Klaim Artikel Anda
Verifikasi kepemilikan artikel akademik
Apakah artikel-artikel ini milik Anda?
Daftarkan diri Anda sebagai author untuk mengklaim artikel dan dapatkan profil akademik terverifikasi dengan fitur lengkap.
Badge Verifikasi
Profil terverifikasi resmi
Statistik Lengkap
H-index, sitasi, dan metrik
Visibilitas Tinggi
Tampil di direktori author
Kelola Publikasi
Dashboard artikel terpadu
Langkah-langkah Klaim Artikel:
- 1. Daftar akun author dengan email akademik Anda
- 2. Verifikasi email dan lengkapi profil
- 3. Login dan buka menu "Klaim Artikel"
- 4. Cari dan klaim artikel Anda
- 5. Tunggu verifikasi dari admin (1-3 hari kerja)
Menampilkan 1751–1760 dari 15734 artikel
Bayesian Generalized Poisson Regression Modeling for Overdispersed Maternal Mortality Data
Advance Sustainable Science, Engineering and Technology
Vol 7
, No 3
(2025)
Maternal mortality is a global health issue that reflects disparities in access to and the quality of healthcare services. This study applies the Bayesian Generalized Poisson Regression (BGPR) approach to address the problem of overdispersion in the data, which renders the standard Poisson regression model less appropriate. The Generalized Poisson model was chosen for its ability to handle overdispersion, while the Bayesian approach provides more stable parameter estimates, particularly when wor...
Sumber Asli
Google Scholar
DOI
Fuzzy Logic-Based Clustering of Teacher Digital Pedagogy Using Cybergogy Framework for Sustainable Educational Innovation
Waryanto, Nur Hadi
; Retnawati, Heri
; Setyaningrum, Wahyu
; Insani, Nur
; Hery Murtianto, Yanuar
; Caturiyati, Caturiyati
; RR Rianto, Vivi
Advance Sustainable Science, Engineering and Technology
Vol 7
, No 3
(2025)
Rapid changes in educational technology necessitate innovative approaches to sustainable teacher development. However, implementing learning technologies like Cybergogy faces significant challenges due to imbalances in digital pedagogy competencies and motivation among secondary school mathematics teachers. This study aims to cluster mathematics teachers' profiles based on the Cybergogy model's application using the Fuzzy C-Means (FCM) algorithm. The study involved 88 mathematics teachers from v...
Sumber Asli
Google Scholar
DOI
Enhancing Biology Students’ Mastery of Animal Anatomy with a Web-Based Electronic Atlas: Toward Sustainable Digital Learning Tools
Advance Sustainable Science, Engineering and Technology
Vol 7
, No 3
(2025)
Learning animal anatomy in higher education often suffers from limitations in terms of visual media and practical time. Technology-based solutions such as web-based electronic atlases (e-atlases) can improve conceptual understanding and support digital continuous learning. This study aims to evaluate the effectiveness of web-based e-atlas in improving biology students' animal anatomy learning outcomes through a flipped classroom approach. This study used the ADDIE development model and a quasi-e...
Sumber Asli
Google Scholar
DOI
Digital Transformation of Import Logistics for Operational Efficiency: Case-Based Evidence from the Plastics Industry
Advance Sustainable Science, Engineering and Technology
Vol 7
, No 3
(2025)
This study aims to explore the use of digital systems to reduce import process costs, increase the percentage of national direct deliveries from ports to consumers, and analyze the impact of proposed improvement measures. The research employs a single case study approach with data collected through observation, document analysis, and quantitative data collection from one of the biggest plastic resin distribution companies in Indonesia. The data were analyzed using the CIMO (Context-Intervention-...
Sumber Asli
Google Scholar
DOI
Recent Advances in Catalytic Systems for the Sustainable Synthesis of Ethyl Levulinate from Biomass
Advance Sustainable Science, Engineering and Technology
Vol 7
, No 3
(2025)
The esterification of levulinic acid to ethyl levulinate presents challenges in catalyst efficiency, reusability, and environmentally friendly process design, restricting commercial scalability. This study examines recent studies on diverse catalysts, including Deep Eutectic Solvents (DES), homogeneous and heterogeneous systems, and their effects on yield. DES is positioned as a more sustainable option, with yields as high as 99.8%, quicker reaction times, and a lower environmental effect. Wh...
