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1. Social Network Analysis of Cryptocurrency using Business Intelligence Dashboard

Author

Jonathan C. Setyono, William S. Suryawidjaja, and Abba S. Girsang

Subjects
business intelligence, cryptocurrency, social network analysis, social media., Technological innovations. Automation, HD45-45.2
Abstract

There are currently more than 10.000 cryptocurrencies available to buy from the online market, with a vast range of prices for each coin it sells. The fluctuation of each coin is affected by any social events or by several important companies or people behind it. The aim of this research is to compare three cryptocurrencies, which are Bitcoin, Ethereum, and Binance Coin, using Social Network Analysis (SNA) by visualizing them using Business Intelligence (BI Dashboard). This study uses the SNA parameters of degree, diameter, modularity, centrality, and path length for each network and its actors and their actual market price by crawling(data collecting process) from Twitter as one of the social media platforms. From the research conducted, the popularity of cryptocurrencies is affected by their market price and the activeness of their actors on social media. These results are important because they could help in the decision-making to buy cryptocurrencies with high popularity on social media because they tend to retain their value over time and could benefit from price spikes from influential people. Doi: 10.28991/HIJ-2022-03-02-09 Full Text: PDF

Published
2022
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24. Non-linear Ensemble Modeling for Multi-step Ahead Prediction of Treated COD in Wastewater Treatment Plant

Author

Abba, S. I., Elkiran, Gozen, Nourani, Vahid, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Aliev, Rafik A., editor, Pedrycz, Witold, editor, Jamshidi, Mo, editor, Babanli, Mustafa B., editor, and Sadikoglu, Fahreddin M., editor

Published
2020
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28. Novel Ensemble Machine Learning Paradigms for the Prediction of Antioxidant Activity of Bryophyllum pinnatum(Lam.) Oken

Author

Abdulrahman, Mahmoud Dogara, Usman, A. G., Ozsahin, Dilber Uzun, Ibrahim, Abdullahi Umar, and Abba, S. I.

Abstract

For herbal and modern drug research, secondary metabolites produced by plants are a valuable source of pharmaceutically active compounds. Northern Nigeria relies heavily on plants as a source of medication. Succulent perennial herb Bryophyllum pinnatumis endemic to Africa and Asia. The current study investigates the in vitro pharmacological potential of the B. pinnatumwith the use of predictive data intelligence algorithms to unveil the inhibitory properties of the plant. In vitro biological evaluation of B. pinnatumwas carried out. This study explored the utilization of four different data intelligence models composing of two linear models; multi-linear regression (MLR) and step-wise linear regression (SWLR) as well two other nonlinear artificial intelligence (AI)-based models; adaptive neuro-fuzzy inference system (ANFIS) and support vector machine (SVM). Subsequently, four ensemble machine learning approaches including adaptive neuro-fuzzy inference system ensemble (ANFIS-E), support vector machine ensemble (SVM-E), simple average ensemble (SAE) and Gaussian process regression ensemble (GPR-E) were proposed to increase the single model’s accuracy. The ensemble techniques depict an average fitness of 0.999 in both training and testing stages. Moreover, recent and state-of-the-art visualization illustrations were also used for easy grasping and assimilations of the findings. The data-driven approach obtained results showed the AI-based model’s potentiality including SVM and ANFIS in outperforming the classical linear models; SWLR and MLR according to the study's performance metrics. Furthermore, based on the DC assessment criteria investigated in the current work, ensemble machine learning paradigms increased the performance skills of the single algorithms by up to 27% in the testing phase.

Published
2024
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40. ERP systems in HEI context from a multiple perspective view : a case study

Author

?Abba¯s, Muh?ammad, Wood-Harper, Trevor, and Wood, Bob

Subjects
378, ERP Systems, benefits, HEI, Challenges, Impacts
Abstract

Enterprise Resource planning has gained prominence in the field of IS literature and is a significant phenomenon in practice in organizations and now also in higher educational institutions. These Institutions have their own unique method of operation and infrastructural facilities; and one of the biggest single most expenditure made by them is in their Enterprise Resource Planning Systems. The drive towards ERP is based on a desire to rationalize and streamline information systems across the whole organization seeking both improvement and business benefits. The ERP systems combine all discrete information into a single, integrated, real-time database. In the HEI context the ERP systems are seen as software solutions that address the diverse needs by tightly integrating all departments and functions within a single computer system configuration to serve particular needs such as students systems which manage all the student records/data and VLE systems like Blackboard which is a course management system. ERP addresses the institutions needs by providing a better service to its various users. The aim of this research study is to explore the quality, impact, benefits, utility and challenges of ERP systems specifically the student systems and VLE Blackboard in a Higher Educational Institution and analyse these ERP systems from a multiple perspective. The ERP systems have been applied by many Educational Institutions around the world as a key part of their organizational infrastructure and these systems tend to have a long life cycle in organizational use. The requirement is for the smooth functioning and utilization of these ERP systems while taking into consideration the changing demands as universities operate in a dynamic environment where there is a rapid change in technology. Millions of pounds and extensive deliberation is made on the implementation of the ERP system on the basis of expectations to align the institution objectives with business needs. This presents a huge challenge, if not properly addressed may lead to heavy investment without the corresponding institution efficiency.

Published
2011

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