Information Assets Research Articles

Security Quality Measurement Based on ISO/IEC 25023 Quality Model Case Study: Hospital Management Information System

Hospitals need to protect the security of data assets, where data assets are an important part of the continuity of hospital operations. In connection with the protection of data and information assets in the hospital, it has become a requirement for the hospital information technology team to carry out a security audit of the hospital management information system (HMIS). In this study, we measured the quality of the HMIS software in X Hospital using ISO 25023 which focused on the security aspects of the outpatient service module and drug services in the outpatient pharmacy unit. The security aspect based on the ISO 25023 standard consists of five main characteristics, namely: confidentiality, integrity, non-repudiation, accountability and authenticity. In the early stages, calculations are carried out to find the value of each measurement standard which is denoted by (X). The X value is based on the standard calculation range of values 0 and 1. The threshold value is determined at 0.80 to categorize the point quality whether it is not good or has met the ISO 25023 quality point. The results of software quality measurements show Internal Data Corruption Prevention is worth 0.75 and is at below a predetermined threshold value. Based on these results, it is recommended to improve one of them by replication the database to minimize the possibility of Internal Data Corruption Prevention. In this study, all aspects of software quality have an average value above the threshold, so it can be concluded that HMIS in RS X meets ISO 25023 standards.

Rapid remote volcanic ashfall impact assessment for the 2022 eruption of Hunga volcano, Tonga: a bespoke approach and lessons identified

When disasters occur, rapid impact assessments are required to prioritise response actions, support in-country efforts and inform the mobilisation of aid. The 15 January 2022 eruption of Hunga volcano, Tonga, and the resulting atmospheric shockwave, ashfall, underwater mass disturbance and tsunami, caused substantial impacts across the Kingdom of Tonga. Volcanic impacts on the scale observed after the eruption are rare, necessitating a reliance on international advice and assistance. The situation was complicated by the loss of Tonga’s international submarine fibreoptic cable (causing a complete loss of communications for approximately 20 days) along with border closures due to the COVID-19 pandemic. A need emerged for a rapid remote volcanic impact assessment and provision of specialist advice to help inform the response of international partners. Here we present a novel methodology for conducting rapid remote volcanic ashfall impact assessments, conducted over a 10-day period following the eruption. We used three different hazard models for ashfall thickness across the main island of Tongatapu and available asset information and vulnerability functions for buildings, agriculture, electricity networks, water supply and roads, to provide initial estimates of losses due to ashfall from the 15 January eruption. For buildings, we estimated losses both as total losses and as percentages of the total replacement cost of buildings on Tongatapu. For agriculture, we made probabilistic estimates of production losses for three different crop classes. For ashfall clean-up, we estimated ranges of ashfall volumes requiring clean-up from road surfaces and roofs. For water supply, electricity networks and roads, our analysis was limited to assessing the exposure of important assets to ashfall, as we had insufficient information on system configurations to take the analysis further. Key constraints on our analysis were the limited nature of critical infrastructure asset inventories and the lack of volcanic vulnerability models for tropical regions including Pacific Island nations. Key steps towards iteratively improving rapid remote impact assessments will include developing vulnerability functions for tropical environments as well as ground-truthing estimated losses from remote approaches against in-person impact assessment campaigns.

Village Asset Management Policy Implementation In Galagamba Village, Ciwaringin District, Cirebon Regency

This study aims to analyze the management of village assets in Galagamba Village, Ciwaringin District, Regency. In the context of village development, effective asset management is essential to improve community welfare. The research method used is a combination of qualitative and quantitative approaches, with data collection through in-depth interviews, questionnaires, observation, and document analysis. The results showed that village asset management still faces various challenges, including low community participation, weak accountability, and lack of transparency in asset information management. In addition, many assets are poorly inventoried and in need of repair. The impact of this suboptimal management is seen in the social and environmental welfare of the community. Based on the findings, it is recommended to increase the capacity of human resources, open space for community participation, and apply the principle of transparency in asset management. This research provides important insights for village governments in formulating more effective and sustainable policies for village asset management in the future.

