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Optimizing the Productivity of Traditional Textile Artisans through Education and Training for a Sustainable Cultural Industry
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Lasem handmade batik is part of a cultural heritage that has significant economic potential, but the productivity of its artisans is still low due to limited skills and access to innovation. This problem poses a challenge to cultural preservation efforts in line with sustainable development. This study aims to examine the role of education and training in improving the productivity of Lasem handmade batik artisans. The method used is quantitative, with a sample of 100 artisans purposively select...
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Bayesian Generalized Poisson Regression Modeling for Overdispersed Maternal Mortality Data
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
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 wor...
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Enhancing Biology Students’ Mastery of Animal Anatomy with a Web-Based Electronic Atlas: Toward Sustainable Digital Learning Tools
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
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-e...
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Digital Transformation of Import Logistics for Operational Efficiency: Case-Based Evidence from the Plastics Industry
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
This study aims to explore the use of digital systems to reduce import process costs, increase the percentage of national direct deliveries from ports to consumers, and analyze the impact of proposed improvement measures. The research employs a single case study approach with data collected through observation, document analysis, and quantitative data collection from one of the biggest plastic resin distribution companies in Indonesia. The data were analyzed using the CIMO (Context-Intervention-...
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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 (ASSET)
Vol 7
, No 3
(2025)
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 treat...
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1 Sitasi
Artificial Neural Network-Based Forecasting of Rice Yield Using Environmental and Agricultural Data
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
This study presents a high-accuracy predictive model for rice production in Indonesia using Artificial Neural Networks (ANN), achieving an R² of 98.11%, Mean Absolute Error (MAE) of 0.0966, and Mean Squared Error (MSE) of 0.0189. Climate variability remains a significant challenge to rice cultivation in regions like Malang City, where unpredictable environmental factors such as rainfall, temperature, and humidity hinder effective crop planning and yield estimation. To address this, we developed...
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1 Sitasi
Multi-Horizon Short-Term Residential Load Forecasting Using Decomposition-Based Linear Neural Network
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
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-hori...
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Evaluating the Role of Extractives in Biomass Pyrolysis for Enhanced Hydrogen Syngas Production
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
This study explores how extractive content in lignocellulosic biomass affects syngas quality during fixed-bed pyrolysis-gasification, specifically focusing on hydrogen (H₂) concentration. While woody biomass is a known energy source, the link between its non-structural organic compounds (extractives) and H₂ in syngas is often overlooked. We investigated teak, coconut, and jackfruit wood to understand this influence and optimize temperature for better biomass-to-hydrogen conversion. An MQ-8 senso...
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Biosorption of Chromiun in Batik Wastewater Using SCOBY Microbial Biomass: A Sustainable Bioremediation Approach
Nur Lu’lu Fitriyani
; Dina Adelia
; Slamet Budiyanto
; Ristiawati
; Jaya Maulana
; Muhammad Choiroel Anwar
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Batik wastewater poses an environmental threat due to hazardous heavy metals like lead, cadmium, and chromium (Cr). This study investigated the effectiveness of SCOBY (Symbiotic Culture of Bacteria and Yeast), a microbial consortium from kombucha production, in reducing Cr levels in batik wastewater. SCOBY is a promising biosorbent for heavy metals. The research aimed to assess SCOBY's ability to decrease Cr contamination in different types of batik wastewater (hand-drawn, stamped, and printed)...
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Predicting Habitat Suitability of Mahseer Fish (Tor spp.) in Tropical River Systems Using MaxEnt and Google Earth Engine: A Geospatial Modeling Approach
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Rivers are vital freshwater habitats that face threats of degradation and climate change. Mahseer fish, a key species, is in decline. This study predicted Mahseer fish habitats in Central Java using the Google Earth Engine and the MaxEnt machine learning algorithm. Environmental predictors, including NDVI, elevation, slope, river order, temperature, and rainfall, were extracted from Sentinel, SRTM, MODIS, and CHIRPS data. The model identified river order as the most influential variable (73%), f...
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