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asset@upgris.ac.id
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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 50 Documents
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Search results for , issue "Vol. 6 No. 4 (2024): August-October" : 50 Documents clear
Spatial Analysis of Waste Management Facility Distribution Using GIS Arsanti, Vidyana; Kharisma, Rizqi Sukma; Ardiansyah, Ivan; Nugroho, Bayu; Ihsan Fajruna, Muhammad; Zahra Deswanti, Luthfia; Fais Al Qori, Muhammad
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): 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.v6i4.996

Abstract

Recently, waste has become an extraordinary phenomenon that has attracted the attention of all levels of society: authorities, local governments, environmentalists, and regional stakeholders at the village level. Based on DIY Regional Regulation No. 3 of 2013 concerning the Management of Household Waste and Waste Similar to Household Waste and Sleman Regency Regional Regulation No. 6 of 2023 concerning the Implementation of Waste Management, efforts to minimize the amount of waste are made by each waste bank collaborating with TPS3R in Sleman Regency. Based on temporary data from 178 waste banks, there are 97 active waste banks and 32 TPS3R in Sleman Regency. The objectives of this study are (1) To determine the distribution pattern of active waste banks in Sleman Regency and (2) To determine the accessibility of active waste banks to TPS3R locations. This study uses the nearest neighbour analysis method, and the accessibility of active waste bank locations to TPS3R locations is measured using the buffering method—data processing using a Geographic Information System (GIS). The results of this study indicate (1) the distribution pattern of active waste banks in Sleman Regency based on the nearest neighbour ratio value is 0.861485 (<1), indicating a spatial pattern that tends to be clustered or spread in groups; (2) the accessibility of active waste banks to the TPS3R location has not shown an even pattern, from 32 TPS3R only 10 TPS3R have two waste banks, the rest 0 - 8 waste banks. The buffering distance shows that the closer the two locations are, the more effective and efficient waste management will be, with a maximum accessibility distance of 4.1 km.
Risk Mitigation Strategies for Sustainable Poultry Supply Chain Management Haswika; Agus Mansur; Meilinda F. N. Maghfiroh
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): 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.v6i4.997

Abstract

The livestock sector is an important pillar in providing animal protein and sustaining the rural economy. However, the sector faces major challenges from environmental and socio-economic issues, such as climate change and environmental degradation, which can threaten its sustainability. Negative impacts such as environmental contamination can reduce production quality and quantity and increase supply chain operational costs. This study aims to identify effective risk mitigation strategies to reduce these negative impacts and improve the sustainability of supply chain management. Data were collected from laying duck farms and analyzed using the House of Risk (HOR) method with a Phase 1 and 2 approach. This approach allows the identification of the most critical risks and risk agents and mapping mitigation priorities. Key findings indicate that providing drugs or vaccines to prevent animal virus outbreaks is the highest priority mitigation strategy, while strategic policy decision-making has the lowest priority. Overall, 15 risks and 21 risk agents were identified. This study implies that the implementation of effective mitigation strategies can significantly reduce operational risks, strengthen the resilience of the livestock sector, and support the sustainability of supply chain management as a whole.
Assessment of Abiotic Factors for Sea Turtle Nesting Suitability in Coastal Bays Ikegwu, Chukwudi; Nuryanto, Agus; Sastranegara, Moh. Husein
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): 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.v6i4.998

Abstract

Cilacap Bays, critical nesting areas for sea turtles, face growing habitat disturbances from tourism. However, studies on nesting suitability in these regions remain scarce. This research assesses the abiotic factors influencing sea turtle nesting in Cilacap Regency, Indonesia, across eight observation stations. Key ecological parameters—land surface temperature (28°C - 36.3°C), pH (mean 6.8), sand particle size (0.212-0.500 mm), beach slope (11.50%-20.99%), and beach width (28.8m-81.8m)—were evaluated. The results highlight Sidaurip Beach as the most suitable for nesting due to optimal environmental conditions, with Station (SP1) being particularly favorable for producing male hatchlings due to its suitable 28°C temperature. These findings suggest targeted egg relocation to SP1 could help address gender imbalances, ensuring long-term population sustainability. This research provides valuable insights for sea turtle conservation and supports future policy efforts to protect nesting sites in Cilacap amidst growing environmental pressures
Advances in Deep Learning for Skin Cancer Diagnosis Naeemah, Maysaa R.; Kamil, Mohammed
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): 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.v6i4.1002

