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Mega Novita
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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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Kota semarang,
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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 306 Documents
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Viscosity Modeling of MES and SLS Using Machine Learning Method Muhammad Taufiq Fathaddin; Rini Setiati; Fahrurrozi Akbar; Iwan Sumirat; Bharoto; Ranggi Sahmura Ramadhan; Onnie Ridaliani Prapansya; Arinda Ristawati
Advance Sustainable Science Engineering and Technology Vol. 8 No. 2 (2026): 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.v8i2.2304

Abstract

Viscosity is crucial to improve the efficiency of injected fluids for oil displacement in reservoirs. Traditionally, research has focused on polymers that help reduce the mobility of injected fluids, while surfactant viscosity has received less consideration. This research investigated the viscosity behavior of methyl ester sulfonate (MES) and sodium lauryl sulfate (SLS) surfactant solutions using a machine learning method—adaptive neurofuzzy inference system (ANFIS). This study aimed to predict the viscosity of surfactant solutions. Experimental data included viscosity measurements of 36 MES and SLS samples at various concentrations and temperatures, obtained by digitizing viscosity curves. These data served as input and validation for the ANN and ANFIS models. The results showed that ANFIS predicted viscosity values ​​reliably, yielding only 1.33% and 0.43% differences for MES and SLS, respectively. Comparison of viscosity prediction with Artificial Neural Network (ANN) showed that ANFIS prediction was better, because ANN yielded two deviating predictions.
EAZY Digital Accreditation System Evaluation and its Contribution to Digital Citizen: Evidence from POLTESA Runik Machfiroh; Akhmad Fauzi; Yusza Reditya Murti; Hasbi Syuhada
Advance Sustainable Science Engineering and Technology Vol. 8 No. 2 (2026): 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.v8i2.2517

Abstract

Accreditation processes in higher education institutions are often inefficient, particularly in border regions like Indonesia, where limited infrastructure and resources pose significant challenges. This study evaluates the EAZY Digital Accreditation System at POLTESA, a State Polytechnic in West Kalimantan one of border region of Indonesia. using a mixed-methods approach and Social Return on Investment (SROI) analysis to assess its operational and social impacts. The research combines qualitative stakeholder surveys with quantitative SROI metrics to measure efficiency gains and cost savings. Key findings reveal an SROI ratio of 3.948:1 in Year 1, increasing to 11.1:1 by Year 3, along with IDR 592 million in savings. The results highlight the system’s success in improving accreditation efficiency, offering valuable lessons in digital transformation. Furthermore, the implementation of the digital accreditation system enhances digital citizenship by fostering greater transparency, accountability, and participatory governance in educational institutions. These findings suggest that digital accreditation systems can be scaled to other institutions, bridging gaps in educational quality and supporting national resilience.
Design and Experimental Evaluation o`f a PID Based Ship Rudder Control Prototype Referenced to SOLAS Arif Rakhman Suharso Arif; Ario Hendartono; Amthori Anwar Amthori; Slamet Supriyadi
Advance Sustainable Science Engineering and Technology Vol. 8 No. 2 (2026): 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.v8i2.2739

Abstract

The Proportional–Integral–Derivative (PID)-based ship rudder control system is an effective method for maintaining a vessel’s heading automatically. This study aims to design and evaluate a ship rudder control prototype in accordance with SOLAS safety standards. The research method employed is Research and Development (R&D), which includes needs analysis, system design, prototype development, and model testing. The cargo ship prototype is equipped with an HMC5883L compass sensor, an Arduino microcontroller, and a servo motor as the rudder actuator. Data processing and PID algorithm implementation are carried out using Visual Basic software. The PID parameters used are Kp = 0.001, Ki = 0.001, and Kd = 0.2, obtained through a tuning process. Testing was conducted in a controlled pool under calm water conditions. The results show that the system achieves a steady-state condition in an average time of 21 seconds with minimal overshoot and small deviation from the setpoint, while complying with the SOLAS requirement of a maximum rudder angle of 35°.
Cam Simulation and Dimensional Verification of CNC-Machined Orthopaedic Femoral Components: Toolpath Optimization and 3D-Scan Metrology Yuris Setyoadi; Rifky Ismail; Athanasius Priharyoto Bayuseno; I Nyoman Jujur; Robin Novriansyah; Darmanto; Hartanto Prawibowo; Paulus Wisnu Anggoro
Advance Sustainable Science Engineering and Technology Vol. 8 No. 2 (2026): 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.v8i2.2760

