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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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Kota semarang,
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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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Experimental Evaluation of Tali Bamboo Trusses with FRP Connections for Sustainable Structural Applications Budiono; Arif Mudianto
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): 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.v7i4.1975

Abstract

Tali Bamboo is a local material that is widely utilized in traditional construction due to its availability, strength, and flexibility. However, weaknesses in the connection system are a major obstacle in its application as a structural element. This research aims to evaluate the strength and stiffness of tali bamboo joints using Fiber Reinforced Polymer (FRP) as joint reinforcement in plane trusses. The method used was experimental testing of three truss models with varying numbers of FRP laminate layers (1, 2, and 3 layers) combined with Polyvinyl Acetate (PVAc) adhesive and epoxy resin. Tests were conducted with center point loading to assess the performance of the connection. The results showed that the connection with 2 layers of FRP was able to withstand the maximum load optimally, or was able to withstand an average maximum load of 25.2 kN with an average deflection of 3.1 cm. The highest value reached 30 kN and a deflection of 4.0 cm, indicating optimal efficiency and strength. The physical properties of tali bamboo in the internode section are weaker than those in the book section, but still generally meet the criteria for structural materials. The implications of this study suggest that the use of double-layered FRP connections in tali bamboo can be an effective solution in improving the performance of plane truss structures, although further testing is required for more complex connections between truss elements.
Comparison of Conventional and Adaptive Hysteresis Current Control Methods for Power Quality Improvement using Active Filters Handoko, Susatyo; Winardi, Bambang
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): 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.v7i4.1981

Abstract

Hysteresis is widely applied in converter control techniques because of its simplicity and stability. This paper discusses hysteresis current control applied to single-phase active filters. Active filters are designed for harmonic mitigation and reactive power compensation. Simulation and comparison of conventional hysteresis control (constant hysteresis band - variable frequency) and adaptive hysteresis (variable hysteresis band - constant frequency) on active filters were carried out. Simulations were carried out using MATLAB Simulink. The simulation results show that the active filter can work well when using conventional or adaptive hysteresis current control. This is indicated by a decrease in the THDI of the source current and an increase in the power factor on the source side. From the simulations carried out, with a maximum source current THDI target of 5% according to the IEEE 519 standard, the hysteresis band required for conventional hysteresis control is 0.5 A, and the switching frequency required for adaptive hysteresis control is 120 kHz. By increasing the power factor to unity, it results in a reduction in reactive losses in the system. These findings are significant in advancing more efficient power quality control strategies, reducing harmonic distortion and improving power factor in electrical systems. Such improvements contribute directly to the development of more sustainable and resilient electrical infrastructures.
Narrative-Driven Optimization for Sustainable Museum Networks: Integrating Freytag’s Pyramid and Hybrid PSO-Machine Learning Framework Luki Safriana; Nurhayati; Widiyani; Didik Suharjito
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): 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.v7i4.1954

Abstract

This study addresses sustainable urban heritage management needs through an AI-optimized methodology for Government-Museum networks. Integrating dramaturgical storytelling with computational intelligence, we develop a framework combining Freytag's Pyramid narrative framework with a hybrid Particle Swarm Optimization (PSO)-Machine Learning (ML) model. This sustainability-driven design aligns spatial routing with low-carbon objectives and thematic continuity, enhancing tourist itineraries while reducing environmental impact. Our model integrates GIS analysis of museum connectivity, accessibility criteria, and emissions indicators. Validated via Orange ML, the PSO-ML model achieves route optimization by minimizing distance, time, and CO₂ emissions. Results demonstrate significantly reduced travel distances/emissions and improved narrative coherence. The paradigm advances geographical justice, operational efficiency, and AI-mobility systems in promoting urban sustainability.
Barriers to Lean Manufacturing Implementation in the Bakery Industry: An Empirical Study from Indonesia Caroline Felicita Aurelius; Mangngenre, Saiful; Setiawan, Irwan
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): 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.v7i4.1974

