Making Tana Luwu the Mainstream Supporting the Economy of South Sulawesi

Firmanzah, Adi; Mustafa, Sri Wahyuni; Sanuddin, Salju

doi:10.38124/ijisrt/ijisrt20oct215

International Journal of Innovative Science and Research Techno

2020

DOI: 10.38124/ijisrt/ijisrt20oct215

|View full text |Cite

Making Tana Luwu the Mainstream Supporting the Economy of South Sulawesi

Adi Firmanzah,

Sri Wahyuni Mustafa,

Salju Sanuddin

Abstract: The purpose of this study was to determine, analyze and assess which sectors are the leading sectors in the four regions in Tana Luwu with the Location Qoutient (LQ) analysis approach. It was concluded that the economic potential of each region is different. East Luwu Regency has a base sector in mining and quarrying. North Luwu Regency has base sectors in agriculture, forestry and fisheries; electricity and gas procurement; government administration, defense and social security; and educational services. Palo… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article5

Relationship

Self Cite0

Independent5

Authors

Journals

Cited by 708 publications

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Molecular Classification with Graph ConvolutionalNetworks: Exploring the MUTAG Dataset for Mutagenicity Prediction

Pathak,

Desai,

Kela

et al. 2024

International Journal of Innovative Science and Research Techno

View full text Add to dashboard Cite

This paper presents the implementation of a Graph Convolutional Network (GCN) for the classification of chemical compounds using the MUTAG dataset, which consists of 188 ni- troaromatic compounds labeled according to their mutagenicity. The GCN model leverages the inherent graph structure of molec-ular data to capture and learn from the relationships between atoms and bonds, represented as nodes and edges, respectively. By utilizing three graph convolutional layers followed by a global mean pooling layer, the model effectively aggregates node features to generate meaningful graph-level representations. The model was trained using the Adam optimizer with a learning rate of 0.01, and cross-entropy loss was employed to supervise the classification task. The results demonstrate the efficacy of GCNs in graph classification tasks, with the model achieving a training accuracy of 79.33% and a test accuracy of 76.32%. This study highlights the potential of GCNs in cheminformatics and other domains where graph-structured data is prevalent, paving the way for further exploration and application of advanced graph neural networks in similar tasks.

show abstract

Molecular Classification with Graph ConvolutionalNetworks: Exploring the MUTAG Dataset for Mutagenicity Prediction

Pathak,

Desai,

Kela

et al. 2024

International Journal of Innovative Science and Research Techno

View full text Add to dashboard Cite

show abstract

Optimizing Supply Chain Management in Boiler Manufacturing through AI-enhanced CRM and ERP Integration

Saiteja Kalluri

2024

International Journal of Innovative Science and Research Techno

View full text Add to dashboard Cite

The boiler manufacturing industry faces unique challenges in supply chain management due to complex product specifications, stringent regulatory requirements, and fluctuating demand patterns. This paper presents an innovative approach to optimizing supply chain management in boiler manufacturing through the implementation of artificial intelligence (AI) enhanced Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP) integration. Our study employs a multi-faceted methodology, combining machine learning algorithms, predictive analytics, and natural language processing to create an intelligent system that seamlessly connects customer- facing CRM data with backend ERP processes. This AI- driven approach enables real-time decision making, predictive demand forecasting, and adaptive inventory management specifically tailored to the boiler manufacturing sector. The research demonstrates significant improvements in key performance indicators across the boiler manufacturing supply chain, including reduced lead times for custom boiler orders, optimized inventory levels for critical components, enhanced supplier relationship management for specialized parts, and increased customer satisfaction through improved order tracking and delivery precision. A case study of a mid- sized boiler manufacturer that implemented this AI- enhanced integration is presented, showcasing a 20% reduction in operational costs and a 18% increase in on- time deliveries over a 12-month period. Furthermore, we address industry-specific challenges such as regulatory compliance tracking, energy efficiency optimization, and integration with Industrial Internet of Things (IIoT) sensors for predictive maintenance. The findings of this study have significant implications for boiler manufacturing enterprises seeking to leverage AI and data integration to gain a competitive edge in supply chain management and meet the evolving demands of the energy sector.

show abstract

Climate Change and SADC`s Role in Malawi: A Brief Situational Analysis after Cyclone Freddy

Jaffar,

Nyengo Nkhoma

2024

International Journal of Innovative Science and Research Techno

View full text Add to dashboard Cite

The economic integration process of the Southern African Development Community is being affected by the damage caused by storms and floods in the region. The study looked at the role of the Southern African Development Community in the aftermath of Tropical Cyclone Freddy. The aim of the research is to provide an overview of the response of the Southern African Development Community to Cyclone Freddy in Malawi, based on secondary data published in newspapers, reports, articles and research papers. The need for assistance in the country increased because of the economic, social and infrastructural development that was affected by the storm. The study shows that the Southern African Development Community didn't play much of a role in providing emergency assistance. The study found that the Southern African Development Community has invested a lot in climate change and adaptation measures rather than responding quickly to the impact of storms in the country. The establishment of a good office in the Southern African Development Community would be important in the event of a storm in the region.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Making Tana Luwu the Mainstream Supporting the Economy of South Sulawesi

Cited by 708 publications

References 9 publications

Molecular Classification with Graph ConvolutionalNetworks: Exploring the MUTAG Dataset for Mutagenicity Prediction

Molecular Classification with Graph ConvolutionalNetworks: Exploring the MUTAG Dataset for Mutagenicity Prediction

Optimizing Supply Chain Management in Boiler Manufacturing through AI-enhanced CRM and ERP Integration

Climate Change and SADC`s Role in Malawi: A Brief Situational Analysis after Cyclone Freddy

Contact Info

Product

Resources

About