Misuse Of Data Research Articles

Quo vadis Indonesian public relations profession: dilemma on the rise of AI

The debate over AI has focused on its contrast with human employment. Simple perspectives are inadequate in public communication fields like Public Relations (PR). The conversation must shift from discussing AI's impact on human jobs to how AI will shape public communication as AI becomes more important in PR. To examine AI's effects on Public Relations, this study uses a literature review focusing on authority and public voice. Due to the risks of AI misuse, data discrimination, and data poisoning, public relations must carefully consider the implications of AI integration. Artificial Intelligence (AI) in Public Relations is studied using a literature review as its main method. Experts are consulted to identify AI's most significant challenges and opportunities in public relations. Public relations (PR) are affected by Artificial Intelligence (AI), which presents both opportunities and challenges. AI can boost public communication, but it also risks data misuse and discrimination. Ethical issues arise when AI represents the public's voice. This study provides useful insights into how Indonesia's Public Relations profession should approach Artificial Intelligence. PR professionals can overcome technical and ethical challenges and revolutionise public communication with AI integration. Therefore, ethical PR practice and the use of AI are becoming increasingly important.

안면인식기술과 개인정보보호

Face recognition technology is a method that utilizes thermal infrared photography, three-dimensional measurement, and skeletal analysis to scan, store, and recognize facial shapes or thermal images. It verifies identity by comparing facial images captured by cameras with those in a stored photo database. This technology is extensively applied in various sectors, such as identity verification and access control, due to its high accuracy and quick identification capabilities. The advancement of facial recognition technology, coupled with CCTV, the Internet of Things (IoT), and widespread network connections, is materializing dystopian fears concerning omnipresent surveillance and the ensuing erosion of privacy. Additionally, biased facial recognition technology may serve as a tool for discrimination, infringing upon the rights and freedoms of minorities and other marginalized groups. In 2023, the National Human Rights Commission of The Republic of Korea issued a statement regarding human rights violations facilitated by facial recognition technology and urged the Speaker of the National Assembly and the Prime Minister to actively respond. The statement highlighted that direct observation of individuals' faces in public spaces by the state could limit citizens' freedom of movement and lead to unwarranted surveillance. Given the unique nature of biometric information, such as facial recognition technology, the repercussions of data breaches and misuse are more severe compared to other types of personal information. Specifically, real-time facial recognition technology that targets an unspecified number of individuals in public spaces without their consent may infringe upon the right to privacy and informational self-determination, as well as other fundamental rights including privacy, freedom of assembly, and freedom of association. Furthermore, real-time facial recognition security systems pose challenges in terms of privacy protection and invasion. Hence, the security of collected facial data, defenses against hacking threats, and the secure management of facial databases require thorough examination. This study explores the legal framework and international legislative trends related to biometric information, including facial recognition technology, to identify measures for protecting personal information and ensuring the safe use of this technology.

Development and Threats of Artificial Intelligence in Industry and Workforce

The abstract explores the transformative impact of Artificial Intelligence (AI) on global industries, highlighting its role in enhancing efficiency and innovation while also posing challenges such as job automation, skills gaps, data misuse, and ethical concerns. Drawing from the Global Risk Report 2024 and recent regulatory actions by the European Union and Indonesia, the abstract discusses the pressing need for AI governance. However, it lacks specificity in articulating the study's objectives and scope, and could benefit from providing concrete examples or statistics to support its claims. A clearer organizational structure and citation of relevant sources would enhance the coherence and credibility of the abstract. Furthermore, while emphasizing the importance of human control over AI, the abstract could offer a more nuanced conclusion that underscores the significance of the study's findings in achieving this goal.

A medical big data access control model based on smart contracts and risk in the blockchain environment.

