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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 50 Documents
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Search results for , issue "Vol. 7 No. 1 (2025): November-January" : 50 Documents clear
An Experimental Study on Axial Stress-Strain Behaviour of FRP-Confined Square Lightweight Aggregate Concrete Columns Louk Fanggi, Butje Alfonsius; Budi Suswanto; Yuyun Tajunnisa; Jusuf Wilson Meynerd Rafael; Jonatan Lassa; Ahmad Basshofi Habieb
Advance Sustainable Science Engineering and Technology Vol. 7 No. 1 (2025): 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.v7i1.865

Abstract

This article presents the results of a research project that aimed to evaluate how the number of fiber-reinforced polymer (FRP) layers and the compressive strength of concrete affect the stress-strain behaviors of concrete columns produced from artificial lightweight aggregate with square cross-sectional shapes. Eighteen test specimens were manufactured and wrapped with glass fiber-reinforced polymer (GFRP) material. The specimens were later subjected to concentric compression for experimental evaluation. The experimental results suggest that GFRP efficiently confines square lightweight aggregate concrete columns. Furthermore, the test results indicate that adding FRP layers augments the ultimate stress and strain. Finally, the results suggest that an increase in the compressive strength of concrete leads to a corresponding increase in the ultimate stress. On the other hand, it has been observed that the ultimate strain decreases as compressive strength increases. The research findings reveal the behaviour of FRP-confined square lightweight aggregate concrete columns, which may also be utilized to formulate a new design-oriented model for these columns.
Sustainable Digital Transformation in Healthcare: Challenges and Directions in the Society 5.0 Era Kusumo, Haryo; Dian Marlina; Achmad Solechan
Advance Sustainable Science Engineering and Technology Vol. 7 No. 1 (2025): 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.v6i4.876

Abstract

This study conducts a comprehensive literature review on the digital transformation required by health service institutions during the Society 5.0 era. Utilizing articles related to digital transformation and health services, the study presents qualitative data simplified into descriptive narratives to draw meaningful conclusions. The method employed is a qualitative literature review. The review identifies significant challenges, including big data utilization, data security, privacy concerns, and the implementation of cloud computing systems. Furthermore, the research synthesizes current trends and proposes actionable recommendations for overcoming these challenges, such as adopting Health 5.0 and fostering integrated Community 5.0 systems. The study underscores the importance of maintaining the human aspect amidst technological advancements. Future research directions are outlined, focusing on the "big data-based society" within Society 5.0 to explore innovative solutions, mitigate barriers, and ensure sustainable digital transformation in healthcare services.
Financial Performance Assessment of Flat Buildings Using Life Cycle Cost and Cost–Benefit Analysis Velantika, Griselda Junianda; Mikhail, Reguel; Putri, Karina Meilawati Eka; Widowati, Elok Dewi; Alghiffary, Rizqi; Akbari, Muhamad Fauzan
Advance Sustainable Science Engineering and Technology Vol. 7 No. 1 (2025): 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.v7i1.1005

Abstract

Buildings resulting from construction projects are durable assets and decisions related to construction projects have enduring impacts. In many cases, building owners prioritize only the initial costs, such as building design, construction, and equipment costs, while neglecting the future operation and maintenance costs. This research studies life cycle costing (LCC) analysis to evaluate the financial feasibility of urban housing. The LCC calculates all the costs incurred and benefits during the building's operation. The cost is generated from construction, operational, and maintenance costs. At the same time, the benefit breaks down into flat rental costs, retail rental costs, and parking costs. The costs incurred are estimated over 25 years, and the parameters of feasibility are net Present Value (NPV), Benefit-Cost Ratio (BCR), and Internal Rate of Return (IRR). The study generates negative NPV, BCR < 1, and 0.61% of IRR. It indicates that the project is not feasible. This research gives alternatives to make the project feasible. This study employed a trial-and-error approach to ascertain the viability of investing in flat rentals by systematically adjusting rental rates. Incremental adjustments to rental rates are tested by a series of rate hikes of 50%, 100%, 150%, and 200% using a trial-and-error approach. The project will become feasible if the flat rate increases to 150-200% of the initial rental rate.
Non-Verbal Cues in Interactive Systems: Enhancing Proactivity through Winking and Turning Gestures Binti Anas, Siti Aisyah; Mazran bin Esro; Ahamed Fayeez bin Tuani Ibrahim; Yogan Jaya Kumar; Vigneswara Rao Gannapathy; Yona Falinie binti Abd Gaus; R. Sujatha
Advance Sustainable Science Engineering and Technology Vol. 7 No. 1 (2025): 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.v7i1.1011

