Komparasi Data Mining Naive Bayes dan Neural Network memprediksi Masa Studi Mahasiswa S1 by Azahari Azahari, Yulindawati Yulindawati, Dewi Rosita, Syamsuddin Mallala

“…The research results show the many weaknesses of the results of prediction of Naive bayes because the level of accuracy of its validity is not high. The evaluation and analysis process are conducted to see where the errors and truths are in the results of the study period predictions. …”
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Does fiscal decentralization foster renewable electricity generation? A panel data study of OECD countries by Serhiy Lyeonov, Oksana Okhrimenko, Artem Artyukhov, Mariia Saiensus, Iuliia Myroshnychenko, Yuliia Yehorova, Oleksii Havrylenko

“…Utilizing a panel dataset of 34 countries spanning 2000–2023, the analysis employs a fixed-effects regression model with Driscoll-Kraay standard errors. …”
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High-Resolution Mapping of Litter and Duff Fuel Loads Using Multispectral Data and Random Forest Modeling by Álvaro Agustín Chávez-Durán, Miguel Olvera-Vargas, Inmaculada Aguado, Blanca Lorena Figueroa-Rangel, Ramón Trucíos-Caciano, Ernesto Alonso Rubio-Camacho, Jaqueline Xelhuantzi-Carmona, Mariano García

