Pub Date : 2023-06-27DOI: 10.11113/oiji2023.11n1.247
Tengku Putri Nurain, Marwan Abdullah Hasan Al-Kubati, N. A. Abu Bakar
This study proposes a concept for establishing an Enterprise Architecture in the semiconductor manufacturing industry for equipment performance analysis using Internet of Things (IoT) technology. The plan is to implement The Open Group Framework approach as Enterprise Architecture in the manufacturing analytics department. The TOGAF approach improves data governance in the business process and analytics department. Manufacturing focuses on providing excellent and high-quality products to customers. As a result, the manufacturer must use a data analytics application to monitor the performance of the equipment. The performance of the equipment is monitored around the clock to ensure that it meets the requirements and does not exceed the threshold. The business process, data from the warehouse, and how it is processed will be discussed. Implementing Enterprise Architecture in manufacturing will also be discussed, focusing on the three layers of the TOGAF Architecture Development Method (ADM). The three layers are business, technology, and application. The Enterprise Architecture framework is a blueprint for the architecture used to align the business and information technology. Enterprise architecture optimises business processes and structures processes and functions to integrate information technology into the business. The proposed Enterprise Architecture for equipment performance analysis in the semiconductor manufacturing industry can be used as a guideline for implementing a comprehensive framework for tool performance monitoring.
{"title":"Enterprise Architecture for Equipment Performance Analysis Based on Internet of Things (IoT) Technology in the Semiconductor Manufacturing Industry","authors":"Tengku Putri Nurain, Marwan Abdullah Hasan Al-Kubati, N. A. Abu Bakar","doi":"10.11113/oiji2023.11n1.247","DOIUrl":"https://doi.org/10.11113/oiji2023.11n1.247","url":null,"abstract":"This study proposes a concept for establishing an Enterprise Architecture in the semiconductor manufacturing industry for equipment performance analysis using Internet of Things (IoT) technology. The plan is to implement The Open Group Framework approach as Enterprise Architecture in the manufacturing analytics department. The TOGAF approach improves data governance in the business process and analytics department. Manufacturing focuses on providing excellent and high-quality products to customers. As a result, the manufacturer must use a data analytics application to monitor the performance of the equipment. The performance of the equipment is monitored around the clock to ensure that it meets the requirements and does not exceed the threshold. The business process, data from the warehouse, and how it is processed will be discussed. Implementing Enterprise Architecture in manufacturing will also be discussed, focusing on the three layers of the TOGAF Architecture Development Method (ADM). The three layers are business, technology, and application. The Enterprise Architecture framework is a blueprint for the architecture used to align the business and information technology. Enterprise architecture optimises business processes and structures processes and functions to integrate information technology into the business. The proposed Enterprise Architecture for equipment performance analysis in the semiconductor manufacturing industry can be used as a guideline for implementing a comprehensive framework for tool performance monitoring.","PeriodicalId":379468,"journal":{"name":"Open International Journal of Informatics","volume":"28 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120913795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.11113/oiji2023.11n1.246
Nur Izwani Mohd Rahimi, Syukriah Mat Yatya, N. A. Abu Bakar
This paper examines the role of Enterprise Architecture (EA) in facilitating digital transformation for healthcare organisations, considering the expanding demand for a comprehensive blueprint to leverage information technology in achieving long-term strategic goals. Through a review of pertinent EA literature, this study investigates the applicability of EA and the Architecture Development Method (ADM) from TOGAF in healthcare. The article emphasises the benefits of employing TOGAF ADM as a proven EA methodology, which provides a systematic and precise step-by-step process for capturing an organisation's current and future states and identifying gaps between them. By adopting TOGAF ADM, healthcare organisations can employ decision-making and management analytic tools to expedite digital transformation. The primary objective is to develop a robust EA framework that facilitates the seamless transition from the existing baseline architecture to the desired target architecture while also addressing any identified voids. In addition, TOGAF ADM plays a crucial role in identifying areas where governance mechanisms may be absent, thereby enhancing alignment with system requirements, objectives, and stakeholder engagement. This research ultimately demonstrates the significance of Enterprise Architecture in facilitating digital transformation within the healthcare industry. By implementing TOGAF ADM, healthcare organisations can utilise EA to improve their operational efficiency, strategic decision-making, and overall performance. The study illuminates the critical role of enterprise architecture (EA) in designing and developing an effective healthcare architecture, enabling organisations to navigate the complexities of the digital landscape and leverage technology to meet their evolving requirements and aspirations.