Abstract

This investigation investigates the extent to which proactive behaviours in interactive objects—specifically animated eyes that exhibit behaviours such as blinking and turning—improve user interaction. Through a two-phase process, we investigate the influence of these behaviors on users’ perceptions of proactivity in both physical and virtual environments. In Phase I, we conducted a real-world study using a tangible box with animated eyes to evaluate user responses to expressive behaviours in single- and multi-person interactions. The results indicate that blinking significantly improves perceptions of the box’s intentionality and engagement, thereby fostering a more robust sense of proactivity. Phase II expands this investigation to a virtual environment, where 240 participants on Amazon Mechanical Turk (MTurk) participated, thereby validating the real-world findings. The online study confirms that perceived proactivity is consistently increased across contexts by blinking and turning. These findings indicate that integrating basic, human-like behaviors into interactive systems can enhance user engagement and provide practical advice for the development of sustainable, low-complexity interactive technologies. These discoveries facilitate the future development of resource-efficient and accessible human-computer interaction and robotic systems by simulating intentionality through minimal behavior.
Current Scenario of Maintenance 4.0 and Opportunities for Sustainability-Driven Maintenance Suhas H. Sarje; A. Kumbhalkar, Manoj; N. Washimkar, Dinesh; H. Kulkarni, Rajesh; D. Jaybhaye, Maheswar; Hussein Al Doori, Wadhah
Advance Sustainable Science Engineering and Technology Vol. 7 No. 1 (2025): 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.v7i1.1028

Abstract

Industry 4.0, a shift from Industry 3.0, aims to enhance productivity and efficiency in operations and supply chain management. Maintenance plays a crucial role in this process, and IoT-enabled (Ind. 4.0) condition monitoring is a key component of this technology. However, challenges persist in implementing effective IoT-enabled condition monitoring solutions. The triple bottom line perspective (Economical, Ecological, and Social) is also crucial for realizing Ind. 4.0. This paper investigates the state of IoT-enabled industrial condition monitoring (Maintenance 4.0) and sustainability-driven maintenance (Maintenance 5.0), focusing on the challenges associated with implementing these concepts. The IoT-enabled technologies are divided into three layers: the application layer, the networking layer, and the physical layer. The physical layer, the lowest layer, faces numerous challenges in realizing maintenance 4.0 effectively. A new system configuration for vibration-based condition monitoring in an Ind. 4.0 environment is proposed to address these shortcomings. Wi-Fi technology is found to be the best option for high-throughput communication needs in the current scenario. The literature review reveals that while the economic aspect of maintenance 5.0 has been thoroughly examined, the environmental and social aspects have not been thoroughly assessed. Future research should focus on developing a new sustainable maintenance model that incorporates IoT-enabled technologies and investigates sustainable performance indicators to understand sustainability aspects quantitatively.
Enhancing Security in Wireless Mesh Networks: A Deep Learning Approach to Black Hole Attack Detection Mansi Bhonsle; Gunji Sreenivasulu; Kilaru Chaitanya; Dhumpati Raghu; Gunti Surendra; Konduru Kranthi Kumar; Mandalapu Srinivasa Rao; Kandukuri Prabhakar; Vamsi Krishna Vuppu
Advance Sustainable Science Engineering and Technology Vol. 7 No. 1 (2025): 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.v7i1.1036

Abstract

Wireless Mesh Networks (WMNs) are susceptible to various security threats, including black hole attacks, where malicious nodes attract and drop packets, disrupting network communication. Traditional security mechanisms are often inadequate in detecting and mitigating these attacks due to their dynamic and evolving nature. In this paper, we propose a novel deep learning-based defense mechanism against black hole attacks in WMNs. It utilizes Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks to analyze network traffic patterns and detect abnormal behavior indicative of black hole attacks. The proposed approach offers several advantages, including the ability to adapt to new attack patterns and achieve high detection accuracy. The evaluations of this method using an NSL KDD   demonstrate its effectiveness in mitigating black hole attacks. Results indicate a significant improvement in attack detection rates compared to traditional rule-based systems, reducing both false positives and the overall impact of such attacks on network performance. The proposed solution not only strengthens WMN security but also has the potential to adapt to evolving attack strategies through continuous learning. This research paves the way for future advancements in adversarial learning and autonomous, self-healing security systems for mesh networks. It offers scalable solutions to secure critical infrastructure like smart cities and IoT ecosystems, ensuring reliable communication. Integrating Deep Learning Algorithms security in WMNs enhances resilience against evolving cyber threats in next-generation wireless networks.
Advancements and Challenges in Additive Manufacturing: Future Directions and Implications for Sustainable Engineering Mohammed, Raffi; Shaik, Abdul Saddique; Mohammed, Subhani; Bunga, Kiran Kumar; Aggala, Chiranjeevi; Babu, Bairysetti Prasad; Badruddin, Irfan Anjum
Advance Sustainable Science Engineering and Technology Vol. 7 No. 1 (2025): 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.v7i1.1079