Abstract

The implementation of lean manufacturing is essential for companies to minimize waste by reducing non-value-added activities while maintaining product quality and customer satisfaction. Despite its advantages, various barriers hinder its optimal application. This study aims to identify the factors that impede the implementation of lean manufacturing and determine the most dominant factors in bakery factories in Indonesia. The research was conducted across 14 bakery factories on the islands of Sumatra, Java, Kalimantan, and Sulawesi. Data was collected using a survey questionnaire and analyzed using factor analysis and the Decision Making and Evaluation Laboratory (DEMATEL) method. The results reveal seven key factors with significant influence, with technology emerging as the most dominant factor (1.404), followed by organizational culture (0.497). These findings underscore the importance of addressing the technological limitations and organizational culture to enhance lean manufacturing efficiency. The practical implications of this study suggest that bakery companies should focus on improving their technological infrastructure and fostering a culture supportive of lean principles to optimize production efficiency. Theoretical implications include the extension of lean manufacturing frameworks to address sector-specific challenges in the bakery industry, contributing to the broader field of sustainable manufacturing practices
Unlocking Indonesia’s Critical Minerals for Renewable Energy: Challenges and Pathways to Net-Zero Emissions Andrew Cahyo Adhi; Nur Widi Priambodo; Muchammad; Suryo Utomo, Tony; Akmal Setia Abdrian, Reyhan Kevin
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): 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.v7i4.2005

Abstract

Indonesia holds a pivotal role in the global renewable energy (RE) transition due to its abundant reserves of critical minerals like nickel, cobalt, and rare earth elements (REEs). However, a significant gap exists between these resources and the technologies needed to leverage them, highlighting supply chain vulnerabilities. This qualitative, exploratory-descriptive study integrates Life Cycle Assessment (LCA), criticality matrix analysis, and value chain mapping to examine Indonesia’s mineral supply chains, sustainability, and Local Content (TKDN) policies. The findings reveal that despite its mineral wealth, Indonesia's inadequate management capacity complicates the achievement of TKDN goals and exposes supply chain deficiencies. The research advocates for developing downstream industries, adopting sustainable mining practices, and international collaboration. Policy recommendations include simplifying regulations, fostering innovation, and embracing circular economy principles, providing Indonesia with a strategic framework for its energy transformation.
Mechanical Performance of Epoxy Composite Reinforced with Wood Dust and Crumb Rubber Waste Imran, Al Ichlas; Siregar, Januar Parlaungan; Cionita, Tezara; Fitriyana, Deni Fajar; Anis, Samsudin; Dewi, Rozanna; Junaedi, Thomas; Wijayanto, Etanto Heiliano; Prayogo, Wisnu
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): 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.v7i4.2041

Abstract

The incorporation of wood dust and crumb rubber waste as filler in polymer matrix composite still requires in-depth evaluation of mechanical properties because they have different characteristics. This study evaluates the tensile, flexural, and hardness properties of epoxy composites reinforced with various fractions of wood dust and crumb rubber (5, 10, and 15%). The results showed that the composite with 5% crumb rubber produced the highest tensile strength of 15.52 MPa (CR5), while the highest flexural strength was 30.46 MPa (CR10), and the highest hardness was 75.9 HRC (CR15), indicating superior performance for CR fillers. The observations of the fracture surface showed that increasing the fraction of wood dust contributed to lowering the mechanical performance due to the relatively large distribution of voids and agglomeration. This finding confirms the importance of filler type and fraction selection on composite performance. Future research is recommended to explore filler surface modification and hybrid combinations to improve dispersion and bonding between phases in composites.
Quantifying the Causal Impact of Employment Trends on Academic Performance Using Time-Series and Public Interest Data in Indonesia Muttaqin, Alif Noorachmad; Lubis, Muharman; Mulhartono, Tomi; Lubis, Arif Ridho
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): 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.v7i4.2358