Abstract

The most prevalent type of cancer worldwide is known as skin cancer. Early detection is critical because if left undiagnosed in the primary stage, it might be fatal. Although there are differences within the class and high inter-class similarities, it is too difficult to distinguish with the naked eye. Owing to the disease's global prevalence, a number of deep learning based automated systems were created thus far to help doctors identify skin lesions early on. Using pre-trained ImageNet weights and fine-tuning the Convolutional Neural Networks (CNNs), we trained VGG19 on the HAM10000 dataset. The optimal performance was observed with FT. The model that was created, which yielded an accuracy that was greater overall than the one used in transfer learning, was 82.4±1.9 %. By offering a second opinion and supporting the clinician's diagnosis, this performance could lower morbidity and treatment costs.
Utilizing Sequential Pattern Mining and Complex Network Analysis for Enhanced Earthquake Prediction Henri Tantyoko; Nurjanah, Dade; Rusmawati, Yanti
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): 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.v6i4.1003

Abstract

Earthquakes are natural events caused by the movement of the earth's plates, often triggered by the energy release from hot liquid magma. Predicting earthquakes is crucial for raising public awareness and preparedness in seismically active areas. This study aims to predict earthquake activity by identifying patterns in seismic events using Sequential Pattern Mining (SPM). To enhance the prediction accuracy, Sequential Rule Mining (SRM) is applied to derive rules with confidence values from these patterns. The results show that using betweenness centrality as a weight increases the prediction accuracy to 83.940%, compared to 78.625% without weights. Using eigenvector centrality as a weight yields an accuracy of 83.605%. These findings highlight the potential of using centrality measures to improve earthquake prediction systems, offering valuable insights for disaster preparedness and risk mitigation.
The Effects of Extraction Temperature on the Physicochemical Properties of Mangrove-Derived Glucomannan (Bruguiera gymnorhiza) Wibawanti, Jeki; Zulfanita; Norhaslinda Arun; Anang Mohamad Legowo; Sri Mulyani; Sapto Pamungkas
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): 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.v6i4.1026

Abstract

This study investigates the impact of different extraction temperatures on the physicochemical properties of glucomannan derived from mangrove fruits (Bruguiera gymnorhiza). Various extraction temperatures ranging from 45°C to 85°C were utilized. Significant differences (p < 0.05) were observed in solubility (58.41% ± 2.45), total reducing sugar content (0.39% ± 0.09), yield (35.13 ± 2.95), and L* color value (71.97 ± 1.53), while no significant differences (p > 0.05) were found in a* and b* color values. These findings have implications for expanding the applications of Bruguiera and advancing research on Bruguiera glucomannan. Scanning electron microscopy (SEM) analysis revealed an increase in the cross-linking density of glucomannan molecules.
Typology Model Based Building and Land Infrastructure Structure Organization and Duties Bali Area Police Ni Ketut Natalia Wulansari; I Nengah Sinarta; Agus Kurniawan
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): 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.v6i4.1053

Abstract

Polsek was a police station in the district that provides police services to the community. There are four types of Polsek, namely A, B, C, and D. Polsek in the Bali Area are 58 with types B and C. Polsek is expected to have adequate supporting infrastructure such as Integrated Police Service Center rooms, facilities for the disabled, children's playgrounds, breastfeeding rooms, detention cells, and parking, open spaces. However, the land area is only sometimes adequate. The analysis used interview methods, observation, literature studies, and SWOT analysis. The results show that Polsek's need for land Type B is 631.54 m2, and Type C is 377.14 m2. The SWOT analysis was in the strength and threat quadrant, so a policy is needed to evenly distribute the development of each Polsek type B and C, starting from land acquisition by the main tasks and functions of the police in serving the community.
Posthumanist Technologies in Business: AI and Cloud Computing for Global Optimization and Ethical Challenges Rodriguez Barboza, Jhonny Richard; Oscar David Carreño-Flores; Luis Miguel Davila-Zamora; Hans Manuel Jalixto-Erazo; Miguel Alfonso Oré de los Santos; Orlando John Cruces-Torres; Ricardo Edmundo Ruiz-Villavicencio; Danny Villegas-Rivas
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): 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.v6i4.1064

