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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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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 (ASSET)
Vol 7
, No 3
(2025)
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 v...
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Recent Advances in Catalytic Systems for the Sustainable Synthesis of Ethyl Levulinate from Biomass
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
The esterification of levulinic acid to ethyl levulinate presents challenges in catalyst efficiency, reusability, and environmentally friendly process design, restricting commercial scalability. This study examines recent studies on diverse catalysts, including Deep Eutectic Solvents (DES), homogeneous and heterogeneous systems, and their effects on yield. DES is positioned as a more sustainable option, with yields as high as 99.8%, quicker reaction times, and a lower environmental effect. Wh...
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Computational Assessment of Orthopedic Implant Durability Using Finite Element Analysis
Haryanto, Ismoyo
; Bagastomo, Riondityo Soni
; Ismail, Rifky
; Siregar, Januar Parlaungan
; Cionita, Tezara
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Finite Element Analysis (FEA) provides a rapid and cost-effective method to evaluate orthopedic implants. This research investigates the mechanical performance and long-term durability of a seven-hole SS 316L Basic Fragment Set (BFS) reconstruction plate designed for pelvic fractures. Adhering to ASTM standards, material properties were defined via tensile testing (ASTM E8), while static and fatigue analyses were performed using a displacement control method in a four-point bending test setup in...
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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
Comparative Performance of GLMM and GEE for Longitudinal Beta Regression in Economic Inequality Modelling
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
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 d...
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Comparative Analysis of Observed and Empirical Rainfall Distribution for Flood Hydrograph Modeling
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Flood disasters in Indonesia are persistent challenges during the rainy season, primarily due to intense rainfall and inadequate flood control. This study evaluates hourly rainfall to characterize hydrology and predict flood discharge more accurately, benefiting water infrastructure planning. The research used modified Mononobe methods, observational data, and rainfall-runoff modeling, including HEC-HMS simulations with the SCS-CN unit hydrograph. Observed rainfall simulated a flood discharge of...
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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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