Harnessing Big Data and AI for Predictive Insights: Assessing Bankruptcy Risk in Indonesian Stocks DOI
Maureen Marsenne, Tubagus Ismail, Muhamad Taqi

et al.

Data & Metadata, Journal Year: 2024, Volume and Issue: 3

Published: Dec. 31, 2024

Introduction: This research aims to investigate the use of financial Big Data and artificial intelligence (AI) in predicting bankruptcy risk companies listed on Indonesia Stock Exchange (BEI), with Altman Z-Score model as main framework. Objective: In this research, an intervening variable form data quality is introduced assess role mediation increasing accuracy predictions.. Method: The method used quantitative analytical Structural Equation Modeling Partial Least Squares (SEM-PLS), which allows analysis relationship between independent variables (Big AI), (quality data), dependent (bankruptcy prediction). Result: results show that integration AI significantly increases company predictions IDX, acting strengthens relationship. influence prediction through has also been proven provide more precise faster compared conventional model. Conclusion: These findings confirm a key factor must be considered optimizing capital market. implications for development technology (Fintech) management strategies public companies, especially identifying risks effectively by utilizing latest technology.

Language: Английский

Ethical Food Consumption in the Digital Age: Consumer Attitudes Towards Digitally Monitored Animal Welfare in Pork Products DOI Creative Commons
Heerah Jose, Elizabeth Jackson, Pham Bao Duong

et al.

Appetite, Journal Year: 2025, Volume and Issue: unknown, P. 107853 - 107853

Published: Jan. 1, 2025

Climate change is an emerging global reality with widespread effects on ecosystems and human communities. However, its significant impact livestock animals often goes underdiscussed as more focus given to of production climate change. Implementing high-welfare systems, such digital monitoring animals, can help mitigate climate-related challenges by reducing temperature fluctuations controlling disease spread. Despite the potential benefits, consumer acceptance this innovation remains uncertain. This study examines attitudes toward digitally monitored animal welfare practices, aiming understand their values they associate these practices. It investigates role technology in enhancing decision-making addressing concerns. Using means-end chain theory Schwartz's value typology, research explores motivational layers product attributes tied values. Semi-structured interviews twenty pork consumers revealed hierarchical relationships between attributes, Analysis through NVivo 14 LadderUX software generated themes a map. The findings indicate that prioritise diets, stress-free environments, humane processing health conditions, linking both ethical hedonic Intrinsic like appearance freshness are crucial for at-home consumption decisions, while sustainable packaging also plays role. found differences behavior based context, shifting restaurateurs when dining out. underscores importance transparency, quality influencing providing actionable insights marketing strategies promote improve standards.

Language: Английский

Citations

0
Malic acid- heat- treatment of proteins reduces methane and nitrogen emissions with improvement in growth, feed efficiency and nutrient utilization in Murrah buffalo (Bubalus bubalis) DOI Creative Commons
Shubham Thakur, Avijit Dey,

R.S. Berwal

et al.

Journal of Agriculture and Food Research, Journal Year: 2025, Volume and Issue: unknown, P. 101647 - 101647

Published: Jan. 1, 2025

Language: Английский

Citations

0
Development and Validation of Data Acquisition System for Real-Time Thermal Environment Monitoring in Animal Facilities DOI Creative Commons
Carlos Eduardo Alves Oliveira,

Thalya Aleixo Avelar,

Ilda de Fátima Ferreira Tinôco

et al.

AgriEngineering, Journal Year: 2025, Volume and Issue: 7(2), P. 45 - 45

Published: Feb. 17, 2025

In animal facilities, monitoring and controlling the thermal environment are essential in ensuring productivity sustainability. However, many production units face challenges implementing maintaining effective control systems. Given need for Smart Livestock Farming systems, this study aimed to develop validate an easy-to-use, low-cost embedded system (ESLC) real-time of dry-bulb air temperature (Tdb, °C) relative humidity (RH, %) facilities. The ESLC consists data collection/transmission modules a server Internet Things (IoT) storage. standard recording sensors (SRS) were installed prototype Over 21 days, their performance was evaluated based on Data Transmission Success Rate (DTSR, Interval (DTI, minutes). Additionally, agreement between SRS assessed using daily mean root square error (RMSE) (RE) across different Tdb RH ranges. successfully collected transmitted cloud server, achieving average DTSR 94.04% predominant DTI one minute. Regarding measurement agreement, distinct RMSE values obtained (0.26–2.46 (4.37–16.20%). Furthermore, four sensor exhibited RE below 3.00% all ranges, while showed progressively increasing as levels rose. Consequently, calibration curves established each module, high correlation raw corrected (determination coefficient above 0.98). It concluded that is promising solution enabling continuous reliable collection transmission.

