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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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INDONESIA
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 272 Documents
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Bayesian Generalized Poisson Regression Modeling for Overdispersed Maternal Mortality Data Dewi Ratnasari Wijaya; Henny Pramoedyo; Ni Wayan Surya Wardhani
Advance Sustainable Science Engineering and Technology Vol. 7 No. 3 (2025): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i3.1928

Abstract

Maternal mortality is a global health issue that reflects disparities in access to and the quality of healthcare services. This study applies the Bayesian Generalized Poisson Regression (BGPR) approach to address the problem of overdispersion in the data, which renders the standard Poisson regression model less appropriate. The Generalized Poisson model was chosen for its ability to handle overdispersion, while the Bayesian approach provides more stable parameter estimates, particularly when working with small sample sizes. The analysis results show that all independent variables have a statistically significant effect on maternal mortality. In addition, the BGPR model yields a lower Bayesian Information Criterion (BIC) value compared to the standard Poisson model, indicating better model performance. The BGPR model helps identify the key factors that truly contribute to maternal mortality, making the results useful for local governments or health institutions in setting priorities for intervention.
Fuzzy Logic-Based Clustering of Teacher Digital Pedagogy Using Cybergogy Framework for Sustainable Educational Innovation Waryanto, Nur Hadi; Retnawati, Heri; Setyaningrum, Wahyu; Insani, Nur; Hery Murtianto, Yanuar; Caturiyati, Caturiyati; RR Rianto, Vivi
Advance Sustainable Science Engineering and Technology Vol. 7 No. 3 (2025): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i3.1946

Abstract

Rapid changes in educational technology necessitate innovative approaches to sustainable teacher development. However, implementing learning technologies like Cybergogy faces significant challenges due to imbalances in digital pedagogy competencies and motivation among secondary school mathematics teachers. This study aims to cluster mathematics teachers' profiles based on the Cybergogy model's application using the Fuzzy C-Means (FCM) algorithm. The study involved 88 mathematics teachers from various secondary schools in Yogyakarta, Indonesia. Clustering results converged at the sixth iteration with an objective function value of 620.006, and an optimal two-cluster structure (PCI = 0.5578). Cluster 1 comprises teachers with high digital competencies and effective use of online learning media in understanding Cybergogy. Conversely, Cluster 2 includes teachers with limited online learning experience and low Cybergogy understanding. These findings highlight the lack of appropriate training efforts to support technology implementation and motivate each cluster based on their unique perceptions of Cybergogy. This study contributes to educational technology by offering insights into how the Cybergogy model can enhance digital learning quality, with long-term implications for teacher competency development and the sustainability of digital education innovation in Indonesia.
Scenario-Based Dynamic Modeling for Urban Settlement Management Hidayat, Janthy Trilusianthy; Apriyanto, Heri
Advance Sustainable Science Engineering and Technology Vol. 7 No. 3 (2025): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i3.1953

Abstract

The growth of residential areas in peri-urban regions of metropolitan areas such as Jabodetabek demonstrates high complexity due to the dynamic interaction between population growth, land use, and environmental degradation. This study aims to develop a dynamic system-based simulation model using a scenario approach to analyze sustainable residential area management policies. The scenarios were developed consists of no intervention, pessimistic, moderate, and optimistic based on parameters such as local government commitment, regional capacity improvement, and the rate of incoming migration. The simulation results indicate that the optimistic scenario is the most effective in controlling population size (a reduction of 29.14%), limiting residential expansion (a 58.57% decrease in the settlement area ratio), and improving the quality of the physical environment (a 95.18% increase) by the year 2040. The findings recommend strengthening spatial planning policies through enhanced cross-sectoral coordination, vertical housing development, and migration control. Although the model has limitations due to its assumption of a fixed system and the exclusion of external dynamics, this research provides valuable insights for the development of dynamic system-based policies in the sustainable planning of complex metropolitan regions.
Assessing the Feasibility of Small-Scale RDF Technology in Urban Solid Waste Management Using Cost-Benefit Analysis Purwanto, Heru; Nurhasana, Renny; Rohimah, Azizah
Advance Sustainable Science Engineering and Technology Vol. 7 No. 3 (2025): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i3.1988

