cover
Contact Name
Mega Novita
Contact Email
asset@upgris.ac.id
Phone
+6281958990880
Journal Mail Official
asset@upgris.ac.id
Editorial Address
Advance Sustainable Science, Environmental Engineering and Technology (ASSET) Jl. Sidodadi Timur No.24, Karangtempel, Kec. Semarang Tim., Kota Semarang, Jawa Tengah 50232
Location
Kota semarang,
Jawa tengah
INDONESIA
Advance Sustainable Science, Engineering and Technology (ASSET)
ISSN : -     EISSN : 27154211     DOI : https://doi.org/10.26877/asset
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
Articles 272 Documents
Road Damage Management Model Due to Overloading: AHP Priorities and Policy Implications (Case Study of Lampung Province) Tosulpa, M. Enriko; Putranto, Leksmono Suryo; Sulistyorini, Rahayu
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2629

Abstract

Lampung Province serves as a vital gateway for Trans-Sumatra-Java land transportation, placing a heavy burden on its 1,298 km of national roads. Managed by the Lampung National Road Traffic Management Agency (BPJN), these roads face accelerated degradation primarily due to Over-Dimension and Over-Loading (ODOL) vehicles. This study aims to identify causal variables of road damage, analyze significant parameters, and prioritize road sections for maintenance. Data were gathered through interviews and questionnaires with key stakeholders. Using the Analytical Hierarchy Process (AHP), the results identify ODOL vehicles as the primary cause of damage (67%), with the International Roughness Index (IRI) as the most critical parameter (27%). Consequently, the BTS Sukamaju – Km 10 Panjang Bandar Lampung segment is identified as the highest maintenance priority. The study recommends stricter ODOL enforcement through functional weighbridges, legal sanctions, and cross-agency oversight. These measures are essential to extend road service life, ensure safety, and improve regional transportation efficiency.
Development and Evaluation of an IndoBERT-Based NLP Model for Automated Clickbait Detection Kurniawan, Sandy; Pramayoga, Adhe Setya; Ashari , Yeva Fadhilah; Muhammad Afrizal Amrustian
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2637

Abstract

The rapid growth of digital news platforms necessitates reliable and automated systems for maintaining content quality at scale. This study presents the engineering and evaluation of an IndoBERT-based Natural Language Processing (NLP) framework for automated clickbait detection in Indonesian news headlines. The proposed framework is designed as an end-to-end text classification pipeline, incorporating data preprocessing, tokenization, fine-tuning of a pretrained IndoBERT model, and systematic performance evaluation. Experiments were conducted using the CLICK-ID dataset comprising 15,000 Indonesian news headlines, with an 80:20 stratified train–test split. The fine-tuned model achieved an accuracy of 0.83, with a precision of 0.82, recall of 0.77, and an F1-score of 0.79 for the clickbait class. Further evaluation using threshold-independent metrics yielded a ROC-AUC value of 0.89 and an average precision of 0.88, indicating strong discriminative capability under moderate class imbalance. Comparative analysis shows that the proposed approach outperforms prior CNN, Bi-LSTM, and ensemble-based methods evaluated on the same dataset. These results demonstrate that IndoBERT provides a robust foundation for engineering automated clickbait detection systems tailored to Indonesian-language news streams.
The Moderating Role of Digital Culture in the Relationship between Physical Ergonomics and Organizational Culture in SMI Nurwildani, Mohammad Fajar; Hari Purnomo; Elisa Kusrini; Hartomo Soewardi
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2666

Abstract

This study investigates the moderating role of digital culture in the relationship between physical ergonomics, organizational culture, and the performance of Small and Medium Industries (SMI). Using survey data from 123 manufacturing SME employees in Tegal, Indonesia, the analysis employed Structural Equation Modeling (SEM-AMOS). The findings reveal that digital culture significantly moderates the relationship between physical ergonomics and organizational culture (β = 0.083; CR = 12.126; p < 0.001). However, physical ergonomics demonstrated an unexpected negative effect (β = –1.031; CR = –5.958; p < 0.001). In addition, organizational culture was found to have no significant influence on performance (β = 0.113; CR = 1.038; p = 0.299). These counterintuitive results highlight digital culture as a key moderator that strengthens the adaptive role of ergonomics. The study contributes by demonstrating the complex interplay between ergonomics, organizational culture, and digitalization, offering practical insights for SME managers to integrate ergonomic practices with digital initiatives to enhance competitiveness.
Importance–Performance Analysis of Bus Rapid Transit Service Attributes for Passenger Satisfaction and Sustainability Hermawati, Putu; Hj. Zainordin, Nadzirah; Wei Eng, Thung; Oktaviani Putri, A. A. Ayu Asta; Sutapa, I Ketut
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2725