Abstract

. This study explores the integration of artificial intelligence (AI) and cloud computing within posthumanist technologies, focusing on their impact on business optimization and information security. A systematic review of 40 studies across sectors such as banking and retail highlights the benefits of AI in automating tasks and enhancing decision-making, while cloud computing provides flexibility and scalability. However, risks like data privacy issues, algorithmic bias, and cybersecurity vulnerabilities demand attention. The research emphasizes the need for ethical frameworks and security strategies to mitigate these risks. Additionally, it stresses the importance of equitable access to these technologies for small and medium-sized enterprises (SMEs) and marginalized communities. The study provides actionable recommendations for businesses and calls for future research on the long-term societal implications of these technologies
A New Approach to Measuring Institutional and Researcher Contributions to the SDGs: Combining Data from Elsevier SciVal and VOSviewer Pertiwi, Fungky Dyan; Anindito, Dhimas Cahyo; Habibi, Ilham; Saifudin; Munahar, Suroto; Purnomo, Bagiyo Condro; Fatimah, Yun Arifatul; Waluyo, Budi; Setiyo, Muji
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): 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.v6i4.1076

Abstract

The Sustainable Development Goals (SDGs), established by the United Nations in 2015, are a comprehensive global framework that addresses social, economic, and environmental challenges through sustainable development. This study examines the role of universities, specifically focusing on the Department of Mechanical Engineering at Universitas Muhammadiyah Magelang (UNIMMA), in contributing to the SDGs. The study utilized data from Elsevier’s SciVal to analyze the department’s contribution to the SDGs through scientific publications in the Scopus database. A total of 97 out of 156 articles published by nine researchers from the department were found to contribute to various SDGs, with a significant focus on Goals 7 (affordable and clean energy), 17 (partnerships for the goals), 9 (industry, innovation, and infrastructure), and 12 (responsible consumption and production). The study highlights the department’s collaborative efforts and alignment with global sustainability goals. In addition, VOSviewer was used to map the research collaboration network within the department, revealing strong contributions to energy efficiency, sustainable technologies, and climate action. However, the department's research shows limited contribution to social SDGs such as poverty alleviation and gender equality. By mapping the university’s contributions to the SDGs, this study helps faculty members identify opportunities for targeted research collaborations, address gaps in SDG contributions, and enhance partnerships with researchers from other institutions, thus broadening the university’s impact on global sustainable development goals.
Web Server Based Electrical Control System Analysis for Smart Buildings Masnur, Masnur; Alam, Syahirun
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): 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.v6i4.1120

Abstract

Energy management in smart buildings still faces challenges in optimizing energy use, particularly for high-load devices, such as HVAC systems and lighting. Conventional control systems are often inadequate for optimizing energy usage based on the operational needs of the building. This study aims to develop and analyze a web server-based electrical energy control system that can be accessed in real time to improve the energy efficiency of smart buildings. This study employed a quasi-experimental method by implementing a web server-based control system in a smart building and comparing the energy consumption before and after the application of the system. The results show that the system reduces the energy consumption by up to 25%, particularly for HVAC systems and lighting. The most significant energy savings occurred during off-peak hours, when the system automatically reduced power for unnecessary devices. The implications of this research suggest that a web server-based control system not only enhances energy efficiency and reduces operational costs, but also provides greater flexibility in energy management through more adaptive and responsive remote control. This research contributes to the development of more sustainable energy management technologies for smart buildings, with wide potential applications in commercial and institutional building scenarios

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