The rapid development of the Hospital Information System has significantly enhanced the convenience of medical research and the management of medical information. However, the internal misuse and privacy leakage of medical big data are critical issues that need to be addressed in the process of medical research and information management. Access control serves as a method to prevent data misuse and privacy leakage. Nevertheless, traditional access control methods, limited by their single usage scenario and susceptibility to single point failures, fail to adapt to the polymorphic, real-time, and sensitive characteristics of medical big data scenarios. This paper proposes a smart contracts and risk-based access control model (SCR-BAC). This model integrates smart contracts with traditional risk-based access control and deploys risk-based access control policies in the form of smart contracts into the blockchain, thereby ensuring the protection of medical data. The model categorizes risk into historical and current risk, quantifies the historical risk based on the time decay factor and the doctor's historical behavior, and updates the doctor's composite risk value in real time. The access control policy, based on the comprehensive risk, is deployed into the blockchain in the form of a smart contract. The distributed nature of the blockchain is utilized to automatically enforce access control, thereby resolving the issue of single point failures. Simulation experiments demonstrate that the access control model proposed in this paper effectively curbs the access behavior of malicious doctors to a certain extent and imposes a limiting effect on the internal abuse and privacy leakage of medical big data.

Analysis of Public Policy and Criminal Law in The Perspective of Consumer Protection for Online Loan Users in Indonesia

The development of online loan services or pinjol in Indonesia raises new problems in consumer protection. Many cases of fraud and misuse of customer personal data are very concerning. The government has not had specific regulations regarding online loans. The existing regulations are merely appeals and suggestions for fintech pinjol to conduct business responsibly. In fact, stricter regulatory and enforcement steps are needed to address the increasing violations that harm consumers. This study aims to analyze public policies and criminal law in the perspective of protecting pinjol consumers in Indonesia. This research uses a normative legal approach with statute and conceptual approaches. The results are expected to provide recommendations for more effective legal protection for online lending consumers in Indonesia, as well as enriching academic literature on fintech and digital consumer protection. The conclusion is that firmer public policy and criminal law provisions are needed to protect consumer rights in using online loan services which currently have weak legal protection.

Urgensi Perlindungan Hukum terhadap Konsumen Lembaga Pinjaman Online Ilegal di Era Revolusi 4.0

Online lending institution is a product of the 4.0 revolution. Its emergence has had many positive impacts on the economy, but on the other hand it has also raised several problems including misuse of personal data, intimidating collecting, and other problems caused by unlicensed or illegal online lending institutions. This study aims to identify the urgency of legal protection for consumers of illegal online lending institution.The method used in this study is normative juridical method by examining library materials or secondary data. The results showed that there are substance problems in legal protection for consumers of illegal online loan institutions in the era of revolution 4.0 which has implications for the ineffectiveness of existing regulations. Therefore, it is urgent to form new regulations that are able to regulate specifically, firmly, and thoroughly so as to create responsive laws, in order to create comfort and security for consumers of online lending institutions in Indonesia.

Our needs have been ignored for a long time: Factors affecting willingness of Black and Hispanic/Latinx sexual and gender minority communities to donate biospecimens.

The study aimed to document factors affecting willingness to engage in biospecimen donation for substance use research among Black and Hispanic/Latinx sexual and gender minority (SGM) people. From May to July 2022, we interviewed 22 Black and Hispanic/Latinx SGM people from The PRIDE Study, a cohort of SGM people in the United States and its territories, using Zoom videoconferencing software. Fourteen participants were sexual minority people, and eight participants were gender minority people. We took an inductive, collaborative qualitative analytic approach to identify themes. Themes included: (1) community benefits, (2) personal benefits, (3) community exploitation, (4) personal risks, (5) convenience, (6) trustworthiness of the research team, (7) perceived value in donating, and (8) normalization of biospecimen collection. Participants were generally motivated to engage in biospecimen donation for altruistic purposes. The most cited concerns were related to data security, misuse, and privacy. Researchers must be proactive in building trust with Black and Hispanic/Latinx SGM communities to increase engagement, diversify biospecimen repositories and reduce health inequities. Future research involving biospecimens should provide biospecimen education during the consent process and prioritize participant convenience.

Neurobiological evidence and criminal competencies.