Abstract

This study investigates the optimization of manufacturing femoral components for Total Knee Replacement (TKR) using Computer-Aided Manufacturing (CAM) simulation and 5-axis CNC milling, followed by dimensional verification based on 3D scanning. The machining process was simulated in Autodesk PowerMill to generate collision-free toolpaths for AISI 316L stainless steel. Dimensional verification was conducted by comparing the 3D-scanned physical model (using Creality CR-Scan Ferret Pro) with the original CAD model in Geomagic Control X. The metrological analysis showed a Root Mean Square (RMS) deviation of 0.5317 mm and an average positive deviation of 0.2572 mm. Spatial deviation analysis revealed significant dimensional variations, with a maximum deviation of +2.5761 mm and a minimum deviation of -2.5713 mm. Specifically, in critical functional regions, the medial and lateral condyles exhibited deviations ranging from -0.4683 mm to 0.232 mm, while the patellar groove showed a deviation of 0.1989 mm. Although the machining strategy successfully produced the complex implant geometry, the tolerance distribution data indicated that only 17.22% of the surface fell within the strictly specified tolerances, highlighting the need for further optimization of cutting parameters and fixturing strategies to minimize surface roughness and dimensional inaccuracies.
Altitude-dependent Variation in Antibacterial Properties of Red Ginger (Zingiber officinale var. rubrum): Implications for Natural Anti-Salmonella Agents Dyah Ayu Widyastuti; Tri Rini Nuringtyas; Abdul Rohman; Djoko Santosa
Advance Sustainable Science Engineering and Technology Vol. 8 No. 2 (2026): 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.v8i2.2781

Abstract

Red ginger contains diverse bioactive compounds with strong antioxidant and antibacterial activities. This study investigated the influence of growth location on the anti-Salmonella activity of red ginger extracts from seven regions in Java, Indonesia. The fractions were analyzed for total phenolic and flavonoid contents, as well as antioxidant capacity using DPPH and FRAP assays. Antibacterial activity was assessed against Salmonella using the Kirby-Bauer disk diffusion method. Results showed that methanol and ethyl acetate fractions exhibited the highest phenolic and flavonoid contents, while the chloroform fraction demonstrated the strongest radical scavenging activity. Extracts from Bumiaji and Lendah displayed the most potent anti-Salmonella activity (inhibition zone: 10.08 to 18.00 mm). These findings highlight that altitude and solvent polarity influence red ginger bioactivity, supporting its potential as a natural antibacterial source.
Data-Driven Techno-Behavioral Segmentation of Post-Pandemic Tourists Using TwoStep Cluster Analysis Radinal; Sigit Priyanto; Dewanti Dewanti
Advance Sustainable Science Engineering and Technology Vol. 8 No. 2 (2026): 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.v8i2.2950

Abstract

Post-pandemic tourism is characterized by increasing behavioral heterogeneity as digital technologies reshape travel planning and mobility practices, challenging traditional demographic-based segmentation. This study develops a techno-behavioral, data-driven segmentation framework within the Smart Tourism Ecosystem perspective by conceptualizing digital adoption as a mediating mechanism between socio-demographic attributes and travel behavior. Using survey data from 805 domestic tourists in Yogyakarta, Indonesia, TwoStep Cluster Analysis (log-likelihood distance; BIC-based cluster selection) identifies two distinct segments: Digital Leisure Travelers (DLT) and Budget-Conscious Digital Natives (BDN). The clustering solution demonstrates fair quality (Silhouette = 0.32). Predictor-importance and validation tests indicate that income, education, generational cohort, and digital application use are the strongest discriminators, while itinerary intensity differs significantly between clusters (p < 0.001; η² = 0.10). The findings highlight that widespread digital engagement produces differentiated mobility outcomes shaped by socio-economic capacity, emphasizing the need for segment-sensitive and inclusive smart tourism strategies.

Page 31 of 31 | Total Record : 306

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