{"title":"Enterprise Architecture: Enabling Digital Transformation for Healthcare Organization","authors":"Nur Izwani Mohd Rahimi, Syukriah Mat Yatya, N. A. Abu Bakar","doi":"10.11113/oiji2023.11n1.246","DOIUrl":"https://doi.org/10.11113/oiji2023.11n1.246","url":null,"abstract":"This paper examines the role of Enterprise Architecture (EA) in facilitating digital transformation for healthcare organisations, considering the expanding demand for a comprehensive blueprint to leverage information technology in achieving long-term strategic goals. Through a review of pertinent EA literature, this study investigates the applicability of EA and the Architecture Development Method (ADM) from TOGAF in healthcare. The article emphasises the benefits of employing TOGAF ADM as a proven EA methodology, which provides a systematic and precise step-by-step process for capturing an organisation's current and future states and identifying gaps between them. By adopting TOGAF ADM, healthcare organisations can employ decision-making and management analytic tools to expedite digital transformation. The primary objective is to develop a robust EA framework that facilitates the seamless transition from the existing baseline architecture to the desired target architecture while also addressing any identified voids. In addition, TOGAF ADM plays a crucial role in identifying areas where governance mechanisms may be absent, thereby enhancing alignment with system requirements, objectives, and stakeholder engagement. This research ultimately demonstrates the significance of Enterprise Architecture in facilitating digital transformation within the healthcare industry. By implementing TOGAF ADM, healthcare organisations can utilise EA to improve their operational efficiency, strategic decision-making, and overall performance. The study illuminates the critical role of enterprise architecture (EA) in designing and developing an effective healthcare architecture, enabling organisations to navigate the complexities of the digital landscape and leverage technology to meet their evolving requirements and aspirations.","PeriodicalId":379468,"journal":{"name":"Open International Journal of Informatics","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122766373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.11113/oiji2023.11n1.30
Ahmad Syafiq Ahmad Tamerin, Nur Azaliah Abu Bakar, N. H. Hassan, N. Maarop
Terrorism is the imminent threat that Malaysia and the entire world are facing nowadays. This has become a severe threat to Malaysia’s national security as extremist groups such as ISIS and DAESH are leveraging cyberspace to gain more supporters and sympathisers. These extremists used social media to disseminate their narratives among the Malaysian Armed Force (MAF) personnel to recruit them for their excellent military skills. Nevertheless, the current MAF counter-narrative is still using traditional media operations like roadshows, brochures dissemination, articles, and short videos in combating the terrorism agenda, which are less effective and time-consuming. Therefore, this study proposes an enhanced counter-terrorism approach to fight this terrorism narrative by utilising the MAF IT infrastructure to focus on the social media platform. The model was built based on ISO / IEC 27032:2012 standard, concerning three cyber-terrorism models. Six military IT experts then verified this new enhanced model. They agreed that it is crucial to establish such a model and emphasise that counter-terrorism effort needs full cooperation with other services and collegiality. This study’s final output is the Counter-Narrative Information Technology Model, which will later potentially be adopted to the MAF environment in line with the national inspiration in fighting terrorism.