Abstract

The Bus Rapid Transit (BRT) system in Bali serves as a vital component of sustainable urban mobility. This study uniquely integrates Importance-Performance Analysis (IPA) with technical recommendations to provide a comprehensive evaluation of BRT performance and its contribution to sustainable transportation. The analysis identifies key service strengths—such as seating comfort, air conditioning, cleanliness, and personnel service quality—that exceed passenger expectations. Conversely, deficiencies are evident in bus stop conditions, accessibility for disabled passengers, punctuality, and environmental sustainability. By linking IPA results with actionable technical strategies, the study recommends upgrading bus stop infrastructure, enhancing accessibility design, implementing real-time scheduling, and tracking systems, transitioning to eco-friendly bus fleets, and strengthening passenger information and security systems. This integrated approach not only highlights priority areas for improvement but also offers a practical roadmap for policymakers and transit authorities to enhance service quality, boost ridership, and advance Bali’s progress toward a resilient and sustainable urban transport system.
SIMPORA: An Android-Based Data Management and Analytics Framework for Enhancing Community Sports Ecosystems Edi Purwanto; Setyawati , Heny; Cahyo Yuwono
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2735

Abstract

The increasing adoption of digital technologies in sports management highlights the need for efficient, data-driven systems that enhance community engagement and program evaluation. However, regional sports organizations in Indonesia, such as the Central Java Regional Indonesian Sports Community (KORMI), still face challenges in data integration, monitoring, and communication across stakeholders. This study aimed to design and evaluate SIMPORA, an Android-based data management and analytics system that supports sports activists, trainers, and administrators in planning, monitoring, and evaluating community sports programs. Using a Research and Development (R&D) approach with the Agile development model, the system was developed and tested among 45 users, including community sports leaders and KORMI administrators. Instruments included usability testing (System Usability Scale), task completion efficiency, and user satisfaction surveys. Quantitative evaluation results showed a mean usability score of 84 (excellent category), a 27% increase in data recording accuracy, and a 34% improvement in communication efficiency compared to manual reporting. User satisfaction reached 91%, indicating strong acceptance of the system. These findings demonstrate that SIMPORA effectively facilitates real-time data-driven decision-making and enhances coordination within community sports ecosystems. The system offers practical implications for expanding digital transformation initiatives in sports management across regional and national contexts.
Flood Mitigation in East Coast Semarang City: Hydrological and Hydraulic Analysis for Polder System Optimization Ikhwanudin; Harjanto, Imadudin; Afifah, Risdiana Cholifatul; Farida Yudaningrum
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2764

Abstract

Flooding is a recurring hazard across Indonesia, particularly in urban regions such as Semarang City, where high-intensity rainfall, tidal surges, land subsidence, and changes in land use contribute to frequent inundation. This study investigates the effectiveness of the Sringin Polder system in mitigating flood risks through an integrated hydrological and hydraulic analysis. The hydrological component involved calculating design rainfall values for various return periods, with a peak intensity of 113 mm recorded for the 10-year event. These values were used to simulate flood discharges using HEC-RAS.For the 25-year return period, the main river channel produced a simulated flood discharge of 47.42 m³/s, resulting in water overtopping the left embankment by 0.545 m at station P.30.  calculated flood flow and the existing capacity of the river cross-sections.
Integrating Lean Warehousing and Systematic Analysis to Minimize Waste in Finished Product Storage: A Case Study and Generalizable Improvement Framework Qurtubi; Haswika; Purnomo, Hari; Kien, Pham Trung
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2765

