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This study aims to analyze the reconceptualization of national security in the digital era through the case of the 2021 Facebook data breach involving 533 million users across 106 countries. As digital technologies become increasingly integrated into governance, economic activities, and social interactions, cyber threats have emerged as a significant challenge to contemporary security frameworks. This research employs a qualitative descriptive approach using library research methods, drawing upon academic literature, official reports, and relevant policy documents. The findings indicate that national security has evolved from a traditional military-centered concept toward a broader and multidimensional framework that includes cyber threats as a form of non-traditional security challenge. The Facebook data breach demonstrates how cyber threats transcend geographical boundaries, involve complex attribution problems, and generate multidimensional impacts on individuals, societies, economies, and states. Through the lens of Securitization Theory developed by Buzan, Wæver, and de Wilde (1998), the incident illustrates how data security has become securitized as a matter of national and international concern. Furthermore, the Human Security framework proposed by UNDP (1994) highlights the vulnerability of individuals whose personal information becomes exposed in the digital environment. This study concludes that cybersecurity should be recognized as a fundamental pillar of national security in the digital age, requiring comprehensive strategies that integrate technological resilience, data protection regulations, human resource development, and international cooperation.

This study aims to analyze the authority of the Regional People's Representative Council (DPRD) of Sukabumi City based on Government Regulation Number 12 of 2018 concerning Guidelines for the Preparation of Standing Orders of Regional People's Representative Councils of Provinces, Regencies, and Cities. The authority of the DPRD is a crucial element in ensuring the effective implementation of regional governance under the principle of check and balances. This research employs a normative juridical legal research method with a descriptive-analytical specification. The approaches used include the statute approach, conceptual approach, and case approach. The analysis is conducted using the Authority Theory of Philipus M. Hadjon, which classifies sources of authority into attribution, delegation, and mandate. The results indicate that the authority of the DPRD of Sukabumi City in exercising its supervisory function originates from constitutional attribution directly conferred by Article 20A paragraph (1) of the 1945 Constitution, reinforced by Law Number 17 of 2014, Law Number 23 of 2014, and operationalized through Government Regulation Number 12 of 2018 Articles 19, 21, and 22. Such authority is imperative in nature, not merely discretionary. Failure to exercise it constitutes a violation of the constitutional mandate, resulting in what Hadjon refers to as a legal oversight vacuum that enables systematic and recurring legal violations.

Sentiment analysis for Indonesian regional languages faces two persistent challenges: labeled training data is extremely limited for most regional varieties, and transformer models pre-trained on Bahasa Indonesia do not generalize reliably to languages with substantially different morphological structures. Prior work on the NusaX benchmark has primarily relied on direct fine-tuning, treating each regional language independently and without exploiting linguistic proximity between related languages as a transfer signal. This paper proposes Language-Similarity-Guided Transfer (LSGT), a sequential fine-tuning strategy that first adapts a pre-trained model to a pivot language selected using character trigram similarity, followed by fine-tuning on the target language. Four transformer models are evaluated across all 12 NusaX languages using the official train/validation/test splits: IndoBERT, NusaBERT, mBERT, and XLM-R. Performance is evaluated using four metrics: accuracy, macro F1, macro precision, and macro recall. Experimental results show that LSGT improves macro F1 in 44 of 48 model-language combinations, demonstrating that the fine-tuning strategy itself is a major factor in low-resource cross-lingual sentiment classification. XLM-R benefits most strongly from LSGT, achieving an average improvement of +0.137 macro F1 and a peak gain of +0.298 on Madurese. SHAP-based token attribution analysis further reveals that predictions rely heavily on named entities and domain-specific nouns rather than sentiment-bearing vocabulary, indicating a dataset-level bias inherited from the original SmSA corpus and propagated through the NusaX translation pipeline.

