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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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Development Of Smart Energy Monitoring Internet of Things System Based on App Inventor for Electric Energy Efficiency I Wayan Dikse Pancane; I Nyoman Gede Adrama; I Wayan Sutama
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.v7i4.2006

Abstract

Electricity Demand for electrical energy in the food industry, including restaurants, continues to increase alongside the use of high-powered production equipment. This study aims to develop an Internet of Things (IoT)-based electrical load monitoring and control system using App Inventor at the Bakmi GM Denpasar production unit. The system consists of two components: a server (App Inventor) and a client (a microcontroller device based on a current sensor). Methods used include hardware design for power consumption data acquisition and development of a user interface for real-time monitoring and control. Test results show that the system can detect and manage electrical loads with 96.8% accuracy and reduce energy consumption by 18.5%, compared to before the system was implemented. These results demonstrate that integrating IoT technology into industrial electricity systems can significantly improve energy efficiency, reduce energy waste, and support environmental sustainability.
Effect of Natural Fiber Stacking Sequence on the Properties of Hybrid Composites for Drone Frame Applications Janiviter Manalu; Jefri Bale; Khristhoper Aris Arianto Manalu; Frans Augusthinus Asmuruf; Fitriyana, Deni Fajar; Nizar Alamsyah; Januar Parlaungan Siregar; Al Ichlas Imran; Tezara Cionita; Natalino Fonseca Da Silva Guterres
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.v7i4.2048

Abstract

The present study highlights the effective utilization of waste fibers in structural composites for drone frame applications, offering a sustainable pathway for developing high-performance materials while simultaneously addressing the issue of textile waste pollution. This study investigates the effect of ramie and cotton fiber waste fabric stacking sequences on the physical and mechanical properties of composites for quadcopter drone frames. Waste fabric was selected as an eco-friendly material to address textile pollution. The composites were fabricated using the hand lay-up technique with a 3:1 epoxy resin to hardener ratio, incorporating five layers of fabric in different configurations. The physical and mechanical properties, including density, water absorption, material hardness, flexural strength, and macro photography, were tested. The results showed that the composite made from fully cotton fabric (K-K-K-K-K) had the best density (1.182 g/cm³), lowest water absorption (2.22%), highest hardness (85.6 HD), and flexural strength of 179.1 MPa. These findings indicate that cotton fabric waste is a promising, sustainable material for composite reinforcement in quadcopter drone frame applications.
Smart Hospitality and Innovation: The Role of Leadership, Local Wisdom, and Technology Integration in Five-Star Hotels Suliati, Ni Nyoman; Noermijati; Sudiro, Achmad; Kurniawati, Desi Tri
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.v7i4.2462

Abstract

Innovative work behavior is a key driver of technology-based service innovation in the hospitality industry. This study integrates innovative work behavior into Technology-Enabled Innovative Behavior and reconceptualizes organizational commitment into Technology Adoption Commitment to capture employees' psychological attachment to technology adoption underexplored area. Commitment to capture employees’ psychological attachment to adopting technologies. This study aims to examine and analyze the influence of transformational leadership on Technology-Enabled Innovative Behavior, and through the mediating roles of paras-paros citizenship behavior and Technology Adoption Commitment. Using survey data from 377 employees of five-star hotels in Bali analyzed with PLS-SEM, the results show that transformational leadership significantly enhances Technology-Enabled Innovative Behavior, with Paras Paros Citizenship Behavior as a partial mediator, while Technology Adoption Commitment has no mediating effect. Higher Technology-Enabled Innovative Behavior is reflected in the frequent use of Property Management Systems, digital payment, and mobile check-in, whereas lower use of AI-driven customer service indicates areas for further innovation. The findings highlight that leadership and Paras Paros Citizenship Behavior provide strong cultural support, but innovation outcomes depend on the accessibility and integration of specific technologies. Strengthening leadership practices, local wisdom values, and the operational integration of underutilized tools can accelerate digital transformation in the hospitality industry.
Design of Wideband SPDT RF Switch Using Switchable DGS for Sustainable Wireless Systems Othman, Adib; Shairi, Noor Azwan; A Majid, Huda; Saparudin, Faiz Asraf; Zakaria, Zahriladha; Najib Al-Fadhali
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.v7i4.1957