{"title":"Counter-Narrative Cyber Security Model to Address the Issues of Cyber Terrorism","authors":"Ahmad Syafiq Ahmad Tamerin, Nur Azaliah Abu Bakar, N. H. Hassan, N. Maarop","doi":"10.11113/oiji2023.11n1.30","DOIUrl":"https://doi.org/10.11113/oiji2023.11n1.30","url":null,"abstract":"Terrorism is the imminent threat that Malaysia and the entire world are facing nowadays. This has become a severe threat to Malaysia’s national security as extremist groups such as ISIS and DAESH are leveraging cyberspace to gain more supporters and sympathisers. These extremists used social media to disseminate their narratives among the Malaysian Armed Force (MAF) personnel to recruit them for their excellent military skills. Nevertheless, the current MAF counter-narrative is still using traditional media operations like roadshows, brochures dissemination, articles, and short videos in combating the terrorism agenda, which are less effective and time-consuming. Therefore, this study proposes an enhanced counter-terrorism approach to fight this terrorism narrative by utilising the MAF IT infrastructure to focus on the social media platform. The model was built based on ISO / IEC 27032:2012 standard, concerning three cyber-terrorism models. Six military IT experts then verified this new enhanced model. They agreed that it is crucial to establish such a model and emphasise that counter-terrorism effort needs full cooperation with other services and collegiality. This study’s final output is the Counter-Narrative Information Technology Model, which will later potentially be adopted to the MAF environment in line with the national inspiration in fighting terrorism.","PeriodicalId":379468,"journal":{"name":"Open International Journal of Informatics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127364197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.11113/oiji2023.11n1.248
Yunnyzar Mohd Zain, N. A. Abu Bakar, Surya Sumarni Hussien
A company's architecture significantly affects how much it is worth. Enterprise Architecture (EA) is the term used to describe the ideas and standards that guide the execution of information, technology, and business mission in defence companies. The main objective is to align information technology and business strategy better. For this project, we selected Defence Technologies Sdn Bhd (DefTech) for the case study in implementing the EA. the purpose of this research is to include the as-is and to-be scenarios in detail of each division in the organisation by using DoDAF. DefTech is in the security and defence industry. The main aim is to implement Cybersecurity for data security and asset planning since they supply and produce armoured and logistic vehicles specifically for military and homeland security. The As-Is and To-Be scenarios for DefTech were explained, and data leak protection has been added as the future architecture for the organisation. The component will increase cybersecurity protection and traceability during data leakage. Implementing and enforcing a DoDAF standard reduces inefficiencies in enterprise security and identifies weaknesses. EA has shown potential utility for designing integrated architectures for a business on its own. Still, it can also act as the hub for other initiatives to govern the collaborative enterprise, particularly those centred on security.
{"title":"Implementing Cybersecurity In DefTech Sdn Bhd using DoDAF","authors":"Yunnyzar Mohd Zain, N. A. Abu Bakar, Surya Sumarni Hussien","doi":"10.11113/oiji2023.11n1.248","DOIUrl":"https://doi.org/10.11113/oiji2023.11n1.248","url":null,"abstract":"A company's architecture significantly affects how much it is worth. Enterprise Architecture (EA) is the term used to describe the ideas and standards that guide the execution of information, technology, and business mission in defence companies. The main objective is to align information technology and business strategy better. For this project, we selected Defence Technologies Sdn Bhd (DefTech) for the case study in implementing the EA. the purpose of this research is to include the as-is and to-be scenarios in detail of each division in the organisation by using DoDAF. DefTech is in the security and defence industry. The main aim is to implement Cybersecurity for data security and asset planning since they supply and produce armoured and logistic vehicles specifically for military and homeland security. The As-Is and To-Be scenarios for DefTech were explained, and data leak protection has been added as the future architecture for the organisation. The component will increase cybersecurity protection and traceability during data leakage. Implementing and enforcing a DoDAF standard reduces inefficiencies in enterprise security and identifies weaknesses. EA has shown potential utility for designing integrated architectures for a business on its own. Still, it can also act as the hub for other initiatives to govern the collaborative enterprise, particularly those centred on security.","PeriodicalId":379468,"journal":{"name":"Open International Journal of Informatics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134072183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.11113/oiji2023.11n1.250
Muhammad Umar Diginsa, Y. Md Yusof, A. Azizan, Suriani Mohd Sam, Noor Azurati Ahmad, H. Abas, S. Yuhaniz, M. Z. Adam
At present, people in the countryside use a manual agricultural machine for harvesting. This contributes to global warming and agricultural safety problems as manual irrigation increases farmers' time on the farm. The use of manual machinery causes smoke during irrigation, which increases the heating of the earth's surface and thus reduces the green energy effect. So they do not spend a lot of money on buying crude oil when they use the system. On the other hand, there are bandits who come into conflict with farmers and animals that attack farmers in the bush, which makes it difficult for farmers to reach their farms. A simple but effective IoT system, as we have proposed in this study, helps to solve these problems to a large extent. In this study, we use a combination of a Raspberry Pi as the main processor and sensor modules as devices to collect agricultural data for further insights and analysis. Apart from automatic irrigation through the power-saving water pump, the developed systems have taken the initiative to reduce the time farmers have to spend on the farm and provide instant notifications to a mobile device at any time and place.