This study analyzes the gap between legal certainty and justice in patent protection in Indonesia through a case study of the transfer of patent rights for the Spider Nest Construction. The problem formulation includes two things. First, what is the form of distortion of legal certainty in the transfer of patent rights. Second, how is the violation of the inventor's moral and economic rights and the institutional factors that cause it. The method used is normative juridical with a statutory, case, conceptual, and comparative approach. The results of the study indicate that the distortion of legal certainty occurs because the registration of the transfer of rights only uses a Power of Attorney without an authentic deed, which violates Article 11 of the Patent Law. In addition, the unilateral action of the Directorate General of Intellectual Property to freeze and revoke the freezing of patents without a court decision violates Article 132 of the Patent Law. Violation of moral rights is manifested in the form of false attribution in the JALLA patent. Economic rights are ignored through embezzlement of royalties. The peak of injustice is the accusation of plagiarism against the original inventor for his own development invention. Inhibiting factors include institutional weaknesses within the Directorate General of Intellectual Property, excessive judicial intervention, low human resource capacity, regulatory disharmony, and an unsupportive legal culture. Strengthening strategies include institutional reform, revision of the Patent Law, ratification of international conventions, digitalization, international certification, and the establishment of a specialized intellectual property court. In conclusion, without strengthening integrated intellectual property legal policy, the gap between procedural legal certainty and substantive justice will continue to weaken the national innovation ecosystem.

This study examines the legality of on-street parking levy practices in Kupang City from a constitutional law perspective, with a primary focus on the application of the legality principle. The background of this research stems from a significant discrepancy between the legal norms established in statutory regulations and the empirical administrative practices occurring in the field. Identified issues include the collection of levies without official tickets, the lack of clarity regarding the identity and legal status of collection officers, and the inconsistent and non-transparent application of parking tariffs. This research employs a normative-empirical legal method by applying statutory, conceptual, and empirical approaches through limited field observations. The findings indicate that although the Kupang City Government formally possesses the attribution of authority to collect parking levies, the implementation frequently deviates from the established legal procedures. Such deviant practices potentially constitute ultra vires actions and violate the principle of due process of law in government administration. This study concludes that the substantive legality of parking levies in Kupang City has not been fully realized, thereby undermining legal certainty and public trust in the legitimacy of local governance. The implications of this research emphasize the imperative for comprehensive reform of the supervision system and stricter enforcement of administrative procedures to ensure the rule of law at the local level.

This research seeks to examine the influence of taxpayer knowledge, taxpayer awareness, and tax sanctions on the compliance of motor vehicle taxpayers in Boyolali Regency. Motor vehicle tax constitutes a significant component of regional original revenue; however, the level of revenue realization has not yet fully met the established targets, indicating the presence of compliance-related challenges. The study adopts a quantitative explanatory design. Primary data were obtained by distributing questionnaires to 100 motor vehicle taxpayers registered at the Boyolali Samsat Office, with respondents selected through accidental sampling based on the Slovin formula. Data analysis was conducted using multiple linear regression with the assistance of SPSS software, following preliminary tests of validity, reliability, and classical assumptions. The findings demonstrate that taxpayer knowledge and taxpayer awareness exert a positive and statistically significant effect on motor vehicle taxpayer compliance. In addition, tax sanctions are also shown to have a positive and significant impact and represent the most dominant factor influencing compliance. These results are consistent with Attribution Theory and the Theory of Planned Behavior, which highlight the importance of both internal and external determinants in shaping taxpayer compliance behavior. This study is expected to provide empirical support for research on regional tax compliance and offer practical insights for local governments in developing strategies to improve motor vehicle tax compliance.

Honor killing cases often involve a distributed structure of perpetrators between decision-makers, providers of means, and implementers. This collective pattern raises the problem of role attribution in criminal law enforcement, which often shifts toward two problematic tendencies: centralizing responsibility on the executor or expanding criminal responsibility based on family ties. This article aims to formulate a tested role attribution model so that criminal responsibility does not stop at the direct perpetrator and does not develop into association-based punishment. This research uses a normative legal research method with a conceptual approach. Data collection methods were collected using literature studies, then analyzed qualitatively and presented descriptively. The research results formulate a role map of instigator, facilitator, and executor, operationalized through group role attribution based on two axes: causal contribution and normative contribution. The instigator is understood as the driver who shapes the will and locks the decision, the facilitator is understood as an assistant who deliberately provides the opportunity, means, or information. Meanwhile, the executor is someone who carries out the material act, although in terms of position, their actions are not automatically identical to the dominance of the decision. This division of roles is complemented by evidentiary indicators covering communication, financing, provision of facilities, field control, and post-incident intimidation, along with negative criteria to prevent inferences based on blood relations or passive presence. This model provides a more measurable standard of attribution for investigation, prosecution, and sentencing in collective honor killing cases.

