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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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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 30 Documents
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Search results for , issue "Vol. 7 No. 2 (2025): February-April" : 30 Documents clear
Advancing Adaptive and Personalized E-Learning Systems: A Systematic Literature Review Amastini, Fitria; Kinanti Suci Sekarhati, Dwinanda; Puspitasari, Maya
Advance Sustainable Science Engineering and Technology Vol. 7 No. 2 (2025): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/m82zg802

Abstract

With the rise of Information and Communication Technologies (ICTs), adaptive e-learning has become a promising method for enhancing educational practices. This study reviews current research on personalized adaptive e-learning systems and proposes a mobile-based design to addressing the requirements toward Industry 4.0 and Society 5.0. Using a systematic literature review methodology by Kitchenham and Charters, 28 studies were analyzed further. The findings suggest a necessity for clearer definitions of "personalized" and "adaptive" learning and categorize adaptive e-learning designs into four models: learning materials, learner characteristics, pedagogical approaches, and learning structure systems. The findings show there is still a lack of clarity in the definitions of "personalised" and "adaptive" learning, emphasizing the importance of more standardized terminology. The proposed system dynamically customized learning content material based on user preferences, cognitive abilities, and performance metrics, demonstrating the potential for increased students’ engagement and their learning outcomes. This study focusses on the possibilities of blockchain-based open educational resources, artificial intelligence, and gamification as for more engaging personalized student test to improve adaptive learning environments. Future study should confirm the suggested paradigm using empirical investigations and assess its usefulness in promoting lifelong learning.
A Review of Factors Affecting the Mechanical Performance of PLA in FDM 3D Printing Saefudin, Slamet; Samsudi Raharjo; Ilham Yustar Afif; Syarifudin; Purnomo; Muhammad Omar Rusydi; Kuzmin Anton; Muhammad Subri; M. Edi Pujianto
Advance Sustainable Science Engineering and Technology Vol. 7 No. 2 (2025): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/chs1gc62

Abstract

3D printing has rapidly evolved due to its significant advantages in rapid prototyping. 3D-printed products for industrial applications require stable mechanical properties, which are influenced by various factors. The lack of a comprehensive discussion addressing the factors affecting mechanical properties is the main reason for this review. This article aims to provide an overview of Fused Deposition Modeling (FDM) 3D printing concerning the factors that influence the mechanical performance of FDM 3D products using polylactic acid (PLA) material. The article covers the impact of material factors, process parameters (such as layer thickness, infill patterns, print orientation, infill patterns, infill density, infill width, temperature, and printing speed), as well as post-processing treatments as key considerations. The contribution of this article is to explain to researchers and industry practitioners the factors that affect the mechanical performance of FDM 3D printed products. 
Adaptive Learning Systems for Data Conversion in EHRs through Machine Learning Janardhan Deepa; Jayashree Jayaraman
Advance Sustainable Science Engineering and Technology Vol. 7 No. 2 (2025): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/aqvgnq17

Abstract

Healthcare data management has advanced with Electronic Health Records (EHRs), enhancing the efficiency of medical procedures. Machine learning applied to EHRs transitions healthcare from reactive to proactive, supporting the cost-efficiency and sustainability goals of smart cities. However, digitizing medical records introduces security risks, especially from internal threats, necessitating strong detection systems. Research into machine learning techniques, such as decision trees, random forests, and support vector machines (SVMs), shows their effectiveness in detecting EHR breaches. Balancing system usability with patient privacy remains a key challenge amid widespread data sharing. This study highlights SVMs and deep learning models as promising for improving EHR data accuracy, enhancing detection efficiency, and supporting clinical decisions. Despite advancements in AI, deep learning continues to play a crucial role in refining clinical decision systems, including translating EHR data using technologies like natural language processing (NLP). The study provides a qualitative analysis of how deep learning can optimize EHR processes while addressing security and functional challenges.
A Novel Classification Framework Using Transformer-Based Encoding and Low-Rank Tensor Fusion for Enhanced Classification and Efficiency Venkatachalam Uma; Vanmeeganathan Ganesh
Advance Sustainable Science Engineering and Technology Vol. 7 No. 2 (2025): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jgz0xe27