{"title":"Low-cost IoT-Based Smart Notification System for Rural Agriculture","authors":"Muhammad Umar Diginsa, Y. Md Yusof, A. Azizan, Suriani Mohd Sam, Noor Azurati Ahmad, H. Abas, S. Yuhaniz, M. Z. Adam","doi":"10.11113/oiji2023.11n1.250","DOIUrl":"https://doi.org/10.11113/oiji2023.11n1.250","url":null,"abstract":"At present, people in the countryside use a manual agricultural machine for harvesting. This contributes to global warming and agricultural safety problems as manual irrigation increases farmers' time on the farm. The use of manual machinery causes smoke during irrigation, which increases the heating of the earth's surface and thus reduces the green energy effect. So they do not spend a lot of money on buying crude oil when they use the system. On the other hand, there are bandits who come into conflict with farmers and animals that attack farmers in the bush, which makes it difficult for farmers to reach their farms. A simple but effective IoT system, as we have proposed in this study, helps to solve these problems to a large extent. In this study, we use a combination of a Raspberry Pi as the main processor and sensor modules as devices to collect agricultural data for further insights and analysis. Apart from automatic irrigation through the power-saving water pump, the developed systems have taken the initiative to reduce the time farmers have to spend on the farm and provide instant notifications to a mobile device at any time and place. ","PeriodicalId":379468,"journal":{"name":"Open International Journal of Informatics","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131396453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.11113/oiji2023.11n1.245
Maisa Mubarak Said AlKharbush, Mahmoud Hamed Zohdi Mahmoud, N. A. Abu Bakar
This paper reviews the use of Enterprise Architecture (EA) for strategic performance management in the transport sector's digital transformation, focusing on the Balanced Scorecard (BSC) theory. EA is essential for strategic planning and performance management in the transport industry, which is vital to the economy. The study analyses academic publications, industry reports, and case studies to assess EA's benefits, drawbacks, and novel solutions in transportation. The Balanced Scorecard framework, which measures and manages performance holistically, should be used to align EA projects. EA and the Balanced Scorecard theory may provide a solid foundation for strategic performance management in the transportation sector's digital transition. It aligns goals, objectives, and KPIs with strategic vision and mission. EA also helps identify important capabilities, processes, and IT systems to accomplish desired results. It also improves decision-making by offering an integrated perspective of the organisation's resources, capabilities, and dependencies. In the transportation industry, EA for strategic performance management faces obstacles, including imprecise communication, insufficient governance, and limited planning. Innovative solutions, including improved communication channels, stronger governance systems, and enhanced planning techniques, are recommended to tackle these issues. This review analysis sheds light on the transport sector's digital transition using EA and the Balanced Scorecard theory. It advises researchers, practitioners, and policymakers to use EA to improve performance management and maintain transportation industry growth.