Artificial intelligence in healthcare facilities asset information management: mixed review

Healthcare facilities are pivotal in ensuring continuous access to services, particularly for individuals with complex health conditions. Effective asset information management (AIM) in these facilities through artificial intelligence (AI) can enhance operational efficiency. The exploratory bibliometric and systematic review assesses the status and trends of AI applications in AIM within healthcare facilities. The findings reveal a significant gap between research findings and practical implementation, highlighting the need for further integration and real-world usage of AI-powered solutions in healthcare facilities settings. This study identified notable gaps, including the need for research on utilising AI to enhance asset management in healthcare, including maintenance scheduling and procurement processes. Involving stakeholders, such as healthcare professionals, facility managers, and patients, in effective facility management using AI requires further investigation. Research is needed to evaluate the economic benefits and develop robust ethical guidelines for responsible AI implementation. Notably, previous research has given limited attention to AI for healthcare AIM, with emerging trends focusing more on AI and infrastructure than the ‘asset’ aspect. Implementing AI-powered solutions tailored to the unique needs of healthcare facilities and evaluating cost-effectiveness will lead to improved asset management practices, enhanced decision-making processes, and, ultimately, more efficient and effective healthcare operations.

Realizing the Promise of Digital Engineering: Planning, Implementing, and Evolving the Ecosystem

ABSTRACTGaining benefits of digital engineering is not only about implementing digital technologies. An ecosystem for innovation is a system of systems in its own right, only partly engineered, subject to risks and challenges of evolving socio‐technical systems. This paper summarizes an aid to planning, analyzing, implementing, and improving innovation ecosystems. Represented as a configurable model‐based reference pattern used by collaborating INCOSE working groups, it was initially applied in targeted INCOSE case studies, and subsequently elaborated and applied to diverse commercial and defense ecosystems. Explicating the recurrent theme of consistency management underlying all historical engineering, it is revealing of digital engineering's special promise, and enhances understanding of historical as well as future engineering and life cycle management. It includes preparation of human and technical resources to effectively consume and exploit digital information assets, not just create them, capability enhancements over incremental release trains, and evolutionary steering using feedback and group learning.

Diversification of Taro Commodity-Based Derivative Products To Increase Community Income in Gunajaya Village, Tasikmalaya District

The constraints of local food development are the lack of derivative products that are easily accepted, accessible to the community and the implementation is not optimal. The purpose of Community-Based empowerment with the scope of Community Partnership Empowerment (PbM-PkM) is to empower the community through partners KWT Teratai and Poktan Kertaraharja III Gunajaya Village, Manonjaya District, Tasikmalaya to increase the diversification of derivative products from Talas Pratama to increase community income. This activity was carried out from May to December 2024. Gunajaya Village is the centre of Talas Pratama producers with productivity/ha around 30-40 tonnes, but most of it is sold raw so that the added value is low. There is an effort to diversify Talas Pratama into several derivative products, but until now it is still constrained by limited knowledge and skilled personnel to process products. This activity uses methods of socialisation, counselling, product processing diversification training, evaluation, grant assistance and mentoring. This activity has had an impact on the socio-economic conditions of the participants in the form of psychological assets, informational assets, organizational assets, material assets, financial assets, and human assets. Partners have produced various taro derivative products including taro flour which is processed into Cilok, Crackers, Bolu, Perkedel

INFORMATION ASSET PROTECTION IN ACCOUNTING: ANALYZING CORPORATE GOVERNANCE AND RISK MANAGEMENT THROUGH A BIBLIOMETRIC LENS

This paper deals with the protection of information assets related to accounting, based on bibliometric analysis involving 333 articles from the Web of Science. The five clusters that had been targeted by this research included: Corporate Governance and Board Characteristics (Cluster 1); Financial and Performance Metrics (Cluster 2); Accounting Standards and Reporting (Cluster 3); Risk Management and Disclosure (Cluster 4); Information Quality and Investor Protection (Cluster 5). It aims to define the current boundaries of the literature, identify main tendencies, and give a view on the future course of research. Bibliometric and content analysis methods were applied in the study to certain articles, and the relevance and impact were identified by the data obtained in the period between the years 2007–2024. Consequently, this chapter presents a broad-based analysis of how corporate governance ensures and drives information protection, the presentation of financial metrics internally within the organization, the importance of accounting standards, and the effectiveness of risk management and disclosure practices. The findings shall add to the better understanding of researchers, practitioners, and policy-makers in developing the protection of information assets in the accounting area.

