values and calorific value (air-dried basis). The results show a strong positive relationship between coal density and calorific value, with coefficients of determination ranging from 0.90 to 0.98. These findings indicate that the density log measurements can serve as a reliable proxy for estimating coal energy quality. The proposed relationship model demonstrates the potential of geophysical logging data to support faster coal quality prediction. This approach contributes to the development of data-driven coal quality assessment methods that can complement laboratory testing within integrated digital mining workflows.
Smart Urban Road Management: Application of Artificial Neural Networks for Predictive Modeling of the International Roughness Index Yogi Oktopianto; Antonius Antonius; Abdul Rochim
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.3703

Abstract

Road condition assessment is an important indicator within the infrastructure maintenance management system. The International Roughness Index (IRI) is a standard service instrument used in various countries to evaluate road surface roughness. However, assessing road conditions using IRI faces several challenges, including the need for expensive equipment, long operational time and cost, limited coverage, and the fact that it only represents surface roughness, thereby requiring additional surveys to identify pavement distress types directly. The objective of this study is to develop an IRI prediction model based on the Surface Distress Index (SDI) parameters to optimize the efficiency of road condition assessment by using Artificial Neural Networks (ANN) to enhance road maintenance planning. This model was trained on five years of road-damage data across 42 urban road segments. The coefficient of determination from the study findings indicates excellent prediction accuracy, with an R2 value of 0.93, a Mean Absolute Error (MAE) of 0.73, and a Root Mean Square Error (RMSE) of 1.07. This model can serve as a more dynamic strategy for urban road maintenance management in developing countries facing resource limitations. The proposed framework offers an innovative and adaptive solution to issues in road maintenance management and provides support for more sustainable urban infrastructure management.
RSM Optimization of Used Engine Oil Recovery Using Coal-Based Activated Carbon in a Pyrolysis–Distillation Unit Alwathan; Muh. Irwan; Ramli Thahir; Sirajuddin; Siti Hamidah
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.3705

Abstract

Recovery of hydrocarbon compounds from waste lubricating oil has gained considerable attention because of its potential as an alternative liquid fuel source and its contribution to environmental protection. Besides containing valuable hydrocarbons, waste lubricating oil also contains sulfur compounds and heavy metals that may reduce fuel quality and cause environmental pollution. This study evaluates the recovery of waste lubricating oil through a pyrolysis–distillation process assisted by activated carbon derived from low-rank coal from East Kalimantan, Indonesia. The activated carbon was synthesized through carbonization and chemical activation and characterized using iodine number analysis to determine its adsorption capability. Response Surface Methodology (RSM) was applied to optimize pyrolysis temperature and activated carbon dosage in order to maximize liquid yield and contaminant removal efficiency. The synthesized activated carbon exhibited an iodine number of 1163.51 mg/g. Optimization predicted optimum conditions at 416.54 °C and 12.87 wt.% activated carbon dosage, producing 89.67% liquid yield and approximately 76% contaminant removal efficiency. Experimental validation confirmed the model prediction, resulting in 88% liquid yield with satisfactory fuel characteristics. 
Effect of Dimple Topology and Ball Mass on the Aerodynamic and Flight Performance of Golf Balls Agus Baharudin; Yao-Hsuan Tsai; Chen-Hsiang Chen; Dwi Sudarno Putra; Wawan Purwanto; M. Yasep Setiawan; Ahmad Arif
Advance Sustainable Science Engineering and Technology Vol. 8 No. 4 (2026): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i4.3707

Abstract

The flight performance of a golf ball is governed by its surface geometry, which controls boundary-layer transition, separation and wake formation, yet the effects of convex surface topology and of ball mass remain underexplored. This study experimentally compares three surface patterns of identical diameter and feature count: conventional circular dimples (baseline), hexagonal dimples and circular convex protrusions. Wake fields were characterised in a closed-loop water tunnel by Particle Image Velocimetry (PIV) and dye visualisation at Re = 1.5×10³ - 6.7×10³, and drag and lift were measured in a wind tunnel at Re = 2.9×10⁴ - 1.12×10⁵ with a combined uncertainty analysis. Over Re = 5.8×10⁴–1.1×10⁵ the baseline has the lowest drag at every test point, the convex and hexagonal patterns exceeding it by 5.8 ± 0.9 % and 5.1 ± 1.0 % on average, while the convex ball shows a pronounced negative-lift regime at intermediate Re. The measured CD(Re) and CL(Re) were applied to a two-dimensional, no-spin trajectory model with Monte Carlo uncertainty propagation at the regulation mass (45.93 g) and at 190 g. At regulation mass the ball decelerates into the negative-lift regime of the convex pattern, and the baseline carries 3.6 - 6.0 m farther than the convex ball for launch angles of 15.7° - 46.8°; at 190 g the ball remains above this regime and the two patterns become indistinguishable at a shallow launch angle. This Reynolds-number-mediated pattern–mass coupling provides a fluid-mechanical rationale for the dominance of circular dimples on regulation balls.

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