Abstract

This paper presents a single-pole double-throw (SPDT) switch that is integrated with a thin rectangular patch switchable defected ground structure (DGS). It is a novel technology for obtaining wideband and high isolation for the SPDT switch in millimeter-wave (mm-wave) telecommunications due to the usage of switchable DGS with bandstop and bandwidth enhancement capabilities. A wideband and high isolation are required for the switchable DGS SPDT switch to operate optimally in mm-wave frequency ranges, as well as to reduce the effect of leakage signal on both the transmitter and receiver connected to the SPDT switch and hence improve system efficiency and signal integrity. The SPDT switch design was combined with two small rectangular patches switchable DGSs that could switch between bandstop and allpass responses using biasing diodes on the DGS. As a result, the suggested SPDT switch with the switchable DGS had 6 dB of insertion loss and high isolation of more than 25 dB with wideband isolation of 25.24% fractional bandwidth, which was consistent with the simulation results. Furthermore, the isolation magnitude is doubled compared to the conventional SPDT switch. This work demonstrates that integrating switchable DGS into discrete SPDT switches provides a practical solution for realizing wideband, high-isolation performance suitable for 5G mm-wave where compactness and bidirectional reconfigurability is increasingly essential for sustainable RF front-end systems.
Hybrid Deep and Machine Learning Framework for Cloud and Shadow Segmentation in Landsat-8 Imagery Pambudi, Isro Tri; Isa , Sani Muhamad
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.v7i4.1958

Abstract

Cloud and shadow interference in satellite imagery reduces the quality and reliability of remote sensing data. The traditional method would face issue to predict data near the shadow and cloud. To address this challenge, this study is focus improve the accuracy the area near shadow and cloud detection in Landsat-8 imagery. The implementation of hybrid module using standard CNN and U-Net CNN and a machine learning model using K-Nearest Neighbors (KNN) on SPARCS and CCA18 Landsat 8 dataset. A hybrid approach was then implemented by integrating CNN outputs and metadata into the second model (KNN/RF), and final evaluation was conducted using accuracy metrics. The research results show that the proposed hybrid deep and machine learning approach improves the accuracy of cloud and shadow segmentation in Landsat-8 imagery. Additionally, the implementation demonstrates that this method can reduce manual effort and computational cost, making it suitable for researchers with limited resources.
Effect of Biomass Feedstock Granulometry on Thermophysical Characteristics of Charcoal Briquettes via Screw Extrusion Samsudin Anis; Jefri Bale; Septian Eko Cahyanto; Ninda Kurniadi; Fitriyana, Deni Fajar; M. Thooriq Anwar; Januar Parlaungan Siregar; Natalino Fonseca Da Silva Guterres
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.v7i4.2047

Abstract

The present study investigates the impact of particle size variation (10, 18, 20, and 35 mesh) on the physical and thermal properties of charcoal briquettes from coconut shells manufactured with a screw-based extruder machine. The briquette manufacturing process involves crushing, mixing, molding, and drying. Assessments were conducted to ascertain friability, compressive strength, density, calorific value, volatile matter, ash content, fixed carbon, and water content. Comparable assessments were also performed on commercially available export-grade briquettes designated as b_5. The results of this investigation demonstrate that all briquette samples generated conform to the SNI 01-6235-2000 standard for water, ash, and calorific value, and adhere to international standards for fixed carbon, density, and compressive strength. The b_4 specimen (35 mesh) demonstrated the best performance, exhibiting a friability of 0% in the unburned condition and 7.04% in the burned condition. Compared to b_5, the b_4 specimen exhibited notable enhancement, demonstrating a 100% increase in friability in the unburned condition and a 53.22% improvement in the burned condition. This study emphasizes the significance of smaller particle sizes in improving briquettes' mechanical strength and combustion efficiency. It presents the importance of renewable energy technology and sustainable waste management.
Evaluating Ordinal Multivariate Models under Multicollinearity via Pairwise Likelihood: A Simulation Perspective Achmad Fauzan; Kusman Sadik; Anang Kurnia
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.v7i4.2282