{"title":"A Review of Enterprise Architecture for Strategic Performance Management in the Transportation Sector Digital Transformation","authors":"Maisa Mubarak Said AlKharbush, Mahmoud Hamed Zohdi Mahmoud, N. A. Abu Bakar","doi":"10.11113/oiji2023.11n1.245","DOIUrl":"https://doi.org/10.11113/oiji2023.11n1.245","url":null,"abstract":"This paper reviews the use of Enterprise Architecture (EA) for strategic performance management in the transport sector's digital transformation, focusing on the Balanced Scorecard (BSC) theory. EA is essential for strategic planning and performance management in the transport industry, which is vital to the economy. The study analyses academic publications, industry reports, and case studies to assess EA's benefits, drawbacks, and novel solutions in transportation. The Balanced Scorecard framework, which measures and manages performance holistically, should be used to align EA projects. EA and the Balanced Scorecard theory may provide a solid foundation for strategic performance management in the transportation sector's digital transition. It aligns goals, objectives, and KPIs with strategic vision and mission. EA also helps identify important capabilities, processes, and IT systems to accomplish desired results. It also improves decision-making by offering an integrated perspective of the organisation's resources, capabilities, and dependencies. In the transportation industry, EA for strategic performance management faces obstacles, including imprecise communication, insufficient governance, and limited planning. Innovative solutions, including improved communication channels, stronger governance systems, and enhanced planning techniques, are recommended to tackle these issues. This review analysis sheds light on the transport sector's digital transition using EA and the Balanced Scorecard theory. It advises researchers, practitioners, and policymakers to use EA to improve performance management and maintain transportation industry growth.","PeriodicalId":379468,"journal":{"name":"Open International Journal of Informatics","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122950588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.11113/oiji2023.11n1.235
Amarmeet Kaur, Medzhakhed Usama, Doris Wong Hooi Ten, Nur Liana Majid, N. Maarop
The framework of metadata governance is a subset of the primary data governance framework implementation within an enterprise. Metadata management helps identify data provenance and destination systems, explain the categories of data in the system, and assist organisations in comprehending the elucidation of data in various structures. This study aims to construct a literature review on metadata governance including the overview, the definition and proposed work based on previous study in different industries related with metadata governance. According to DAMA-DMBOKv2, five activities are required to establish metadata management which are designing metadata strategy, understanding metadata needs, defining metadata architecture, producing and managing metadata, and querying, reporting, and analysing metadata. Three planning procedures for metadata management includes developing metadata strategy activities, identifying metadata needs, and designing metadata architecture. The metadata management industry would benefit from a comprehensive and effective data stewardship framework to maximise company economic value. An enterprise requires a metadata governance framework, which includes an assessment of metadata responsibilities, life cycles, and statistics, as well as how various business activities incorporate metadata. A metadata strategy guarantees that an organisation's whole data ecology is consistent.
{"title":"Literature Review on Metadata Governance","authors":"Amarmeet Kaur, Medzhakhed Usama, Doris Wong Hooi Ten, Nur Liana Majid, N. Maarop","doi":"10.11113/oiji2023.11n1.235","DOIUrl":"https://doi.org/10.11113/oiji2023.11n1.235","url":null,"abstract":"The framework of metadata governance is a subset of the primary data governance framework implementation within an enterprise. Metadata management helps identify data provenance and destination systems, explain the categories of data in the system, and assist organisations in comprehending the elucidation of data in various structures. This study aims to construct a literature review on metadata governance including the overview, the definition and proposed work based on previous study in different industries related with metadata governance. According to DAMA-DMBOKv2, five activities are required to establish metadata management which are designing metadata strategy, understanding metadata needs, defining metadata architecture, producing and managing metadata, and querying, reporting, and analysing metadata. Three planning procedures for metadata management includes developing metadata strategy activities, identifying metadata needs, and designing metadata architecture. The metadata management industry would benefit from a comprehensive and effective data stewardship framework to maximise company economic value. An enterprise requires a metadata governance framework, which includes an assessment of metadata responsibilities, life cycles, and statistics, as well as how various business activities incorporate metadata. A metadata strategy guarantees that an organisation's whole data ecology is consistent.","PeriodicalId":379468,"journal":{"name":"Open International Journal of Informatics","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115690827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.11113/oiji2023.11n1.244
Amna Sakinah binti Azmi, N. A. A. Bakar, Surya, Sumarni Hussien
Investment companies need to keep up with emerging technologies if they want to remain competitive. If this pattern persists, the investment industry could lose many customers. Several reports stress the importance of rethinking the business model of the investing industry in the Fourth Industrial Revolution. Enterprise architecture is the way to go when controlling an organisation's information technology systems' structure, behaviour, and interconnections. Organisational activities and data flows can be better managed with the help of enterprise architecture. This study aims to help readers comprehend the investing business by delving into its fundamental ideas, advantages, disadvantages, and potential application settings. Enterprise architecture is how a business should run and how many components should collaborate. An all-encompassing architectural framework addressing enterprise IT, application software, and infrastructure are included in this analysis. The proposed design is aimed to facilitate the investment firm's incorporation of state-of-the-art technologies.