Abstract

This study quantifies the causal impact of employment trends on academic performance using a hybrid model of survey data and time-series public interest data from Google Trends in Indonesia. Employing Granger causality and regression analysis, the research investigates eight determinants of GPA and their relationship to labor indicators. A purposive sample of 40 respondents and secondary data from 2011–2019 were analyzed. Granger tests reveal significant one-way causality from employment to GPA indicators, particularly in parental monitoring (F = 7.06; p < 0.05) and learning motivation (F = 9.68; p < 0.05). Regression analysis supports these findings with R² values above 0.50. Results highlight the potential of integrating behavioral data into educational analytics. This research contributes methodological innovation by incorporating public interest data to explain academic outcomes, with implications for predictive modeling in education policy and planning.
A Comparative Analysis of Time-Series Models of ARIMA and Prophet IoT-Based Flood Forecasting in Sungai Melaka Mazran Esro; Siva Kumar Subramaniam; Tuani Ibrahim, Ahamed Fayeez; Yogan Jaya Kumar; Siti Aisyah Anas; Sujatha Rajkumar
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): 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.v7i4.1048

Abstract

Flood prediction is essential for mitigating disasters, especially in low-lying areas. This study presents an IoT-driven flood forecasting system that utilizes ARIMA and Prophet models to predict water levels in Sungai Melaka, Malaysia. Sensor data collected from an IoT-based flood observatory system was used to train and evaluate both models. Performance analysis based on RMSE and MAPE revealed that while ARIMA captures short-term trends, Prophet outperforms it with a lower MAPE of 6% and RMSE of 5, demonstrating superior accuracy and adaptability. Prophet's advantage lies in its robust seasonality handling, flexible trend adjustments, and ability to incorporate external regressors, making it more effective for real-time flood monitoring. The study also highlights Prophet’s limitations in capturing abrupt water level spikes, suggesting that integrating environmental factors such as rainfall intensity and upstream discharge could enhance predictive accuracy. The findings contribute to the development of AI-driven flood warning systems, supporting urban disaster management strategies.
Mechanical Properties of Epoxy Composite Reinforced with Spent Coffee Ground and Coffee Husk Etanto Heiliano Wijayanto; Imran, Al Ichlas; Siregar, Januar Parlaungan; Mohd Ruzaimi Mat Rejab; Tezara Cionita; Wisnu Prayogo; Deni Fajar Fitriyana; Rozanna Dewi; Thomas Junaedi; Agustinus Purna Irawan
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): 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.v7i4.2052

Abstract

This study aims to investigate the effect of increasing the concentration of natural filler on the mechanical properties of Spent Coffee Ground (SCG) / Coffee Husk (CH) reinforced epoxy matrix composite. The materials used in this study are epoxy resin as a matrix and waste coffee grounds and coffee husks as natural fillers with sizes of 100-mesh and concentrations of 10, 20, and 30 wt.%. The results showed that SCG 10 wt.% produced the best mechanical properties compared to the other samples based on tensile strength (19.58 MPa), tensile modulus (1.70 GPa), flexural strength (44.55 MPa), and flexural modulus (2.32 GPa). On the other hand, CH 30 wt.% contributed the highest hardness value of 50.33 HRB compared to other samples. The findings in this study prove that the appropriate composition will affect the compatibility between the filler and the matrix, thus impacting the mechanical properties of the composite. This phenomenon can be seen based on microscope analysis, which shows a strong interaction between the matrix and filler and the formation of voids and agglomeration
Simulation-Based Optimization of Resource Allocation in Seasonal Recreational Facilities Using Discrete Event Simulation and Machine Learning Joko Giyanto, Ferdi; Lestari Widaningrum, Dyah
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): 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.v7i4.2062

Abstract

The study proposes a simulation-based optimization framework to surmount recreational facility operational inefficiencies via spatial design, guest flow, and staff allocation. Adopting Discrete Event Simulation (DES) and Machine Learning (ML), the research optimizes capacity planning and resource allocation in the face of dynamic seasonal demands. A year's worth of operations data was utilized for statistical distribution modeling of visitor interarrival times in RStudio, categorized into low, regular, and high seasons. The simulation model, developed in AnyLogic, uncovered service bottlenecks—particularly at ticketing counters and photo points. Validation results indicated close alignment with real-world operational metrics, ensuring model validity. Actionable suggestions are provided in terms of dynamic employee scheduling and spatial reconfiguration for improved efficiency and visitor experience. By integrating DES and ML, the study contributes to sustainable operations and provides a transferable method for the optimization of service systems in weather-dependent recreational environments.

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