Abstract

This study explores the recent advancements in additive manufacturing (AM) and its significant effects on various industries such as aerospace, automotive, medical, and casting. The research investigates how AM has the potential to enhance design flexibility, reduce weight, and optimize material performance through developments like adaptive algorithms, topology-based process planning, and multi-objective optimization techniques. These advancements have resulted in near-net-shape casting, improved surface finishes, and enhanced structural integrity. However, the widespread adoption of AM in the commercial sector faces challenges such as high costs, limited material compatibility, and inconsistent build quality. This paper assesses these limitations and suggests solutions such as enhanced design algorithms, AI-driven process monitoring, and the creation of sustainable materials to address them. By overcoming these barriers, AM can smoothly integrate into industrial environments and revolutionize manufacturing processes. The study emphasizes the importance of further exploration of AM's potential to drive innovation, sustainability, and productivity across different sectors.
Review of Reliability of Solar Hybrid Generator System as Temporary Power Supply for Offshore Industry for Sustainable Platform Application of Environmentally Friendly Energy Sources Alamsyah, Haryani; Ardiansyah; Sunardi
Advance Sustainable Science Engineering and Technology Vol. 7 No. 1 (2025): 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.v7i1.1116

Abstract

This paper discusses the application of two combined power generation systems namely generator and Solar Panel in improving the efficiency of offshore power supply during downtime. Ensuring reliable and sustainable power in remote and limited range environments is critical for sustainable platform maintenance and sustainability. Traditional power sources, such as diesel generators, although reliable, have high carbon emissions and operational costs. Solar energy, although environmentally friendly, faces spatial constraints in offshore. A hybrid system combines photovoltaic (PV) panels and conventional generators, which provides an optimal balance between renewable energy and reliability. This study focuses on the system design, operational benefits, and its impact on wellhead platform sustainability, highlighting its efficiency and environmental sustainability.
Optimizing Image Preprocessing for AI-Driven Cervical Cancer Diagnosis Chandra Prasetyo Utomo; Neng Suhaeni; Nashuha Insani; Elan Suherlan; Nunung Ainur Rahmah; Ahmad Rusdan Utomo; Indra Kusuma; Muhamad Fathurachman; Dewa Nyoman Murti Adyaksa
Advance Sustainable Science Engineering and Technology Vol. 7 No. 1 (2025): 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.v7i1.1128

Abstract

Cervical cancer ranks among the top causes of cancer-related deaths in women globally. Early detection is vital for improving patient survival rates. The multiclass classification of cervical cell images presents challenges primarily due to the notable variations in cell sizes across different classes. Conventional AI methods for diagnosing cervical cancer often rely on image-resizing techniques that overlook crucial features like relative cell dimensions, which impairs the models' ability to distinguish between classes effectively. This paper presents a novel AI-driven approach that employs constant padding to maintain the natural size differences among cells. Our method utilizes deep learning for both feature extraction and multiclass classification. We assessed the method using the publicly accessible SIPaKMeD dataset. Experimental findings indicate that our approach surpasses traditional image-resizing methods, especially in classes that are more challenging to predict. This strategy highlights AI's potential to improve cervical cancer diagnosis, offering a more precise and dependable tool for early detection. A reliable and precise AI model for diagnosing cervical cancer is crucial for promoting widespread screening and ensuring timely and effective treatment, which can ultimately lower mortality rates. By aiding early and accurate diagnosis, this approach aligns with global health efforts to alleviate the burden of cancer and other diseases, especially in areas with limited access to advanced healthcare services facilities.
Innovation of Artistic Gymnastics Equipment in Limited Space Tubagus Herlambang; Donny Anhar Fahmi; Utvi Hinda Zhannisa
Advance Sustainable Science Engineering and Technology Vol. 7 No. 1 (2025): 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.v7i1.1147

Abstract

This study was motivated by the limited space for men's artistic gymnastics in Central Java, which generally uses a small and unrepresentative school arena, so the arrangement of equipment such as uneven bars, parallel bars, rings and saddle horses is not optimal. The aim of this study is to develop innovative multifunctional artistic gymnastics equipment in a limited space to optimise the gross motor development of junior male artistic gymnasts and to improve the effectiveness and efficiency of training. The research method uses a research and development approach with quantitative data from expert questionnaires, athletes and coaches, as well as analysis of equipment innovation based on Computer Aided Design (CAD) technology. The results of the analysis showed the maximum stress on the developed equipment, namely single bars 45.7 MPa, parallel bars 72.6 MPa, straps 29.48 MPa and saddles 92.9 MPa, which are located at the ends near the pivot point. The results of the analysis showed that the Innovation products are safe to use. The conclusion the conclusion of this research is the creation of artistic gymnastics equipment innovation in a limited space that is feasible to use.

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