Neuroimaging and other neurobiological evidences are increasingly introduced in criminal litigation, especially when a neuropsychiatric disorder is suspected. Evaluations of criminal competencies are the most common type of criminal forensic assessment in forensic psychiatry and psychology. Given this, it is critical for forensic evaluators to understand how neuropsychiatric disorders may affect a defendant's criminal competencies and how neurobiological data may be used in competency determinations. This paper reviews the use of neurobiological data, particularly neuroimaging, while considering the limitations and potential misuse of such data in criminal competency evaluations.

UP-SDCG: A Method of Sensitive Data Classification for Collaborative Edge Computing in Financial Cloud Environment

The digital transformation of banks has led to a paradigm shift, promoting the open sharing of data and services with third-party providers through APIs, SDKs, and other technological means. While data sharing brings personalized, convenient, and enriched services to users, it also introduces security risks, including sensitive data leakage and misuse, highlighting the importance of data classification and grading as the foundational pillar of security. This paper presents a cloud-edge collaborative banking data open application scenario, focusing on the critical need for an accurate and automated sensitive data classification and categorization method. The regulatory outpost module addresses this requirement, aiming to enhance the precision and efficiency of data classification. Firstly, regulatory policies impose strict requirements concerning data protection. Secondly, the sheer volume of business and the complexity of the work situation make it impractical to rely on manual experts, as they incur high labor costs and are unable to guarantee significant accuracy. Therefore, we propose a scheme UP-SDCG for automatically classifying and grading financially sensitive structured data. We developed a financial data hierarchical classification library. Additionally, we employed library augmentation technology and implemented a synonym discrimination model. We conducted an experimental analysis using simulation datasets, where UP-SDCG achieved precision surpassing 95%, outperforming the other three comparison models. Moreover, we performed real-world testing in financial institutions, achieving good detection results in customer data, supervision, and additional in personally sensitive information, aligning with application goals. Our ongoing work will extend the model’s capabilities to encompass unstructured data classification and grading, broadening the scope of application.

Protection of Citizens' Personal Data as Voters in the Organization of Simultaneous General Elections in 2024 (A Study in the East Lombok Election Commission)

This research aims to examine the Legal Protection of Voters' Personal Data in the Implementation of the Simultaneous General Elections in 2024. There are several problem formulations in this research, including the following: What are the forms of Legal Protection of Voters' Personal Data in the Implementation of the Simultaneous General Elections in 2024? How is the implementation of the Protection of Citizens' Personal Data as Voters in the Implementation of the Simultaneous General Elections in 2024 in the East Lombok Election Commission (KPU Lombok Timur)? The Legal Protection of Voters' Personal Data in the Implementation of the Simultaneous General Elections in 2024 takes the form of legal protection through regulations such as Law No. 7 of 2017 regarding general elections and the Personal Data Protection Act No. 27 of 2022. This can be considered as a form of protection for electoral participants' data from regulations governing unauthorized data usage, misuse of data for specific interests, and data tampering. The Implementation of the Protection of Citizens' Personal Data as Voters in the Implementation of the Simultaneous General Elections in 2024 in the East Lombok Election Commission involves two steps: preventive and repressive measures. The preventive steps taken by the East Lombok Election Commission include data protection, starred NIK markers, information transparency, data accuracy and updating, and cooperation with relevant institutions. The repressive steps include enforcement against personal data theft, enhancement of cybersecurity, and Governance of Personal Data Protection Policy.

The Risks and Challenges of Artificial Intelligence in Endocrinology.

Artificial intelligence (AI) holds the promise of addressing many of the numerous challenges healthcare faces, which include a growing burden of illness, an increase in chronic health conditions and disabilities due to aging and epidemiological changes, higher demand for health services, overworked and burned-out clinicians, greater societal expectations, and rising health expenditures. While technological advancements in processing power, memory, storage, and the abundance of data have empowered computers to handle increasingly complex tasks with remarkable success, AI introduces a variety of meaningful risks and challenges. Among these are issues related to accuracy and reliability, bias and equity, errors and accountability, transparency, misuse, and privacy of data. As AI systems continue to rapidly integrate into healthcare settings, it is crucial to recognize the inherent risks they bring. These risks demand careful consideration to ensure the responsible and safe deployment of AI in healthcare.