Criminal responsibility is constructed through the elements of homicide offences, the assessment of mens rea, accomplice liability, and sentencing rationality grounded in individual culpability. In judicial practice, however, cases involving the killing of women are frequently framed at the outset through the labels of “honour” or “intimate relationship,” leading honour killing and intimate partner femicide to be treated as interchangeable categories. This practice shifts the assessment of intent toward the perpetrator’s narrated motive and narrows accountability to the last physical actor. This research aims to formulate, first, legal criteria and evidentiary indicators for distinguishing the two categories through a staged judicial classification test, and second, to assess the implications of such classification for the construction of intent, the attribution of responsibility to non-executing actors, and sentencing rationality through disciplined reason-giving. The study employs a normative legal method with a conceptual approach, based on library research of primary and secondary legal materials. The findings demonstrate that the core deficiency lies in the absence of an operational classification device, allowing honour narratives to displace structured mens rea analysis and to obscure the causal contributions of non-executors. The article proposes working definitions and a stepwise indicator-based test—focusing on the presence of determinative social pressure or sanctioning, provable role allocation within perpetrator networks, and prior threats framed in terms of honour restoration—and links these indicators to concrete doctrinal consequences for intent, accomplice liability, and sentencing. Through this framework, judicial reasoning is redirected from label-driven interpretation toward accountability, while restraining the use of honour as a mitigating rationale and preventing femicide patterns from being concealed by reputational narratives.

The development of Artificial Intelligence (AI) has significantly influenced the formation of contracts in civil law, particularly through the automation of clause drafting, risk analysis, and the standardization of contractual documents. The use of AI in contract drafting raises complex legal issues, especially concerning the validity of agreements and the attribution of legal liability in the event of default. This study aims to analyze the validity of contracts created through Artificial Intelligence from the perspective of Indonesian civil law and to examine models of legal liability in AI-based contracts. This research employs a normative legal method with statutory and conceptual approaches, examining the provisions of the Indonesian Civil Code, particularly Article 1320, as well as legal doctrines and scholarly perspectives on digital contracts and AI. The findings indicate that AI-based contracts are, in principle, legally valid as long as they fulfill the requirements of a valid agreement, namely the consent of the parties, legal capacity, a specific object, and a lawful cause. Artificial Intelligence cannot be positioned as a legal subject because it lacks intent, consciousness, and the capacity to bear rights and obligations, and therefore functions solely as a technological tool. Consequently, legal intent and liability remain attached to the human or legal entity that uses, controls, or benefits from AI. This study also emphasizes that the primary challenge of AI-based contracts lies in the absence of specific legal regulations governing the allocation of liability among AI users, system providers, and developers, particularly when default occurs due to algorithmic errors or system failures. Therefore, clearer, adaptive, and comprehensive regulations are required to ensure legal certainty, protect the parties involved, and maintain a balance between technological innovation and the principles of justice in AI-based contractual practices in Indonesia.

The use of Large Language Models (LLMs) in scientific research is becoming increasingly widespread, but presents epistemic risks that are not yet fully understood. This article discusses how the probabilistic mechanisms of LLM can produce outputs that appear correct and justified but are actually dependent on epistemic luck, thus resembling the Gettier case pattern. Through a conceptual study approach, this research clarifies concepts, analytically reconstructs the generative structure of LLM, and conducts a normative analysis of its implications for scientific accountability and authorship. The results of the analysis show that Algorithmic Gettier Cases (AGCs) occur when linguistic coherence deceives users and creates the impression of justification, even though the truth that emerges is statistical coincidence and is not supported by valid causal relationships. This condition poses a serious challenge to the attribution of knowledge and author responsibility in the production of academic texts. To address this issue, this article proposes the principle of Hyper-Justification Obligation, which is the ethical obligation for researchers to actively verify and causally reason every AI output before using it in scientific works. This research provides a theoretical contribution to understanding the epistemic risks of LLM and offers an ethical foundation for academic practice in the era of generative AI.

