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 631–640 dari 5543 artikel
Hybrid Approaches for Advanced Medical Text Summarization: Combining TF-IDF, BERT, and Seq2Seq Models
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Clinicians, researchers, and healthcare professionals are confronted with the challenge of efficiently extracting relevant knowledge from vast amounts of textual data. Medical text summarization emerges as a crucial tool to address this challenge by condensing lengthy medical documents into concise, informative summaries. A comprehensive hybrid approach is proposed to address the challenges in medical text summarization by combining both extractive and abstractive methods, by integrating Term Fr...
Google Scholar
DOI
1 Sitasi
Evaluating Sustainable Waste Collection Models Using the Analytical Hierarchy Process (AHP): A Multi-Criteria Decision-Making Approach
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
The growing issue of disposable baby diaper waste requires an effective collection model to support sustainable waste management. This study designs a community-based collection model using the Analytical Hierarchy Process (AHP) method to identify the most effective approach. Three models are evaluated: Model 1 (Community-Based Diaper Bank), Model 2 (Scheduled Diaper Pick-Up Program), and Model 3 (Diaper Collection Points at Public Facilities). Results show Model 1 is the most effective, with th...
Google Scholar
DOI
Enhanced Air Quality Prediction Using AI: A Comparative Study of GRU, CNN, and XGBoost Models
Kayam Saikumar
; Munugapati Bhavana
; Rayudu Prasanthi
; Singaraju Suguna Mallika
; Deepthi Kamidi
; Naveen Malik
; Kapil Joshi
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Weather monitoring is vital due to environmental changes and rising air pollution, which affects health and lifestyles. Accurate air quality prediction models are essential yet challenging due to complex weather-pollution interactions. This study employs explainable deep learning and machine learning techniques—GRU, CNN, and XGBoost—on a custom dataset of 100,000 samples with 15 features, including PM2.5, PM10, humidity, and temperature. Using SHAP for interpretability, the GRU model outperforms...
Google Scholar
DOI
Association Between PAI-1 4G/5G Genetic Polymorphism and Uncontrolled Allergic Asthma
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Airway remodeling is a major challenge in the management of uncontrolled allergic asthma, despite standard therapy with a combination of inhaled corticosteroids (ICS) and long-acting bronchodilators (LABA). Increased levels of Plasminogen Activator Inhibitor-1 (PAI-1) are thought to play a role in this process, and the 4G/5G polymorphism in the PAI-1 gene is one of the genetic factors that affect it. This study aimed to analyze the association between the 4G/5G PAI-1 genetic polymorphism and unc...
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 (ASSET)
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...
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 (ASSET)
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...
Google Scholar
DOI
Optimizing Human Resource Performance in Building Construction through Technology-Enhanced Strategy Development
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Construction projects involve complex processes requiring effective management and skilled human resources to ensure successful outcomes. This study analyzes key factors influencing human resource (HR) performance in building construction, identifying ability, working conditions, organizational structure, motivation, discipline, and compensation as critical determinants. A structured questionnaire using a 5-point Likert scale was employed as the data collection instrument, distributed to 130 con...
Google Scholar
DOI
Comparative Analysis of Observed and Empirical Rainfall Distribution for Flood Hydrograph Modeling
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Flood disasters in Indonesia are persistent challenges during the rainy season, primarily due to intense rainfall and inadequate flood control. This study evaluates hourly rainfall to characterize hydrology and predict flood discharge more accurately, benefiting water infrastructure planning. The research used modified Mononobe methods, observational data, and rainfall-runoff modeling, including HEC-HMS simulations with the SCS-CN unit hydrograph. Observed rainfall simulated a flood discharge of...
Google Scholar
DOI
Biosorption of Chromiun in Batik Wastewater Using SCOBY Microbial Biomass: A Sustainable Bioremediation Approach
Nur Lu’lu Fitriyani
; Dina Adelia
; Slamet Budiyanto
; Ristiawati
; Jaya Maulana
; Muhammad Choiroel Anwar
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Batik wastewater poses an environmental threat due to hazardous heavy metals like lead, cadmium, and chromium (Cr). This study investigated the effectiveness of SCOBY (Symbiotic Culture of Bacteria and Yeast), a microbial consortium from kombucha production, in reducing Cr levels in batik wastewater. SCOBY is a promising biosorbent for heavy metals. The research aimed to assess SCOBY's ability to decrease Cr contamination in different types of batik wastewater (hand-drawn, stamped, and printed)...
Google Scholar
DOI
Predicting Habitat Suitability of Mahseer Fish (Tor spp.) in Tropical River Systems Using MaxEnt and Google Earth Engine: A Geospatial Modeling Approach
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 7
, No 3
(2025)
Rivers are vital freshwater habitats that face threats of degradation and climate change. Mahseer fish, a key species, is in decline. This study predicted Mahseer fish habitats in Central Java using the Google Earth Engine and the MaxEnt machine learning algorithm. Environmental predictors, including NDVI, elevation, slope, river order, temperature, and rainfall, were extracted from Sentinel, SRTM, MODIS, and CHIRPS data. The model identified river order as the most influential variable (73%), f...
Google Scholar
DOI