Protecting Confidentiality in the Digital Ecosystem of Humanitarian Aid

Protecting Confidentiality in the Digital Ecosystem of Humanitarian Aid

PERSONAL DATA PROTECTION POLICY: ENSURING EFFECTIVE IMPLEMENTATION OF DATA PRIVACY POLICIES IN PRIVATE HIGHER INSTITUTIONS

Faculty of Business and Management Sciences, Kolej Universiti Islam Perlis, Malaysia As digital technology develops globally, the protection of personal data in the commercial sector becomes extremely important. Cases of selling data to third parties are increasing, and the government is required to tighten provisions in personal protection laws. Therefore, the Personal Data Protection Act 2010 (Act 709) was passed by the Parliament of Malaysia for the purpose of regulating the processing of personal data and to prevent the misuse of the personal data in commercial transactions. The Act confers rights on Data Subjects in relation to the collection, use and or retention (processing) of their Personal Data, and places obligations on Data Users. The Personal Data Protection Order (Group Data Users) 2013 lists the categories of data users who need to register with Personal Data Protection Department. One of group data users is the education sector including educational institutions and private higher education registered under the Private Higher Education Institutions Act 1996 (Act 555). As data users, private higher education institutions are responsible for protecting Personal Data of two categories of data subjects, namely students and employees in the institution. The obligation including to exercise an appropriate policies and procedures to safeguard the Personal Data collected, to maintain data accuracy, and to prevent unauthorized disclosure. This paper aims to measure the implementation of personal data protection laws including the formulation of operational policies and procedures in private higher education institutions. This will be done by looking at the provisions from the Act regarding the principles of data protection as well as the duties for compliance to the legislation. Furthermore, non-compliance of the Act commits an offence and on conviction, be liable to a fine not exceeding RM500,000 or to imprisonment for a term not exceeding 3 years or both. The study also seeks to determine what are the challenges in implementing the Act successfully.

Design of Reversible Quantum Vigenere Cryptographic Cipher in QCA and IBMQ Platforms for Secure Nanocommunication

Using cryptography correctly is crucial in the current situation to safeguard data and ensure data security during data transfer. In this digital era, messages must be appropriately encrypted and decoded to prevent data misuse and ensure its accessibility to the intended recipient. Conventional cryptography techniques mostly depend on the mathematical intricacy of the encoding functions and the shared key. One such encoding approach that we may take into consideration is the Vigenere cipher algorithm. In this study, we want to apply this strategy utilizing reversible logic with the assistance of two helpful tools, namely, IBM Quantum (IBMQ) and QCADesigner. The encoder and decoder circuits for the Vigenere cipher are therefore proposed in this work in QCADesigner by utilizing Peres and DG gates in quantum-dot cellular automata (QCA) that consist of a single layer with 42 cells for encryption and 47 cells for decryption. The proposed circuit outperforms the existing ones concerning area, cell count and latency. Given that the layouts’ energy consumption is assessed, it is guaranteed that the QCA nanodevice might serve as a stand-in platform for the creation of reversible circuits. The same simulation outcome was also obtained while building the identical circuits in a quantum presentation using IBMQ. The two applications are closely connected and both rely on quantum concepts. The outcomes are therefore verified for each of the two situations. The reversible Vigenere cipher technique enhances data security. Further sophisticated low-power nanoscale lossless nanocommunication architecture may be created with the help of the suggested circuits.

Fortifying Democracy: Deploying Electoral Justice for Robust Personal Data Protection in the Indonesian Election

Elections stand as a cornerstone of democracy, yet the burgeoning integration of technology and personal data underscores the pressing need for safeguarding individual privacy within the electoral process. This study endeavors to scrutinize the efficacy of the Electoral Justice System in fortifying the protection of personal data throughout the registration, verification, and adjudication phases of political party participation in the forthcoming 2024 elections. Through an empirical juridical methodology, this research delves into the practical application of the Electoral Justice System across diverse national contexts, elucidating its role in mitigating the perils of data misuse and upholding electoral integrity. The findings underscore the imperative of imbuing the Electoral Justice System with structural robustness, substantive fidelity, and a conducive legal culture to ensure the seamless functioning of electoral processes. Additionally, stringent regulations, robust data verification protocols, independent oversight mechanisms, and punitive measures emerge as indispensable facets of effective Electoral Justice System implementation, essential for curtailing infringements of the exploitation of personal data and fostering accountable electoral practices.