Abstract

The development of Waste Processing Facilities based on the 3R principles (TPS 3R) with small-scale Refuse Derived Fuel (RDF) technology in Jakarta aims to support waste sorting, composting, reuse, and recycling activities, with locations strategically placed as close as possible to service areas. However, its implementation faces significant challenges, particularly due to high initial investment and operational costs. This study evaluates the feasibility of four TPS 3R facilities using a Cost-Benefit Analysis approach, considering economic, environmental, and social dimensions. The results indicate that all units are economically viable, with TPS 3R Joe demonstrating the highest economic feasibility, marked by a BCR of 1.870, an NPV of IDR 25.81 billion (USD 1.60 million), and an IRR of 15.76%. The study concludes that the successful implementation of small-scale RDF technology is highly influenced by technical efficiency, institutional support, community participation, and policies that are adaptive to local characteristics.
Mechanical Performance of Alkali-Treated Rattan Strips with Epoxy Coating for Sustainable Composite Applications Kalatharan, Sujentheran Nair; Imran, Al Ichlas; Irawan, Agustinus Purna; Siregar, Januar Parlaungan; Cionita, Tezara; Fitriyana, Deni Fajar; Anis, Samsudin; Dewi, Rozanna; Setyoadi, Yuris; Wisnu Prayogo
Advance Sustainable Science Engineering and Technology Vol. 7 No. 3 (2025): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i3.2017

Abstract

The use of natural materials like rattan in eco-friendly composites is gaining attention in materials engineering. However, its hydrophilic nature and interaction with other materials can affect mechanical strength. This study investigates how variations in rattan size and alkali treatment influence the tensile properties of single rattan strips through an epoxy dipping process. Rattan was prepared with varying lengths (5–15 cm), widths (3–8 mm), and a consistent thickness (0.5 mm). Alkali treatment used 5% and 10% NaOH concentrations for 1 and 24 hours. Tensile testing showed that a 5 cm × 8 mm strip achieved the highest tensile strength (49.95 MPa), Young's modulus (3562.77 MPa), and low strain (5.4%), while the 15 cm × 3 mm strip had the lowest strength (9.48 MPa) and modulus (475.69 MPa) with higher strain (10.32%). A 5% NaOH treatment for 24 hours improved adhesion and performance, while 10% caused degradation.
Multi-Horizon Short-Term Residential Load Forecasting Using Decomposition-Based Linear Neural Network Henri Tantyoko; Satriawan Rasyid Purnama; Etna Vianita
Advance Sustainable Science Engineering and Technology Vol. 7 No. 3 (2025): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i3.2033

Abstract

Short-Term Load Forecasting is crucial for grid stability and real-time energy management, particularly in residential settings where consumption is highly volatile and influenced by behavioral and external factors. Traditional models struggle to capture complex, non-linear patterns. This study proposes a forecasting framework based on the DLinear model, which decomposes time series data into trend and seasonal components using a simple linear neural network architecture. Designed for multi-horizon forecasting, the model predicts electricity demand across several future time points simultaneously. Experimental results show that DLinear performs best at a 24-hour prediction length, achieving the lowest MSE of 41.58 and MAE of 5.11, indicating improved accuracy with longer horizons. These results confirm DLinear’s robustness and efficiency in modeling dynamic residential electricity consumption patterns.
Comparative Performance of GLMM and GEE for Longitudinal Beta Regression in Economic Inequality Modelling Sihombing, Pardomuan Robinson; Erfiani; Khairil Anwar Notodiputro; Anang Kurnia
Advance Sustainable Science Engineering and Technology Vol. 7 No. 3 (2025): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i3.2057

Abstract

Due to the shortcomings of conventional Gaussian methods, specialized models are frequently needed for longitudinal data analysis with bounded outcomes, such as the Gini ratio. In order to model economic inequality in Indonesia, this study compares the effectiveness of Generalized Linear Mixed Models (GLMM) and Generalized Estimating Equations (GEE) for beta-distributed longitudinal data. Root Mean Square Error (RMSE) and pseudo R-squared values are used to assess model performance using panel data from 10 provinces between 2018 and 2024 as well as important socioeconomic indicators. With lower RMSE and higher explanatory power across all provincial subsets, the results consistently demonstrate that GLMM performs better than both GEE and generalized linear models (GLM). ANOVA tests verify that modeling methodologies, not data heterogeneity in GRDP or Gini values, are responsible for the differences in model performance. These results demonstrate how well GLMM handles complex data structures and within-subject correlations, providing more accurate and effective estimates in longitudinal beta regression scenarios. The study encourages the use of GLMM for more precise longitudinal analysis in economic and social research and offers insightful information for researchers modeling inequality indices.
Association Between PAI-1 4G/5G Genetic Polymorphism and Uncontrolled Allergic Asthma Iskandar, Harun; Ilyas, Muh; Muis, Eliana; Tabri, Nur Ahmad; Setiawati, Dewi
Advance Sustainable Science Engineering and Technology Vol. 7 No. 3 (2025): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i3.1872

