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Menampilkan 1241–1250 dari 10045 artikel
Assessing the Feasibility of Small-Scale RDF Technology in Urban Solid Waste Management Using Cost-Benefit Analysis
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
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-...
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1 Sitasi
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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DOI
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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DOI
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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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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Optimizing Human Resource Performance in Building Construction through Technology-Enhanced Strategy Development
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Construction projects involve complex processes requiring effective management and skilled human resources to ensure successful outcomes. This study analyzes key factors influencing human resource (HR) performance in building construction, identifying ability, working conditions, organizational structure, motivation, discipline, and compensation as critical determinants. A structured questionnaire using a 5-point Likert scale was employed as the data collection instrument, distributed to 130 con...
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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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An Artificial Neural Network Approach for Predicting Pavement Distress: A Case Study Toward Sustainable Road Maintenance
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
The Surface Distress Index (SDI) is a crucial parameter to consider when determining road conditions as part of an effective maintenance strategy. This study aims to develop an SDI prediction model using road surface distress data to enhance maintenance planning. The developed Artificial Neural Network (ANN) model resulted in an optimal structure with two hidden layers comprising 6 neurons and 4 neurons, respectively. The model was trained using two years of surface distress data collected from...
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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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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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