“…This paper introduces a novel method for mapping the spatial distribution of litter and duff fuel loads using data collected by unmanned aerial vehicles. The approach leverages a very high-resolution multispectral data analysis within a machine learning framework to achieve precise and detailed results. …”
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Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology by Elliot Gould, Hannah S. Fraser, Timothy H. Parker, Shinichi Nakagawa, Simon C. Griffith, Peter A. Vesk, Fiona Fidler, Daniel G. Hamilton, Robin N. Abbey-Lee, Jessica K. Abbott, Luis A. Aguirre, Carles Alcaraz, Irith Aloni, Drew Altschul, Kunal Arekar, Jeff W. Atkins, Joe Atkinson, Christopher M. Baker, Meghan Barrett, Kristian Bell, Suleiman Kehinde Bello, Iván Beltrán, Bernd J. Berauer, Michael Grant Bertram, Peter D. Billman, Charlie K. Blake, Shannon Blake, Louis Bliard, Andrea Bonisoli-Alquati, Timothée Bonnet, Camille Nina Marion Bordes, Aneesh P. H. Bose, Thomas Botterill-James, Melissa Anna Boyd, Sarah A. Boyle, Tom Bradfer-Lawrence, Jennifer Bradham, Jack A. Brand, Martin I. Brengdahl, Martin Bulla, Luc Bussière, Ettore Camerlenghi, Sara E. Campbell, Leonardo L. F. Campos, Anthony Caravaggi, Pedro Cardoso, Charles J. W. Carroll, Therese A. Catanach, Xuan Chen, Heung Ying Janet Chik, Emily Sarah Choy, Alec Philip Christie, Angela Chuang, Amanda J. Chunco, Bethany L. Clark, Andrea Contina, Garth A. Covernton, Murray P. Cox, Kimberly A. Cressman, Marco Crotti, Connor Davidson Crouch, Pietro B. D’Amelio, Alexandra Allison de Sousa, Timm Fabian Döbert, Ralph Dobler, Adam J. Dobson, Tim S. Doherty, Szymon Marian Drobniak, Alexandra Grace Duffy, Alison B. Duncan, Robert P. Dunn, Jamie Dunning, Trishna Dutta, Luke Eberhart-Hertel, Jared Alan Elmore, Mahmoud Medhat Elsherif, Holly M. English, David C. Ensminger, Ulrich Rainer Ernst, Stephen M. Ferguson, Esteban Fernandez-Juricic, Thalita Ferreira-Arruda, John Fieberg, Elizabeth A. Finch, Evan A. Fiorenza, David N. Fisher, Amélie Fontaine, Wolfgang Forstmeier, Yoan Fourcade, Graham S. Frank, Cathryn A. Freund, Eduardo Fuentes-Lillo, Sara L. Gandy, Dustin G. Gannon, Ana I. García-Cervigón, Alexis C. Garretson, Xuezhen Ge, William L. Geary, Charly Géron, Marc Gilles, Antje Girndt, Daniel Gliksman, Harrison B. Goldspiel, Dylan G. E. Gomes, Megan Kate Good, Sarah C. Goslee, J. Stephen Gosnell, Eliza M. Grames, Paolo Gratton, Nicholas M. Grebe, Skye M. Greenler, Maaike Griffioen, Daniel M. Griffith, Frances J. Griffith, Jake J. Grossman, Ali Güncan, Stef Haesen, James G. Hagan, Heather A. Hager, Jonathan Philo Harris, Natasha Dean Harrison, Sarah Syedia Hasnain, Justin Chase Havird, Andrew J. Heaton, María Laura Herrera-Chaustre, Tanner J. Howard, Bin-Yan Hsu, Fabiola Iannarilli, Esperanza C. Iranzo, Erik N. K. Iverson, Saheed Olaide Jimoh, Douglas H. Johnson, Martin Johnsson, Jesse Jorna, Tommaso Jucker, Martin Jung, Ineta Kačergytė, Oliver Kaltz, Alison Ke, Clint D. Kelly, Katharine Keogan, Friedrich Wolfgang Keppeler, Alexander K. Killion, Dongmin Kim, David P. Kochan, Peter Korsten, Shan Kothari, Jonas Kuppler, Jillian M. Kusch, Malgorzata Lagisz, Kristen Marianne Lalla, Daniel J. Larkin, Courtney L. Larson, Katherine S. Lauck, M. Elise Lauterbur, Alan Law, Don-Jean Léandri-Breton, Jonas J. Lembrechts, Kiara L’Herpiniere, Eva J. P. Lievens, Daniela Oliveira de Lima, Shane Lindsay, Martin Luquet, Ross MacLeod, Kirsty H. Macphie, Kit Magellan, Magdalena M. Mair, Lisa E. Malm, Stefano Mammola, Caitlin P. Mandeville, Michael Manhart, Laura Milena Manrique-Garzon, Elina Mäntylä, Philippe Marchand, Benjamin Michael Marshall, Charles A. Martin, Dominic Andreas Martin, Jake Mitchell Martin, April Robin Martinig, Erin S. McCallum, Mark McCauley, Sabrina M. McNew, Scott J. Meiners, Thomas Merkling, Marcus Michelangeli, Maria Moiron, Bruno Moreira, Jennifer Mortensen, Benjamin Mos, Taofeek Olatunbosun Muraina, Penelope Wrenn Murphy, Luca Nelli, Petri Niemelä, Josh Nightingale, Gustav Nilsonne, Sergio Nolazco, Sabine S. Nooten, Jessie Lanterman Novotny, Agnes Birgitta Olin, Chris L. Organ, Kate L. Ostevik, Facundo Xavier Palacio, Matthieu Paquet, Darren James Parker, David J. Pascall, Valerie J. Pasquarella, John Harold Paterson, Ana Payo-Payo, Karen Marie Pedersen, Grégoire Perez, Kayla I. Perry, Patrice Pottier, Michael J. Proulx, Raphaël Proulx, Jessica L Pruett, Veronarindra Ramananjato, Finaritra Tolotra Randimbiarison, Onja H. Razafindratsima, Diana J. Rennison, Federico Riva, Sepand Riyahi, Michael James Roast, Felipe Pereira Rocha, Dominique G. Roche, Cristian Román-Palacios, Michael S. Rosenberg, Jessica Ross, Freya E. Rowland, Deusdedith Rugemalila, Avery L. Russell, Suvi Ruuskanen, Patrick Saccone, Asaf Sadeh, Stephen M. Salazar, Kris Sales, Pablo Salmón, Alfredo Sánchez-Tójar, Leticia Pereira Santos, Francesca Santostefano, Hayden T. Schilling, Marcus Schmidt, Tim Schmoll, Adam C. Schneider, Allie E. Schrock, Julia Schroeder, Nicolas Schtickzelle, Nick L. Schultz, Drew A. Scott, Michael Peter Scroggie, Julie Teresa Shapiro, Nitika Sharma, Caroline L. Shearer, Diego Simón, Michael I. Sitvarin, Fabrício Luiz Skupien, Heather Lea Slinn, Grania Polly Smith, Jeremy A. Smith, Rahel Sollmann, Kaitlin Stack Whitney, Shannon Michael Still, Erica F. Stuber, Guy F. Sutton, Ben Swallow, Conor Claverie Taff, Elina Takola, Andrew J. Tanentzap, Rocío Tarjuelo, Richard J. Telford, Christopher J. Thawley, Hugo Thierry, Jacqueline Thomson, Svenja Tidau, Emily M. Tompkins, Claire Marie Tortorelli, Andrew Trlica, Biz R. Turnell, Lara Urban, Stijn Van de Vondel, Jessica Eva Megan van der Wal, Jens Van Eeckhoven, Francis van Oordt, K. Michelle Vanderwel, Mark C. Vanderwel, Karen J. Vanderwolf, Juliana Vélez, Diana Carolina Vergara-Florez, Brian C. Verrelli, Marcus Vinícius Vieira, Nora Villamil, Valerio Vitali, Julien Vollering, Jeffrey Walker, Xanthe J. Walker, Jonathan A. Walter, Pawel Waryszak, Ryan J. Weaver, Ronja E. M. Wedegärtner, Daniel L. Weller, Shannon Whelan, Rachel Louise White, David William Wolfson, Andrew Wood, Scott W. Yanco, Jian D. L. Yen, Casey Youngflesh, Giacomo Zilio, Cédric Zimmer, Gregory Mark Zimmerman, Rachel A. Zitomer