The Role Of Business Analytics Adoption In Fostering Value Creation To Achieve Competitive Advantage In Industry 4.0

In the era of Industry 4.0, where disruption and uncertainty reign, the strategic adoption of business analytics emerges as a vital force in driving competitive advantage through value creation. This study investigates the pivotal role of business analytics adoption in fostering value creation to achieve a sustainable edge in Industry 4.0. By analyzing data from 237 E-commerce firms operating in fiercely competitive markets, the research explores the strategic imperatives for maximizing the utilization of data and information assets. It highlights the importance of integrating business analytics into organizational processes and fostering collaboration and dynamic capability to optimize decision-making and spur innovation. The findings underscore the necessity for firms to develop competencies in leveraging data-driven insights for competitive advantage. Moreover, this study contributes to bridging gaps in both Resource-Based Theory and dynamic capability literature, offering insights into practical actions for navigating the complexities of Industry 4.0. Ultimately, the research provides a comprehensive framework for understanding and implementing business analytics adoption as a strategic imperative for organizational success in the digital era, with implications for enhancing competitive advantage and driving sustained growth.

Security in the era of wireless innovations: analysis of potential threats and protective measures

In today's interconnected world, wireless data transmission technologies have seamlessly integrated into the fabric of modern business operations. As reliance on these technologies grows, so does the imperative to ensure robust cyber security measures. Particularly in the age of wireless innovations, exemplified by the proliferation of the Internet of Things (IoT), the discourse surrounding the security of wireless technologies underscores the necessity of comprehending both established threats and the continuous emergence of new vulnerabilities. This underscores the urgent need for timely detection and mitigation strategies. While the convenience afforded by wireless data transmission technologies grants society unprecedented access to information and facilitates the management of diverse devices, processes, and systems, it also exposes users and modern information and communication systems (ICS) to significant cyber threats and vulnerabilities. Consequently, there arises a pressing need to address these challenges comprehensively. This research dissects contemporary methodologies aimed at restricting access to wireless networks, identifying potential vulnerabilities, and crafting effective responses to cyberattacks. It delves into various facets of cyber security, including data encryption, user authentication mechanisms, traffic monitoring protocols, and anomaly detection algorithms. Furthermore, it delves into the crucial aspect of educating personnel on wireless security practices, equipping them with threat awareness and incident response capabilities. Given the dynamic landscape of cybersecurity technologies and threats, this work seeks to establish a foundational understanding of the security landscape within wireless networks. By doing so, it aims to outline pragmatic strategies for effectively managing security risks, thereby fortifying the resilience of modern organizations and safeguarding critical information assets.

Toroidal modified Miller-Turner CME model in EUHFORIA: Validation and comparison with flux rope and spheromak

Rising concerns about the impact of space-weather-related disruptions demand modelling and reliable forecasting of coronal mass ejection (CME) impacts. In this study, we demonstrate the application of the modified Miller-Turner (mMT) model implemented within EUropean Heliospheric FORecasting Information Asset (EUHFORIA) in forecasting the geo-effectiveness of observed coronal mass ejection (CME) events in the heliosphere. Our goal is to develop a model that not only has a global geometry, in order to improve overall forecasting, but is also fast enough for operational space-weather forecasting. We test the original full torus implementation and introduce a new three-fourths Torus version called the Horseshoe CME model. This new model has a more realistic CME geometry, and overcomes the inaccuracies of the full torus geometry. We constrain the torus geometrical and magnetic field parameters using observed signatures of the CMEs before, during, and after the eruption. We perform EUHFORIA simulations for two validation cases -- the isolated CME event of 12 July 2012 and the CME--CME interaction event of 8-10 September 2014. We performed an assessment of the model's capability to predict the most important $B_z$ component using the advanced dynamic time-warping (DTW) technique. The Horseshoe model predictions of CME arrival time and geo-effectiveness for both validation events compare well with the observations and are weighed against the results obtained with the spheromak and FRi3D models, which were already available in EUHFORIA. The runtime of the Horseshoe model simulations is close to that of the spheromak model, which is suitable for operational space weather forecasting. However, the capability of the magnetic field prediction at 1 AU of the Horseshoe model is close to that of the FRi3D model. In addition, we demonstrate that the Horseshoe CME model can be used for simulating successive CMEs in EUHFORIA, overcoming a limitation of the FRi3D model.