Abstract

This paper proposes a transformer-based framework for sentiment analysis, designed to improve both accuracy and computational efficiency across diverse datasets. The model incorporates a low-rank tensor fusion mechanism to reduce computational complexity, optimizing the transformer encoder’s performance. Through an extensive evaluation on three benchmark datasets—Airlines, CrowdFlower, and Apple—our approach demonstrates superior performance in sentiment classification tasks, achieving accuracy levels of 93.2%, 91.5%, and 92.1%, respectively. The framework utilizes standard performance metrics, including precision, recall, and F1-score, showing consistent improvements of 5-10% over traditional models. Additionally, the model's efficiency is highlighted by its reduced processing time (120 ms per sample), making it suitable for real-time applications. The ablation study reveals that components such as pre-trained embeddings and attention mechanisms significantly contribute to its performance. The results underscore the model's robustness in handling varying sentiment distributions and highlight its scalability for large-scale sentiment analysis tasks. This study provides valuable insights into the practical application of transformer-based models in sentiment analysis, offering an efficient solution for processing diverse social media data in real-time.
Molecular Identification of Color Variants of Procambarus clarkii Using the COI Gene for Taxonomic Validation Bhagawati, Dian; Husein Sastranegara, Muhammad; Agus Nuryanto; Anastasia Endang Pulungsari; Elly Tuti Winarni; Atang; Hanan Hassan Alsheikh Mahmoud
Advance Sustainable Science Engineering and Technology Vol. 7 No. 2 (2025): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/hcaz9264

Abstract

This study addresses taxonomic uncertainty surrounding color variants of Procambarus clarkii in aquaculture and conservation contexts. We investigated whether commercially significant color morphs represent distinct subspecies or phenotypic variations of a single species. Using the cytochrome c oxidase subunit I (COI) gene as a molecular marker, we analyzed four color morphs (blue, white, orange, and brown) from aquaculture facilities in Banyumas Regency. DNA extraction, PCR amplification, and sequencing were performed on 20 specimens. Results showed high sequence homology (98.7-99.8%) across all variants, confirming they belong to a single species. Genetic distance analysis revealed minimal divergence (0.2-1.3%), insufficient for subspecies classification. Phylogenetic reconstruction demonstrated specimens clustered by genetic similarity rather than color or geographic origin, indicating coloration results from genetic mutations rather than environmental adaptations. This COI-based approach provides a molecular framework for taxonomic classification of P. clarkii varieties, with implications for breeding programs, variety certification, and management of this economically important yet potentially invasive species.
Comparative Analysis of Formwork Systems: Cost Efficiency and Time Management in Construction Projects Supriyono, Auliyah Shabirah; Putra, I Nyoman Dita Pahang; Bambang Trigunarsyah
Advance Sustainable Science Engineering and Technology Vol. 7 No. 2 (2025): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i2.1320

Abstract

Formwork systems are essential for achieving efficiency and sustainability in multi-story construction. This study compares the cost and time efficiency of multiplex and aluminum formwork systems for constructing beams and slabs on the 6th to 13th floors. Field observations and a literature review were employed to gather data using a mixed-methods approach. This study adopts a mixed-methods approach, combining quantitative and qualitative methods. The findings reveal that aluminum formwork requires 60 days to complete, compared to 112 days for multiplex formwork, saving 52 days. Regarding cost, aluminum formwork amounts to IDR 1,805,910,198, offering savings of IDR 159,540,423 compared to multiplex formwork at IDR 1,965,450,621. Graphical analysis highlights the advantages of aluminum formwork in optimizing project workflows and reducing delays. These results demonstrate aluminum formwork potential to enhance efficiency, minimize material waste, and support sustainable construction practices. Future research is encouraged to explore alternative materials and labor strategies to further advance sustainability in the construction industry.
Assessment of Occupational Noise Exposure in Industrial Environments: A Case Study in Metal Casting Dwiandra, Annisa Restia; Qurtubi; Haswika, Haswika; Sugarindra, Muchamad
Advance Sustainable Science Engineering and Technology Vol. 7 No. 2 (2025): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/3aqgpy70