Abstract

Airway remodeling is a major challenge in the management of uncontrolled allergic asthma, despite standard therapy with a combination of inhaled corticosteroids (ICS) and long-acting bronchodilators (LABA). Increased levels of Plasminogen Activator Inhibitor-1 (PAI-1) are thought to play a role in this process, and the 4G/5G polymorphism in the PAI-1 gene is one of the genetic factors that affect it. This study aimed to analyze the association between the 4G/5G PAI-1 genetic polymorphism and uncontrolled allergic asthma. A case-control study was conducted at Wahidin Sudirohusodo General Hospital between January-March 2024 on 40 patients with allergic asthma and 40 non-asthmatic subjects. Diagnosis was made through prik test (+), bronchodilator test (+), and asthma control classification according to GINA criteria. All asthmatic patients received Budesonide-Formoterol therapy for 4 weeks. PAI-1 levels were measured and 4G/5G polymorphism was analyzed by RT-PCR. Results showed that PAI-1 levels were significantly higher in uncontrolled asthma patients and in individuals with the 4G/4G genotype compared to non-4G/4G (2.38 ± 0.770 vs 1.65 ± 0.714; p=0.001). The 4G/4G genotype was more common in uncontrolled asthma (OR: 5.8) and was associated with the risk of severe obstruction (OR: 11.6). Thus, it was concluded that the 4G/4G genotype in the PAI-1 gene is associated with increased PAI-1 levels, risk of uncontrolled allergic asthma, and more severe degree of airway obstruction. The implication of the results shows that genetic testing of PAI-1 has the potential to be a predictive biomarker in personalized asthma therapy strategies. This approach can help clinicians identify high-risk patients and tailor interventions early and effectively to prevent remodeling and reduce long-term morbidity.
Comparative Efficacy of Two Bamboo-Derived Activated Carbons for Hospital Wastewater Remediation Setyarini, Putu Hadi; Pembayun, Hanum Surya; Sulistyarini, Dwi Hadi; Purwaningtyas, Nuretha Hevy; Dewi, Francisca Gayuh Utami
Advance Sustainable Science Engineering and Technology Vol. 7 No. 3 (2025): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i3.1895

Abstract

Liquid medical waste containing pathogens and hazardous chemicals can pollute the environment and endanger human health. The increasing volume of waste during the COVID-19 pandemic adds urgency to find effective and sustainable treatment methods. However, environmentally friendly and efficient solutions are still limited. This study aims to explore the utilization of activated carbon from two local bamboo species, Gigantochloa apus (GA) and Bambusa vulgaris (BV) as alternative adsorbents in the treatment of liquid medical waste. Two-year-old bamboo was traditionally carbonized and activated using 0.3 M sodium chloride solution. The 50 mesh charcoal powder was tested using BET surface area analysis with QUADRASORB evo™ instrument, morphology using FESEM (FEI Quanta 650), and pollutant reduction efficiency through pH, TDS (HAIK EZ 9909), COD (HACH DBR 200 closed reflux method), and BOD (Winkler method with BOD 6 VELP system) measurements. The results showed that GA activated carbon exhibited a much higher adsorption capacity due to its larger BET surface area compared to BV. In addition, pH and Total Dissolved Solids (TDS) analysis showed that wastewater treated with GA activated carbon exhibited a greater reduction in TDS levels. The study also evaluated the reduction of Chemical Oxygen Demand (COD) and Biological Oxygen Demand (BOD), which confirmed that GA provided higher pollutant removal efficiency than BV. These findings underscore the potential of GA and BV as effective adsorbents for medical wastewater treatment, offering a sustainable solution to improve water quality and reduce environmental impacts associated with liquid medical waste.
Enhancing Biology Students’ Mastery of Animal Anatomy with a Web-Based Electronic Atlas: Toward Sustainable Digital Learning Tools Sulistiyawati, Sulistiyawati; Hanum, Farida; Aminatun, Tien; Yanuarief, Cecilia
Advance Sustainable Science Engineering and Technology Vol. 7 No. 3 (2025): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i3.1952

Abstract

Learning animal anatomy in higher education often suffers from limitations in terms of visual media and practical time. Technology-based solutions such as web-based electronic atlases (e-atlases) can improve conceptual understanding and support digital continuous learning. This study aims to evaluate the effectiveness of web-based e-atlas in improving biology students' animal anatomy learning outcomes through a flipped classroom approach. This study used the ADDIE development model and a quasi-experimental design with a pretest-posttest control group approach. A total of 130 third semester students from three universities in Yogyakarta were divided into control (n=64) and experimental (n=66) classes. Instruments in the form of objective tests were validated by experts, and data were tested using Gain Score, N-gain, and t-test with parametric assumptions. The experimental class using e-atlas showed a significant increase in learning outcomes (N-gain=0.75; high category) compared to the control class (N-gain=0.29; low category), with significant differences based on t-test (p<0.001). These results support that e-atlas integration is effective in improving students' anatomical literacy. The use of web-based e-atlas in flipped classroom learning is effective, efficient, and has the potential to support the sustainability of biology learning. The findings recommend continued development of digital media to expand access and reduce reliance on physical animal dissection.

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