Cybersecurity leadership policy and compliance for institutions of higher education

Cybersecurity pairs with information asset storage and security for institutions of higher education. When institutions of higher education lack effective cybersecurity leadership, cyber incidents escalate. Worldwide, institutions of higher education are experiencing threats and vulnerabilities woven in their information systems and technology applications. This requires strategic resolutions. One strategy is cybersecurity and information security policy. Research collected worldwide proves usage of cybersecurity policy aligned with federal international law, establishes a cyber culture of compliance. Furthermore, personnel, internally and externally, are the bridge to managing access to data assets, and unless they are knowledgeable of the policy mandated by the institution and its cybersecurity infrastructure, the results of non-compliance can be catastrophic. Since the United States National Institute of Standards and Technology enacted cybersecurity policy for federal information systems. Institutions of higher education must adhere to these standards and guidelines to manage threats and vulnerabilities programmed in their hardware, software, and cloud. Therefore, why are so many institutions of higher education neglecting to align policy and enforcement of policy with these standards? What problems are creating non-compliance among institutions of higher education personnel and executive leadership? How can cybersecurity leadership improve policy and compliance to control risks factors programmed in information systems, technology, and cloud applications, institutions of higher education rely on to reduce human error? To assess and answer these questions, the researcher deployed qualitative grounded theory lite research to assess trends of cybersecurity leadership at institutions of higher education and to improve policy development and compliance.

Cloud-based Building Information Modelling (CBIM): software engineers' insights into improving asset information quality

Cloud-based Building Information Modelling (CBIM): software engineers' insights into improving asset information quality

Grayson Insurance Cybersecurity Strategic Plan Part 1

Grayson Insurance, as the name suggests, is an insurance company, which operates in the U.S and all across Europe. In recent weeks, we conducted an assessment on some of the cybersecurity policies that affect our company, including the Federal Information Security Management Act (FISMA) and the General Data Protection Regulation (GDPR). This was followed by conducting a risk assessment on some of the most important information assets that Grayson Insurance uses, including customer data, employee information, patient medical records, and company information. Some of the vulnerabilities that were uncovered from the assessment include phishing attacks, insider threats, data breaches through cyberattacks, and intellectual property theft. The next step is to come up with a Strategic Cybersecurity Plan that is aligned with Grayson Insurance’s business and IT priorities.

Development of Geospatial Asset Management System for Higher Education

Abstract: The integration of Geographic Information System (GIS) for asset management was addressed in this study. Geographic Information System (GIS) as a decision support system was integrated within the process of asset management to strengthen the monitoring of tangible assets within the organization. The main objective of this study is to design and develop a Location-Based Asset Management Application System. A waterfall model was utilized to create the system. GeoJSON was used to represent geographical features or attributes of the data gathered. A standardized adapted evaluation form was used to determine the Functionality, Performance, Robustness, and Workmanship of the developed application and interpreted using descriptive analysis. The analysis shows that the developed system is excellent in terms of Functionality, Performance, Robustness, and Workmanship. Based on the study's findings, the developed spatial asset management system is an effective way of monitoring and delivering asset management information and resources to its various constituents. It is highly recommended that a designed system should be utilized and use the developed systems to proactively respond and adapt to the modern world in delivering and managing resources.

Exploring Market Dynamics: A Qualitative Study on Asset Price Behavior, Market Efficiency, and Information Role in Investment Decisions in the Capital Market

This qualitative study explores market dynamics, asset pricing behavior, market efficiency, and the role of information in investment decisions within the financial markets. The research aims to provide insights into the underlying motivations, perceptions, and experiences of market participants, offering a comprehensive understanding of these complex phenomena. Employing qualitative methods such as semi-structured interviews and textual analysis, data was collected from a diverse range of participants including investors, financial analysts, and market regulators. The study found that market dynamics are influenced by various factors including investor sentiment, economic indicators, regulatory changes, and technological advancements. Behavioral biases among investors, such as herd mentality and overconfidence, challenge traditional theories like the efficient market hypothesis (EMH), indicating the presence of market inefficiencies. Moreover, information plays a central role in shaping investor perceptions and driving market trends, though concerns exist regarding the reliability of information sources in the era of social media and algorithmic trading. The study underscores the importance of investor education, diversified investment strategies, transparency, and regulatory interventions in fostering fair, efficient, and resilient financial markets. Moving forward, addressing these issues will be crucial for informed investment decision-making and advancing our understanding of financial market dynamics.