{"title":"A Quick Start Approach of Enterprise Architecture Implementation in the Investment Industry Sector","authors":"Amna Sakinah binti Azmi, N. A. A. Bakar, Surya, Sumarni Hussien","doi":"10.11113/oiji2023.11n1.244","DOIUrl":"https://doi.org/10.11113/oiji2023.11n1.244","url":null,"abstract":"Investment companies need to keep up with emerging technologies if they want to remain competitive. If this pattern persists, the investment industry could lose many customers. Several reports stress the importance of rethinking the business model of the investing industry in the Fourth Industrial Revolution. Enterprise architecture is the way to go when controlling an organisation's information technology systems' structure, behaviour, and interconnections. Organisational activities and data flows can be better managed with the help of enterprise architecture. This study aims to help readers comprehend the investing business by delving into its fundamental ideas, advantages, disadvantages, and potential application settings. Enterprise architecture is how a business should run and how many components should collaborate. An all-encompassing architectural framework addressing enterprise IT, application software, and infrastructure are included in this analysis. The proposed design is aimed to facilitate the investment firm's incorporation of state-of-the-art technologies.","PeriodicalId":379468,"journal":{"name":"Open International Journal of Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125099708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.11113/oiji2023.11n1.242
Surenthiran Krishnan, Pritheega Magalingam, Roslina Ibrahim
Heart disease is one of the leading causes of death globally, which takes 17.9 million lives each year. The existing heart disease prediction techniques have a gap that does not consider the smoking attributes from the heart disease data. So, the accuracy is based on the limited number of medical data and the deep learning model. The existing deep learning models which use the Recurrent Neural Network (RNN) for heart disease prediction consume more processing and analysing time, mainly due to the delay of data retrieval. This delay causes the prediction process to become slower and leads to a moderate prediction only. The backpropagation of the RNN with an update gate and internal memory to carry the updated data cause a minor data glitch that leads to lower accuracy. Therefore, an efficient heart disease prediction model is very crucial to provide early detection among patients. This research proposes a Heart Disease Risk Prediction Model (HDRPM) with an enhanced RNN to improve the prediction accuracy using Framingham heart disease datasets. The specificity and sensitivity are imposed to improve the quality of the predictions. Sensitivity measure is used for detecting patients with heart disease perfectly and specificity measure is used for detecting patients without the disease perfectly. Besides the accuracy and quality of the prediction problem, the imbalance of minority classes in the dataset occurred in most deep learning prediction fields. This research aims to improve the quality of imbalanced Framingham datasets using Synthetic Minority Over-sampling Technique (SMOTe), which will synthetic instances in a small class to be equalized. The existing RNN model faces vanishing gradients that impede the learning of long data sequences. These gradients that carry information in the RNN cells will become smaller gradually till it minimises the parameter updates and leads to poor learning. For this purpose, the presence of multiple Gated Recurrent Unit (GRU) is used to overcome the vanishing gradients and ensure the hidden layers. The neurons of RNN rapidly cater for the essential information during the training and validation phase of the HDRPM. The integration of multiple GRU with the RNN, operating on the Tensorflow as back-end and Keras as the core for the neural network library has increased the performance of the proposed model. The proposed model provides up to 98.78%, the highest accuracy achieved compared to related previous work, which is a quantum neural network model with 98.57. This HDRPM is expected to significantly contribute to early detection of heart disease patients.