Abstract

This study examines the effect of multicollinearity on ordinal regression through a two-stage Monte Carlo simulation. A synthetic population of 2,000,000 observations was generated with predictors drawn from a normal distribution, and responses simulated using an ordinal probit model. A Monte Carlo procedure was employed with 10 repetitions, each consisting of 100 random samples of 1,000 observations. Parameter estimation employed Maximum Likelihood Estimation (MLE) for univariate models and Pairwise Likelihood (PL) for multivariate models, with performance assessed using mean squared error (MSE), bias, and computation time. Results show that multicollinearity had negligible impact on estimator bias and MSE, confirming the robustness of both MLE and PL to correlated predictors. However, severe multicollinearity substantially increased computation time, indicating a trade-off between estimator stability and efficiency. These findings highlight PL as a viable approach for analyzing complex ordinal data, particularly in applications such as socio-economic surveys and health metrics where predictor correlation is unavoidable.
“Demata 2.0”: An On-Device AI Assistive Technology for the Visually Impaired Integrating YOLOv10 and OCR Abadi, Reza Febri; Pratama, Toni Yudha; Asmiati, Neti; Devi, Ade Anggraini Kartika; Yuwono, Joko; Dwi Setia Permana; Bahrudin, Febrian Alwan
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.v7i4.2380

Abstract

Accessibility to printed materials and independent recognition of the environment remain key challenges for students with visual impairments. To address this issue, this study introduces Demata 2.0, a fully offline on device multimodal AI system. The system integrates Google ML Kit for Optical Character Recognition (OCR) and the YOLOv10 model via TensorFlow Lite for object detection. A mathematical distance algorithm in the RGB color space enables color identification. Evaluation showed that object detection achieved a mean average precision of 31.83%, with an average processing speed of 2–3 FPS. For OCR, the system recorded a Character Error Rate (CER) of 4.81% and a Word Error Rate (WER) of 10.71% on printed documents. The RGB algorithm also determined the closest possible color effectively. Overall, Demata 2.0 advances assistive technology by providing an efficient and practical blueprint for AI integration.
Barium Removal from Produced Water Using RCC-Based Ceramic Adsorbent: Fixed-Bed Column Adsorption Herawati, Netty; Nasir, Subriyer; Roni, Kiagus Ahmad; Karim, Muhammad Arif
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.v7i4.2399

Abstract

This study focuses on the removal of barium ions (Ba²⁺) from produced water, a common challenge in industrial wastewater treatment due to barium’s toxicity and scaling potential. To address this, the research introduces a novel ceramic composite adsorbent formulated from natural clay and residue catalytic cracking (RCC) spent catalyst, combining low cost, sustainability, and enhanced adsorption performance. The main objective is to evaluate the adsorption efficiency of this composite in a fixed-bed column system under varying operational conditions, while also modeling its dynamic behavior. Produced water with an initial barium concentration of 0.58 mg/L (pH 8.8) was fed in up-flow mode at flow rates of 6, 7, and 8 mL/min using a peristaltic pump. Effluent samples collected over 180 minutes were analyzed by UV- Vis. spectrophotometry. Results showed that lower flow rates increased contact time and improved adsorption efficiency, with breakthrough delayed to ~210 minutes at 6 mL/min compared to 160 minutes at 8 mL/min. Breakthrough modeling indicated that the Thomas model best represented the data (R² ≥ 0.95), while the Yoon–Nelson model reliably predicted 50% breakthrough time. This work demonstrates that clay–RCC ceramic composites are effective, low-cost, and sustainable adsorbents.
Development of A Parametric Cost Estimation Model for Landfill Construction Projects Junaedi, Nurhayati; Bayuaji, Ridho; Susilo, Alfred Jonathan
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.v7i4.2424

Abstract

Indonesia’s waste management system is still dominated by the collect–transport–dispose approach, making landfills crucial for environmental sustainability. Landfill construction is a complex process requiring accurate cost estimation to prevent overruns and delays. This study develops a landfill construction cost estimation model using the Cost Significant Model (CSM) approach. Data were obtained from landfill project budgets in Java, Indonesia (2013–2021) and analyzed using multiple linear regression in SPSS. Results show that landfill block, leachate treatment installation, and operational road are the most significant cost components, the estimation model is Y = 3698103502.04 + 1.301X3 + 0.371X4 + 1.236X5. The model falls within the class 4 cost estimation accuracy range according to AACE International standards, making it suitable for feasibility study use. This study introduces a model, context-specific cost estimation model for landfill projects in Indonesia, supporting effective planning and sustainable infrastructure development

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