Sumber Asli
Google Scholar
DOI
Computational Assessment of Orthopedic Implant Durability Using Finite Element Analysis
Haryanto, Ismoyo
; Bagastomo, Riondityo Soni
; Ismail, Rifky
; Siregar, Januar Parlaungan
; Cionita, Tezara
Advance Sustainable Science, Engineering and Technology
Vol 7
, No 3
(2025)
Finite Element Analysis (FEA) provides a rapid and cost-effective method to evaluate orthopedic implants. This research investigates the mechanical performance and long-term durability of a seven-hole SS 316L Basic Fragment Set (BFS) reconstruction plate designed for pelvic fractures. Adhering to ASTM standards, material properties were defined via tensile testing (ASTM E8), while static and fatigue analyses were performed using a displacement control method in a four-point bending test setup in...
Sumber Asli
Google Scholar
DOI
Assessing the Feasibility of Small-Scale RDF Technology in Urban Solid Waste Management Using Cost-Benefit Analysis
Advance Sustainable Science, Engineering and Technology
Vol 7
, No 3
(2025)
The development of Waste Processing Facilities based on the 3R principles (TPS 3R) with small-scale Refuse Derived Fuel (RDF) technology in Jakarta aims to support waste sorting, composting, reuse, and recycling activities, with locations strategically placed as close as possible to service areas. However, its implementation faces significant challenges, particularly due to high initial investment and operational costs. This study evaluates the feasibility of four TPS 3R facilities using a Cost-...
Sumber Asli
Google Scholar
DOI
1 Sitasi
Mechanical Performance of Alkali-Treated Rattan Strips with Epoxy Coating for Sustainable Composite Applications
Kalatharan, Sujentheran Nair
; Imran, Al Ichlas
; Irawan, Agustinus Purna
; Siregar, Januar Parlaungan
; Cionita, Tezara
; Fitriyana, Deni Fajar
; Anis, Samsudin
; Dewi, Rozanna
; Setyoadi, Yuris
; Wisnu Prayogo
Advance Sustainable Science, Engineering and Technology
Vol 7
, No 3
(2025)
The use of natural materials like rattan in eco-friendly composites is gaining attention in materials engineering. However, its hydrophilic nature and interaction with other materials can affect mechanical strength. This study investigates how variations in rattan size and alkali treatment influence the tensile properties of single rattan strips through an epoxy dipping process. Rattan was prepared with varying lengths (5–15 cm), widths (3–8 mm), and a consistent thickness (0.5 mm). Alkali treat...
Sumber Asli
Google Scholar
DOI
1 Sitasi
Artificial Neural Network-Based Forecasting of Rice Yield Using Environmental and Agricultural Data
Advance Sustainable Science, Engineering and Technology
Vol 7
, No 3
(2025)
This study presents a high-accuracy predictive model for rice production in Indonesia using Artificial Neural Networks (ANN), achieving an R² of 98.11%, Mean Absolute Error (MAE) of 0.0966, and Mean Squared Error (MSE) of 0.0189. Climate variability remains a significant challenge to rice cultivation in regions like Malang City, where unpredictable environmental factors such as rainfall, temperature, and humidity hinder effective crop planning and yield estimation. To address this, we developed...
Sumber Asli
Google Scholar
DOI
1 Sitasi
Multi-Horizon Short-Term Residential Load Forecasting Using Decomposition-Based Linear Neural Network
Advance Sustainable Science, Engineering and Technology
Vol 7
, No 3
(2025)
Short-Term Load Forecasting is crucial for grid stability and real-time energy management, particularly in residential settings where consumption is highly volatile and influenced by behavioral and external factors. Traditional models struggle to capture complex, non-linear patterns. This study proposes a forecasting framework based on the DLinear model, which decomposes time series data into trend and seasonal components using a simple linear neural network architecture. Designed for multi-hori...
Sumber Asli
Google Scholar
DOI