{"title":"Enhanced Recurrent Neural Network (RNN) For Heart Disease Risk Prediction Using Framingham Datasets","authors":"Surenthiran Krishnan, Pritheega Magalingam, Roslina Ibrahim","doi":"10.11113/oiji2023.11n1.242","DOIUrl":"https://doi.org/10.11113/oiji2023.11n1.242","url":null,"abstract":"Heart disease is one of the leading causes of death globally, which takes 17.9 million lives each year. The existing heart disease prediction techniques have a gap that does not consider the smoking attributes from the heart disease data. So, the accuracy is based on the limited number of medical data and the deep learning model. The existing deep learning models which use the Recurrent Neural Network (RNN) for heart disease prediction consume more processing and analysing time, mainly due to the delay of data retrieval. This delay causes the prediction process to become slower and leads to a moderate prediction only. The backpropagation of the RNN with an update gate and internal memory to carry the updated data cause a minor data glitch that leads to lower accuracy. Therefore, an efficient heart disease prediction model is very crucial to provide early detection among patients. This research proposes a Heart Disease Risk Prediction Model (HDRPM) with an enhanced RNN to improve the prediction accuracy using Framingham heart disease datasets. The specificity and sensitivity are imposed to improve the quality of the predictions. Sensitivity measure is used for detecting patients with heart disease perfectly and specificity measure is used for detecting patients without the disease perfectly. Besides the accuracy and quality of the prediction problem, the imbalance of minority classes in the dataset occurred in most deep learning prediction fields. This research aims to improve the quality of imbalanced Framingham datasets using Synthetic Minority Over-sampling Technique (SMOTe), which will synthetic instances in a small class to be equalized. The existing RNN model faces vanishing gradients that impede the learning of long data sequences. These gradients that carry information in the RNN cells will become smaller gradually till it minimises the parameter updates and leads to poor learning. For this purpose, the presence of multiple Gated Recurrent Unit (GRU) is used to overcome the vanishing gradients and ensure the hidden layers. The neurons of RNN rapidly cater for the essential information during the training and validation phase of the HDRPM. The integration of multiple GRU with the RNN, operating on the Tensorflow as back-end and Keras as the core for the neural network library has increased the performance of the proposed model. The proposed model provides up to 98.78%, the highest accuracy achieved compared to related previous work, which is a quantum neural network model with 98.57. This HDRPM is expected to significantly contribute to early detection of heart disease patients.","PeriodicalId":379468,"journal":{"name":"Open International Journal of Informatics","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132452814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-27DOI: 10.11113/oiji2023.11n1.249
Muhammad Azlan Bakar, Y. Md Yusof, Suriani Mohd Sam, A. Azizan, Noor Azurati Ahmad, H. Abas, N. Shafie
Waste management is one of the serious issues in maintaining the longevity of life. Managing waste in garbage bins not only requires a systematic garbage segregation policy but also a prevention and control mechanism for human behaviour. With the aid of the low-cost-budget Internet of Things (IoT) approach, managing garbage bins for municipal and town councils become practical, effective, and easy to be enforced. This study proposed a proof-of-concept prototype of a low-cost IoT approach using Raspberry Pi and cheap sensor modules to segregate waste into garbage bins with local alarming and remote notification systems. The systems are capable of detecting metal and non-metal waste so that segregation can be applied, and measuring waste levels in the garbage bin to prevent waste overflow. On top of that, the systems are also able to warn with loudness sound of a mistype waste scanned at the bin lid and send prompt notifications to the remote observer for further actions. The study results from a number of performance testing demonstrated the developed systems can accurately measure waste levels either to be empty, half-filled, or 80% filled when the ultrasonic ranging module sensor is placed 105° inside the bin. This is the best positioning we recommended when working with a bin of size 15 cm in height and 10 cm in width. Finally, we observed that the finest detection results were achieved when the movement of objects are scanned less than 2 cm, but not more than 4 cm away.
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