Abstract

Efficient warehouse management is critical for make-to-order production systems. This study investigates waste reduction in a metal casting company’s finished-product warehouse by applying Lean Warehousing principles. Using time-motion studies, Value Stream Mapping (VSM), Pareto diagrams, and fishbone diagrams, the research analyzed 13 workstations and identified five primary areas of waste. Simulation results demonstrated a significant cycle time reduction from 2,559 to 2,128 seconds, alongside an increased proportion of value-added activities. Although limited to a simulation, the findings highlight the effectiveness of Lean tools in standardizing work and redesigning layouts. The study concludes that continuous monitoring and Lean implementation are essential for achieving sustainable operational efficiency and reducing costs in industrial warehousing.
Optimization of Image Compression Using K-Means Clustering for Digital Heritage Archives Sahria, Yoga; Sudira, Putu; Priyanto
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2772

Abstract

Preserving digital cultural assets requires efficient compression to minimize storage and bandwidth costs. However, existing studies rarely evaluate K-Means Clustering on structurally complex objects such as the Prambanan Temple, leaving a research gap in assessing its performance against standard codecs. This study introduces a novel optimized K-Means pipeline with adaptive cluster selection and improved centroid initialization for compressing high-detail temple imagery. The method groups pixels based on color proximity, reducing redundancy while preserving key structural patterns. Experiments show that K-Means achieves PSNR 28.08–30.65 dB and SSIM 0.86–0.92, outperforming baseline JPEG at similar file sizes PSNR 26–28 dB, SSIM 0.80–0.87. This quantitative comparison demonstrates the model’s superior perceptual retention in textured stone regions. The methodological contribution lies in combining spatial–chromatic feature weighting with iterative centroid refinement, which increases cluster stability and reduces quantization artifacts. Findings confirm K-Means as a viable alternative for controlled-distortion compression. In conclusion, the proposed approach provides practical engineering implications, enabling reduced storage footprints, predictable reconstruction quality, and integration into hybrid compression pipelines for large-scale digital imaging systems.
Analysis and Design Android Augmented Reality Platform (Bilingual) for the Preservation of Cirebon Glass Paintings Suwandi, Suwandi; Willy Eka Septian; Agus Sevtiana; Noor Azura Binti Zakaria; Vanya Adhelita
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2784

Abstract

This study analyzes and designs a bilingual Android Augmented Reality (AR) platform to support the digital preservation of Cirebon Glass Paintings. The development uses Unity and AR Core with a human-centered design approach. A total of 30 participants (n=30) evaluated usability and performance. 3D assets were produced using photogrammetry with an optimized polygon budget of ≤25,000 triangles per object. Model compression applied Draco and KTX2 to reduce memory load. Benchmark testing was conducted on Snapdragon 720G class devices. Experimental results show that the platform achieved a stable performance of ≥30 FPS (mean = 32.6 FPS) and low tracking error (RMSE = 1.8–2.3 cm) under indoor lighting. Usability testing yielded a mean System Usability Scale (SUS) score of 81.4 ± 6.2, indicating excellent user acceptance. Compared with existing AR heritage applications, this research provides a reproducible pipeline for AR-based cultural digitization with performance guarantees on mid-range smartphones. The findings imply that optimized AR asset workflows can enhance public interaction with intangible cultural heritage such as Cirebon Glass Paintings. Limitations include restricted device testing and the need for more complex ecotourism content integration in future development.
A Hybrid Deep-Learning and Evolutionary Feature-Selection Framework for Skin Lesion Classification: Application to Monkeypox Detection Nidhi Chauhan; Alok Singh Chauhan
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2786

Abstract

The recent resurgence of Monkeypox has highlighted the urgent need for fast and accurate diagnostic tools. In this paper, we propose a new framework of hybrid deep learning to combine both DenseNet121 and MobileNetV2 to obtain both rich and supplementary attributes of the skin lesion images. By pooling the outputs of these two models in terms of features, we get the lightweight representation of the images as well as rich representations of the images. To improve the feature set, we use Genetic Algorithm (GA) which is useful in reducing the dimensions and eliminating redundancy. Optimized features are then categorized with the help of the Random Forest model, which has been selected due to its good performance and capacity to work with high-dimensional data. Using two publicly accessible datasets, MSID and MSLD, we tested our approach and obtained remarkable classification accuracies of 92.71% and 97.77%, respectively. These findings highlight the success of combining ensemble learning, evolutionary optimization, and deep learning to achieve accuracy and proper diagnosis of monkeypox through medical images.