PERCEIVED USEFULNESS AND ATTITUDE TOWARD INTENTION AND ACCEPTANCE OF E-PAYMENT ZAKAT

Introduction and Background: As people's lifestyles and behaviour toward daily digital activities are changing, a suitable zakat payment option is required to encourage Muslims to fulfil their commitments. Zakat institutions use technology; as a result, to attract more people to pay zakat. The acceptance is, however, dubious due to data misuse and platform security worrisome. Hence, this study aims to investigate Malaysian Muslims’ acceptance of the e-payment zakat system.
 
 Methodology: In this descriptive study, a survey was carried out on 170 zakat payers in Malaysia. Five constructs were examined in the survey, based on Technology Acceptance Model, which are Perceived Usefulness, Perceived Ease of Use, Attitude, Intention, and User Acceptability. Data were analysed in linear and logistic regression using the Statistical Package for Social Sciences (SPSS).
 Findings: Results revealed that Perceived Usefulness and Perceived Ease of Use significantly impacted Attitude's decision to use electronic payment channels for zakat payments. The correlation between Attitude and Intention for online zakat payment was found to be positive. User acceptability was significantly influenced by the Perceived Usefulness of the e-payment platform and the Intention to pay zakat online. 
 
 Contribution: Understanding that User Acceptability is influenced by Perceived Usefulness and Intention would allow the zakat institution to comprehend the user requirement for zakat payment applications. The study findings have implications zakat authorities to enhance the digital platform for zakat payments to ease users by leveraging technology to streamline the donation process and make it more convenient, secure, and transparent.
 
 Keywords: E-payment, zakat, acceptance, technology acceptance model, user acceptability.
 
 Cite as: Hainnuraqma, R., Hamidah, M. I., Nor Balkish, Z., Mohamed Fairooz, A. K., & Sobhani, F. A. (2024). Perceived usefulness and attitude toward intention and acceptance of e-payment zakat. Journal of Nusantara Studies, 9(1), 320-344. http://dx.doi.org/10.24200/jonus.vol9iss1pp320-344

The Role of Brand Image and Trust in the Adoption of FinTech Digital Payment for Online Transportation

Background: The widespread use of financial technology (FinTech) is a popular aspect across various fields, particularly in online transportation. However, the usage has led to an increase in illegal FinTech, causing significant problems for public. Issues related to account security, such as hacks leading to the loss of user balances and misuse of data, contribute to the erosion of brand image and public trust. Despite the growing prominence of FinTech, explorations on the application in the context of online transportation remain limited. Previous studies have not discussed the impact of brand image on perceived usefulness and ease of use. Therefore, this current study explores the importance of combining brand image and trust factors to increase user intention. This process is achieved by investigating brand image and trust as crucial factors influencing increased perceived ease and benefits during the integration of FinTech in online transportation services. Objective: This study aimed to measure the impact of brand image and trust factors on the adoption of FinTech in online transportation. Methods: The investigation was carried out with a quantitative analysis approach using Partial Least Squares–Structural Equation Modeling (PLS–SEM). Furthermore, it focused on understanding FinTech services in online transportation, incorporating factors such as trust, brand image, perceived ease of use, perceived usefulness, and user intention. Data were collected by using a purposive sampling method through online questionnaire distribution. PLS-SEM was adapted for analyzing variable relationships, hypotheses, and models. Results: The results showed that factors including trust, perceived ease of use, and perceived usefulness significantly influenced the willingness to use FinTech in online transportation services. However, it was observed that brand image factors did not impact user intentions. Conclusion: This study showed a critical aspect in understanding the value of FinTech services by explaining the importance of establishing trust and building a good brand image as precursors. These factors indirectly contributed to increased perceived benefits and ease of use. Therefore, the insights offered valuable input for companies aiming to develop trusted FinTech platforms with a positive product image. Keywords: Brand Image, Trust, FinTech, Online Transportation