Background: The rapid development of financial technology and the increasing volume of cross-border transactions have led to the emergence of increasingly complex digital financial crimes, involving anonymous actors and exploiting regulatory gaps and jurisdictional differences. This condition poses serious challenges to legal systems, particularly in terms of digital evidence, the attribution of legal liability, and the effectiveness of cross-border law enforcement. Objective: This study aims to reconstruct the framework of civil and criminal liability in digital fraud cases to make it more adaptive, integrated, and responsive to technological developments. Method: The research employs a qualitative socio-legal approach, combining normative analysis of cybercrime regulations, case studies of international digital fraud, comparative analysis of legal systems across countries, and interviews with legal practitioners and fintech regulators. Results: The findings reveal significant legal gaps, regulatory fragmentation across jurisdictions, and weaknesses in electronic evidence systems that hinder effective law enforcement. Additionally, the complexity of actors and technologies within digital ecosystems complicates the accurate attribution of legal responsibility. Therefore, an integrated legal framework is required, incorporating both civil and criminal liability, international regulatory harmonization, and the utilization of technology to enhance law enforcement effectiveness.

Background: The rapid development of blockchain technology and smart contracts has fundamentally transformed contractual relationships by shifting the role of human interpretation and enforcement toward automated, code-based, and decentralized systems. This transformation generates complex legal implications, particularly regarding the evolution of contractual liability, which is increasingly distributed and no longer centered on a single legal subject. Objective: This study aims to analyze the evolution of contractual liability in smart agreements and examine how such transformation affects the fundamental principles of traditional contract law within modern legal systems. Methods: This research employs a normative and conceptual legal approach, supported by an analysis of blockchain regulations across multiple jurisdictions, case studies of smart contract implementation, and a comparative legal analysis between civil law and common law systems, complemented by a multidisciplinary literature review. Results: The findings indicate that contractual liability in smart agreements has evolved from a centralized fault-based liability model to an algorithmic, distributed, and code-dependent liability structure within blockchain ecosystems. This evolution creates new legal challenges concerning the attribution of liability, legal certainty, and the limitation of judicial intervention in automated contractual arrangements. Furthermore, the study identifies a tension between technological efficiency and substantive legal justice, highlighting the need for adaptive legal frameworks capable of accommodating decentralized technologies while ensuring the protection of legal rights and accountability of involved parties.

End-to-end autonomous driving has emerged as a promising paradigm in which deep neural networks directly map raw visual inputs to continuous control actions. Despite its effectiveness, this approach suffers from limited transparency, posing significant challenges for deployment in safety-critical driving scenarios. This study addresses the lack of interpretability in vision-based end-to-end autonomous driving systems and aims to analyze model decision-making behavior under critical conditions such as sharp steering maneuvers and abrupt control transitions. To this end, an explainable end-to-end autonomous driving framework is proposed, combining a convolutional neural network trained via imitation learning with gradient-based visual attribution techniques, including Grad-CAM. The model predicts continuous steering, throttle, and braking commands directly from front-facing camera images, while explainability mechanisms are applied to reveal input regions influencing each control decision. Model performance is evaluated using both prediction accuracy and safety-oriented behavioral metrics. Experimental results show that the proposed explainable model achieves lower control prediction errors compared to a baseline end-to-end CNN, reducing steering mean squared error from 0.034 to 0.031, throttle error from 0.021 to 0.019, and brake error from 0.018 to 0.016. Moreover, safety-oriented analysis indicates improved driving stability, with steering variance reduced from 0.087 to 0.072 and abrupt control changes decreased from 14.6 to 10.3 events. Visual explanations consistently highlight road surfaces and lane-related structures during complex maneuvers, indicating reliance on semantically meaningful cues. In conclusion, the results demonstrate that integrating explainability into end-to-end autonomous driving not only preserves predictive performance but also correlates with smoother and more stable driving behavior. This framework contributes to the development of transparent and trustworthy autonomous driving systems suitable for safety-critical applications

This study aims to comprehensively analyze the role of tax consultants in improving taxpayer compliance with the Value Added Tax (VAT) rate increase policy from 11% to 12%, which will take effect in 2025. The research adopts attribution theory to explore how professional assistance can influence taxpayers’ perception and behavioral shifts toward compliance. A descriptive qualitative method was employed, with data collected through literature studies, participatory observation, and semi-structured interviews involving one tax consultant and two taxpayers who received VAT reporting assistance. The findings reveal that the role of tax consultants extends beyond administrative functions. They not only assist in technical adjustments such as Coretax system configuration and Periodic VAT Return reporting but also play a crucial role in fostering fiscal awareness through educational and psychological approaches. Empirically, consultant assistance improved clients’ reporting timeliness from 68% to 91% and reduced tax invoice errors by 27% within a three-month mentoring period. Moreover, consultants contributed to shifting taxpayers’ attribution from external factors—such as blaming the system or regulations—to internal factors, including personal awareness and responsibility. These results demonstrate that the presence of tax consultants strengthens both formal and material compliance, leading to sustainable, awareness-based tax behavior. Therefore, tax consultants serve as catalysts for behavioral transformation and play a strategic role in shaping an adaptive fiscal culture amid dynamic taxation policy changes in Indonesia.