Abstract

Good work environment conditions can affect the increase in worker productivity. One of the work environment factors that needs to be considered is distraction. Noise problems not only interfere with concentration but can also damage workers' hearing and reduce overall work safety. Therefore, this study aims to analyze the noise level in the work area in the production process of a company engaged in the metal casting industry and provide recommendations that can reduce the negative impact on the workforce. This measurement uses Decibel X with a time interval of five seconds, and then data processing is carried out to determine the LTm5 value. The measurement results show that the level of disturbance in some work areas exceeds the recommended threshold, increasing the risk of worker health problems. To reduce this negative impact, the study provides the provision of personal protective equipment (PPE), such as earplugs, as well as the implementation of occupational safety and health (OHS) socialization. This research makes an essential contribution to the management of nuisance risks in industrial environments, especially in improving worker safety and health through effective mitigation strategies. 
Exploration of Identification at Each Phase to Advance Productivity Towards Sustainable Practices Putri, Azhahra Divia; Putra, I Nyoman Dita Pahang; Adibah Nurul Yunisya
Advance Sustainable Science Engineering and Technology Vol. 7 No. 2 (2025): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i2.1333

Abstract

This study analyzes the productivity of tower cranes in high-rise building construction projects in Indonesia, focusing on sustainable practices and advanced techniques. The rapid growth of infrastructure has heightened competition in the construction sector, making efficiency essential. Tower cranes are key to accelerating project timelines and reducing costs, but their productivity can differ between theoretical specifications and actual field conditions. Using a quantitative descriptive method, this study compares theoretical productivity based on equipment specifications with direct field observations of the Potain MCT 205 tower crane at a high-rise site. Data on cycle time and lifting volume for work such as column reinforcement and concrete pouring were collected. Results show that theoretical productivity is higher than field observations, with a 40% increase for works and up to a 92% increase per phase. The findings stress the importance of incorporating advanced planning and sustainable practices to optimize productivity, minimize delays, and reduce costs in construction projects
Artificial Intelligence in Personalized Marketing: Strategies for Enhancing Consumer Engagement Syaharuddin; Hidayanti, Nur Fitri; Iswanto, Dedy; Ningsih, Nurul Hidayati Indra
Advance Sustainable Science Engineering and Technology Vol. 7 No. 2 (2025): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/df5dwp69

Abstract

This study examines the use of artificial intelligence (AI) in personalized marketing to boost consumer engagement. Using a systematic literature review from Scopus, DOAJ, and Google Scholar, it finds that AI helps predict consumer behavior, optimize communication, and deliver real-time adaptive content. These capabilities enhance customer satisfaction and loyalty. However, challenges such as data privacy, ethical concerns, and the need for human oversight remain. The study recommends investing in AI-driven analytics, automation, and dynamic content strategies to improve customer experience and interaction. 
Spectral and Molecular Modifications of Hydrophilic Silica Aerogel: A Study on Doping Effects and Structural Evolution Israa F. Al-sharuee; Orass Abdulhadi Hussein
Advance Sustainable Science Engineering and Technology Vol. 7 No. 2 (2025): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/qtrytk53

Abstract

Silica gel has recently become an interesting material because of its importance in many applications in several fields such as medicine and sustainable technology. It has been found that the impregnation of some materials improves the synthetic properties of silica. Silica gel was prepared via mixed TEOS: ethanol: hydrochloric acid with molar ratios of 2:10:1.5. After doping with Diethyl in different concentrations 10-4, 10-5, and 10-6) g/cm3, the molecular properties were studied by examining the FTIR, and the UV spectrum of the prepared samples. The synthetic and morphological properties were investigated through BET and SEM and EDX. Results showed the ultra-violet to the visible (green) region at the concentration (10-5) g\cm3, and doping was evident through the change in the absorption peaks for different concentrations. The FTIR spectrum remained unchanged, as well, the high specific surface area indicates the inner connection of the dye to the silica network, which makes it a promising material in improving the structural properties for industrial applications. Materials with a limited variety of homogeneous microporous materials except for some aggregation appear at a high concentration (10–4) g/cm3 due to diethyl particles.

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