Calibrating the WSA Model in EUHFORIA Based on Parker Solar Probe Observations

We employ Parker Solar Probe (PSP) observations during the latest solar minimum period (years 2018–2021) to calibrate the version of the Wang–Sheeley–Arge (WSA) coronal model used in the European Heliospheric Forecasting Information Asset (EUHFORIA). WSA provides a set of boundary conditions at 0.1 au necessary to initiate the heliospheric part of EUHFORIA, namely, the domain extending beyond the solar Alfvénic point. To calibrate WSA, we observationally constrain four constants in the WSA semiempirical formula based on PSP observations. We show how the updated (after the calibration) WSA boundary conditions at 0.1 au are compared to PSP observations at similar distances, and we further propagate these conditions in the heliosphere according to EUHFORIA’s magnetohydrodynamic (MHD) approach. We assess the predictions at Earth based on the dynamic time-warping technique. Our findings suggest that, for the period of interest, the WSA configurations that resembled optimally the PSP observations close to the Sun were different from the ones needed to provide better predictions at Earth. One reason for this discrepancy can be attributed to the scarcity of fast solar wind velocities recorded by PSP. The calibration of the model was performed based on unexpectedly slow velocities that did not allow us to achieve generally and globally improved solar wind predictions compared to older studies. Other reasons can be attributed to missing physical processes from the heliospheric part of EUHFORIA but also the fact that the currently employed WSA relationship, as coupled to the heliospheric MHD domain, may need a global reformulation beyond that of just updating the four constant factors that were taken into account in this study.

Perceptions of Students at Andalas University's Payakumbuh Campus Regarding the Security of Academic Information Systems

Higher Education is one of the public service providers that wants to provide the best service to internal and external parties who need information, namely by utilizing academic information systems. The use of academic information systems is prone to data and information crimes, which are problems experienced by many system users and this also occurs in Indonesia. The method in this study uses a qualitative description method in this study and data collection is obtained using triangulation techniques. The results of the study, that it is necessary to improve information security from various threats, thus ensuring the security of valuable information assets. Information security using The International Organization for Standardization (ISO)/IEC 27001. In addition, it is also necessary to perform two-factor authentication which adds a two-step verification process to access the account.

АНАЛИЗ УСЛОВИЙ РЕАЛИЗАЦИИ УГРОЗ БЕЗОПАСНОСТИ ИНФОРМАЦИИ ЧЕРЕЗ ЭКСПЛУАТАЦИЮ УЯЗВИМОСТЕЙ ИНФОРМАЦИОННЫХ АКТИВОВ

The purpose of the study is to analyze the prerequisites and conditions for the implementation of security threats through the exploitation of vulnerabilities of information assets. The research methods consist in generalizing and analyzing the established approach to preventing threats to information security in the public authorities of the Russian Federation through the exploitation of vulnerabilities, as well as in predicting trends and prospects for the growth of vulnerabilities of information assets. The scientific novelty of the research lies in the analysis of the effectiveness of existing information infrastructure vulnerability management processes implemented without the use of specialized process automation tools.

Cybersecurity Management: Developing Robust Strategies for Protecting Corporate Information Systems

This growing complexity and sophistication of cyber threats call for a sea change concerning how organizations handle cybersecurity. Traditional isolated, reactive security models no longer protect against evolving digital risk. This abstract provides an innovation-oriented comprehensive methodology for completely transforming the approach of organizations to the protection of their critical information assets. At the heart of the method lies a recognition of the fact that cybersecurity is not strictly a technological challenge but has multifaceted elements that have to be aligned with the overall business objectives operational constraints, and risk tolerance of the organization. One of the crucial innovations is the integration of advanced analytics, blockchain technology, and machine learning techniques that will enable any organization to create a much more accurate and proactive perspective related to its vulnerability to cyber threats. This holistic cybersecurity methodology can transform security posture, strengthen collaborative capabilities, and build a resilient cybersecurity ecosystem through effective implementation and validation. These insights and lessons learned will, no doubt, inspire and guide other organizations toward a more robust, adaptive, and collaborative approach to cybersecurity management as the organization continues to improve and further innovate in the field of best security practices.

Influencing Factors Analysis IoT Adoption in Indonesian State Housing Management Information System

The Internet of Things (IoT) has revolutionized asset management in Smart Homes. In Indonesia, one of the biggest struggles in implementing emerging technology in the e-government system is connecting the users' behavioral intention with the suitability of the type of work and the technological convenience offered. A technology acceptance and use model is proposed to address this issue by analyzing the correlation between IoT adoption in asset management. The model draws insights from two complementary methods: user behavioral intention predicts utilization, and task-technology fit predicts performance with moderating factors analysis. The study finds that social influence, hedonic motivation, and price value factors are compelling users' intentions to adopt the Internet of Things in asset management. The IoT technology is deemed worth the price for asset management, particularly for state residences, due to its automation, accuracy, and real-time features. It also enhances decision-making, as the asset information is more reliable and secure. This study enriches moderating factors analysis to study the effect of technology adoption. Additionally, research on asset management systems still needs to be improved, especially in the government sector. In conclusion, this study provides insights into adopting IoT in the government sector and its potential to transform asset management.