Overview of big data information privacy protection technology and challenges

With the rapid development of advanced technologies like the mobile internet, cloud computing, and the Internet of Things, the era of big data is gradually upon us. In this era, big data has been widely utilized in various fields like business, finance, social networking, and healthcare, and the value of data has become increasingly prominent. Data has become a new factor of production, the digital economy has become a new engine of development, and an important driving force for promoting social progress and economic development. However, with the advancement of big data technology, the risks of data leakage and misuse have increased. Personal data information leakage or misuse can lead to personal privacy infringement and fraud, such as the Sina Weibo data leak in March 2020 where attackers breached part of the Sina Weibo database, obtaining sensitive data including real names, website usernames, genders, locations, and phone numbers, impacting 538 million Weibo users. Therefore, there is an increasing demand for data information privacy protection. This paper will explore the core technologies and application scenarios in data information privacy protection and investigate data privacy protection in real-life settings.

Inclusive Smart Cities: An Exploratory Study on the London Smart City Strategy

Smart city strategies have been developed in several cities worldwide to improve the well-being of residents, social life and economic welfare through digital transformation and technology-based interventions. The need for cities to supply assistive services and inclusive strategies for all people has also increased with the increasing urban population and smart city applications. Although technology offers several benefits for more inclusive and liveable environments, there are also drawbacks due to difficulties in adapting to digitalization and due to limited accessibility. The present study aims to explore smart city strategies from an inclusiveness perspective by analysing the London smart city strategy as a case study using a qualitative research methodology. Qualitative data analysis was conducted based on secondary data from London smart city strategy documents and semi-structured interviews with domain experts. Although inclusiveness is embedded in the London smart city strategy, there is still room for improvement. The results of this study indicate that spatial inclusion is the major focus of the London smart city policy where inclusive housing, transport and health management systems are promoted with a variety of assistive technologies with some scope on social and economic inclusion. This study proposed ways of boosting inclusiveness by improving citizen engagement through collaborations, increased transparency, and measures for preventing data misuse and misinterpretation. Using London as a case study, potential barriers in implementing inclusive strategies for smart cities in practice are highlighted, which may provide valuable learned lessons for other cities.

Multiple Perspectives on the Adoption of SMART Technologies for Improving Care of Older People: Mixed Methods Study.

Despite the ever-increasing offering of SMART technologies (ie, computer-controlled devices acting intelligently and capable of monitoring, analyzing or reporting), a wide gap exists between the development of new technological innovations and their adoption in everyday care for older adults. This study aims to explore the barriers and concerns related to the adoption of SMART technologies among different groups of stakeholders. Data from 4 sources were used: semistructured in-person or internet-based interviews with professional caregivers (n=12), structured email interviews with experts in the area of aging (n=9), a web-based survey of older adults (>55 years) attending the Virtual University of the Third Age (n=369), and a case study on the adoption of new technology by an older adult care facility. Although all stakeholders noted the potential of SMART technologies to improve older adult care, multiple barriers to their adoption were identified. Caregivers perceived older adults as disinterested or incompetent in using technology, reported preferring known strategies over new technologies, and noted own fears of using technology. Experts viewed technologies as essential but expressed concerns about cost, low digital competency of older adults, and lack of support or willingness to implement technologies in older adult care. Older adults reported few concerns overall, but among the mentioned concerns were lack of ability or interest, misuse of data, and limited usefulness (in specific subgroups or situations). In addition, older adults' ratings of the usefulness of different technologies correlated with their self-rating of digital competency (r=0.258; P<.001). Older adults appeared to have more positive views of various technologies than professional caregivers; however, their concerns varied by the type of technology. Lack of competence and lack of support were among the common themes, suggesting that educationally oriented programs for both older adults and their caregivers should be pursued.