“…Abstract Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. …”
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Research progress on the application of digital technology in the diagnosis and treatment of tooth wear by HE Yi, WANG Dingjie, XIAO Yuhong

“…Deep learning technology can also achieve image recognition and automated analysis to reduce human error and improve diagnostic efficiency, while quantitative analysis techniques guide clinical decision-making by more accurately calculating the tooth volume, surface area, and wear depth. …”
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Ultra-short-term Multi-region Power Load Forecasting Based on Spearman-GCN-GRU Model by Junying WU, Xin LU, Hong LIU, Bin ZHANG, Shouliang CHAI, Yunchun LIU, Jianan WANG

“…To improve the prediction accuracy of multi-region power load, an ultra-short-term multi-region power load forecasting model based on Spearman-GCN-GRU is proposed with focus on the spatial-temporal correlation analysis of multi-region power data. Firstly, the Spearman correlation coefficient is used to analyze the spatial-temporal correlation of power load in different regions and construct the Spearman adjacency matrix. …”
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End-to-end data extraction framework from unstructured geotechnical investigation reports via integrated deep learning and text mining techniques by Jimin Park, Wanhyuk Seo, Tae Sup Yun

“…The proposed framework efficiently extracts data from the test set within seconds without errors. …”
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Confidence interval estimation for the difference of censored zero-inflated gamma distributions by Hongping Guo, Yiran Zhu, Yuhang Qian, Min Wu

“…Furthermore, we conduct Monte Carlo simulations to evaluate the performances of the proposed methods, the results indicate that all CI construction methods achieve satisfactory performances in terms of coverage probability, average length and tail error rates. Finally, we perform real data analysis using 11 years of precipitation data from Zhengzhou and Lhasa.…”
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Finding a Bravais lattice with higher symmetry from lattice parameters of a supercell by Yoyo Hinuma, Hiroyuki Ozaki

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Adaptive ensemble spatial analysis by Alvaro F. Egaña, María Jesús Valenzuela, Mohammad Maleki, Juan F. Sánchez-Pérez, Gonzalo Díaz