Language: Английский

Citations

0
The role of ecosystem services in the pursuit of the doughnut economy – Implications for meat and dairy agroecosystems DOI
David Cook, Brynhildur Davíðsdóttir, Vincent Elijiah Merida

et al.

Ecosystem Services, Journal Year: 2025, Volume and Issue: 72, P. 101709 - 101709

Published: Feb. 24, 2025

Language: Английский

Citations

0
Context is key to understand and improve livestock production systems DOI Creative Commons
Clare E. Kazanski,

Mulubhran Balehegn,

Kristal Jones

et al.

Global Food Security, Journal Year: 2025, Volume and Issue: 45, P. 100840 - 100840

Published: March 18, 2025

Language: Английский

Citations

0
Mombaza (Panicum máximum), aplicación de varios niveles de gallinaza en pasto de corte tropical DOI Creative Commons
Pedro Pablo Cedeño Reyes,

Mishel Domenica Dillon Abarca,

Cristian Morales Alarcón

et al.

LATAM Revista Latinoamericana de Ciencias Sociales y Humanidades, Journal Year: 2024, Volume and Issue: 5(5)

Published: Oct. 19, 2024

El presente trabajo de investigación busca determinar el nivel gallinaza, en que se puede obtener un mayor rendimiento agronómico y mejor calidad nutricional del pasto mombasa. Se utilizó diseño bloques completamente al azar, hicieron cuatro grupos con repeticiones por grupo, a cada grupo adiciona una cantidad gallinaza: Grupo 1, 7Tm/Ha; 2, 6 Tm/Ha; 3, 5 4, o control, 0 Tm/Ha. Las variables campo estudiadas fueron altura la planta, ancho hoja, peso tallo, área raíz, biomasa, las laboratorio fueron, Proteína cruda, Fibra detergente neutra (FDN), acida (FDA), Lignina, Materia Seca (MS), Digestibilidad in-vitro MS, Extracto Etéreo (EE) determinación Ceniza. análisis estadístico realizó prueba ANOVA. Finalmente, este administró gallinaza presentó mayores variables: Ancho hoja 7 Tm/ Ha 1,51 ± 0,09 cm, Peso 1,90 1,46 g, tallo 4,11 1,04 Biomasa Tm/Ha 1993± 529,79 Kg, seca 21,71± 0,8 %, cruda 3,04%, 65,94± 1,37, Lignina 14,15± 0,64 (menor).

Citations

0
Harnessing Big Data and AI for Predictive Insights: Assessing Bankruptcy Risk in Indonesian Stocks DOI
Maureen Marsenne, Tubagus Ismail, Muhamad Taqi

et al.

Data & Metadata, Journal Year: 2024, Volume and Issue: 3

Published: Dec. 31, 2024

Introduction: This research aims to investigate the use of financial Big Data and artificial intelligence (AI) in predicting bankruptcy risk companies listed on Indonesia Stock Exchange (BEI), with Altman Z-Score model as main framework. Objective: In this research, an intervening variable form data quality is introduced assess role mediation increasing accuracy predictions.. Method: The method used quantitative analytical Structural Equation Modeling Partial Least Squares (SEM-PLS), which allows analysis relationship between independent variables (Big AI), (quality data), dependent (bankruptcy prediction). Result: results show that integration AI significantly increases company predictions IDX, acting strengthens relationship. influence prediction through has also been proven provide more precise faster compared conventional model. Conclusion: These findings confirm a key factor must be considered optimizing capital market. implications for development technology (Fintech) management strategies public companies, especially identifying risks effectively by utilizing latest technology.

Language: Английский

Citations

0