“…It aims to provide a methodology that is as data-driven as possible, useful for a more general geoscientific (or expert) audience, and capable of providing quality estimates without the need for specific classical geostatistical expertise, such as variographic analysis. …”
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Large Scale Asset Detection Within Railway Scene Point Cloud Data From Mobile Laser Scanning by Bram Ton, Rick Akster

“…The analysis indicates that the largest contribution to this error originates from the random error. …”
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A hybrid deep learning framework for short-term load forecasting with improved data cleansing and preprocessing techniques by Muhammad Sajid Iqbal, Muhammad Adnan, Salah Eldeen Gasim Mohamed, Muhammad Tariq

“…The process unfolds with data collection, followed by rigorous standardization, preprocessing, and cleansing of demand and generation data. …”
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Investigating pediatric nurses’ perceptions of factors contributing to MAEs at Yendi hospital, Ghana by Ruth Nimota Nukpezah, Nathaniel Awenlesakba Anyaba, Wahab Osman

“…Abstract Background Medication administration errors (MAEs) are a critical concern in pediatric healthcare, contributing to adverse drug events (ADEs) and negatively impacting patient health. …”
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Impact of log file source and data frequency on accuracy of log file-based patient specific quality assurance by Akbar Azzi, Gerd Heilemann, Dietmar Georg, Supriyanto Ardjo Pawiro, Terry Mart, Wolfgang Lechner

“…Furthermore, all doses calculated using Linac log files and OIS log data had a GPR >90% for an RMS error < 3.3 mm. Based on these findings, a tolerance limit of RMS error of 3.3 mm for considering OIS log based PSQA was established. …”
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Data driven models for predicting pH of CO2 in aqueous solutions: Implications for CO2 sequestration by Mohammad Rasool Dehghani, Moein Kafi, Hamed Nikravesh, Maryam Aghel, Erfan Mohammadian, Yousef Kazemzadeh, Reza Azin

“…The boosted trees model optimized with grid search was found to estimate all data points with a residual error of less than 0.15 and an absolute relative error of 4.62 %. …”
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Diagnostic Challenges and Patient Safety: The Critical Role of Accuracy &amp;ndash; A Systematic Review by Alharbi TAF, Rababa M, Alsuwayl H, Alsubail A, Alenizi WS

“…The results of this review indicate that using AI tools, improving clinician training, and creating standardized diagnostic procedures may help reduce diagnostic errors; however, because of the small dataset and lack of meta-analysis, the findings should be interpreted cautiously. …”
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Arctic Sea Ice Surface Temperature Retrieval from FengYun-3A MERSI-I Data by Yachao Li, Tingting Liu, Zemin Wang, Mohammed Shokr, Menglin Yuan, Qiangqiang Yuan, Shiyu Wu

“…Compared with the original algorithm, the developed algorithm has higher accuracy and reliability. The sensitivity analysis shows that the atmospheric water vapor content with an error of 20% may lead to an IST retrieval error of less than 1.01 K.…”
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Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study by Xin Xiong, Linghui Xiang, Litao Chang, Irene XY Wu, Shuzhen Deng

“…We constructed four models with different combinations of predictors: (1) model BE, combining the Baidu index and environmental factors data; (2) model IB, combining mumps incidence and Baidu index data; (3) model IE, combining mumps incidence and environmental factors; and (4) model IBE, integrating all 3 data sources. …”
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A data driven machine learning approach for predicting and optimizing sulfur compound adsorption on metal organic frameworks by Mohsen Shayanmehr, Sepehr Aarabi, Ahad Ghaemi, Alireza Hemmati

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City-scale high-resolution flood models and the role of topographic data: a case study of Kathmandu, Nepal by C. Scott Watson, Januka Gyawali, Maggie Creed, John R. Elliott

“…Our analysis demonstrated that mapping city-scale flood inundation required hydrologically conditioned high-resolution topographic data but not physically complex flood models, highlighting the need for greater availability of high quality open access topographic data.…”
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