The modern doctrine of criminal responsibility is built on the premise of free will and individual deliberative capacity. However, advances in neurogenetics, particularly findings regarding MAOA-L gene expression, have presented a structural disruption to this framework. The MAOA-L gene has been empirically associated with impaired impulse regulation and increased aggressive responses, particularly in combination with childhood trauma. This study aims to evaluate how MAOA-L gene expression influences the capacity for criminal responsibility and to analyze the tension between classical legal constructs and biological determinants within the structure of culpability. The research method employed normative research with a conceptual approach. The results indicate that the dichotomy-based mens rea doctrine fails to accommodate the degree of control capacity shaped by neurobiological structures. MAOA-L cannot be treated as a basis for forgiveness, but rather serves as an evaluative variable in assessing the spectrum of legal responsibility. In this position, criminal law maintains the principle of individual responsibility but formulates it through a new framework based on actual capacity rather than a universal voluntaristic assumption. This reformulation is necessary to avoid disproportionate attribution of blame and to allow criminal law to move toward a system that is more adaptive to biological realities without falling into determinism.

Criminal law based on genetic determinism was once rejected in modern criminal law systems because it was deemed contrary to the principle of individual responsibility. However, the rise of epigenetics and neurocriminology in contemporary legal practice indicates a reconstitution of the biological basis for attribution of criminal culpability. This study aims to analyze the extent to which developments in epigenetics reopen opportunities for the operation of biological approaches in criminal law, while also critiquing the conceptual dangers they pose to the principles of justice and moral responsibility. The research method uses a normative legal approach with a conceptual approach. The results show that epigenetics works as a tool for scientific validation of the formation of risk categories in criminal law, while simultaneously weakening the perpetrator's position as a moral subject. The criminal law structure that technocratically accepts biological arguments creates a new form of legal exclusion through medical classifications that are not open to ethical evaluation. In this situation, the law operates as an instrument of biological management of bodies deemed deviant. The position of neurocriminology in this case is no longer merely a tool, but rather the center of the configuration of biolegal power that defines responsibility based on predisposition, not will. Therefore, a new normative framework is needed that can uphold the principle of individual responsibility while rejecting the ethical reduction of biological diagnoses in the criminal law system.

This study aims to determine the role of work-life balance in mediating the effect of self-efficacy on turnover intention. The research employed a saturated sampling technique with a sample of 112 employees. The method used was a survey method with questionnaires and interviews, analyzed using descriptive statistics and inferential  statistical analysis with SEM-PLS. The results of this study indicate that self-efficacy has a negative effect on turnover intention. Self-efficacy has a positive and significant effect on work-life balance. Work-life balance negatively affects turnover intention. Furthermore, work-life balance is able to mediate the effect of self-efficacy on turnover intention. The theoretical implication of this research is a confirmation of attribution theory and its relation to the research variables. The practical implication provides alternative solutions to the problem of turnover intention. The recommendation given is that the Faculty of Economics and Business, Udayana University, should provide psychological support and a conducive work environment to enhance employees’ self-efficacy, while also developing flexible work policies that support work-life balance through workload management, rest periods, and a work culture that respects personal life.

Tax compliance refers to the behavior and actions of taxpayers in fulfilling their tax obligations in accordance with applicable laws and regulations. High tax compliance is crucial to ensuring the smooth flow of state funding, particularly in the motor vehicle sector. This study aims to provide empirical evidence regarding the influence of tax sanctions, tax socialization, and service quality on motor vehicle taxpayer compliance in Denpasar City. The research method used was accidental sampling, with a sample size of 100 respondents determined using the Slovin formula. Data were collected through questionnaires administered to motor vehicle taxpayers, and the data obtained were analyzed using multiple linear regression analysis. The results indicate that tax sanctions, tax socialization, and service quality have a positive influence on motor vehicle taxpayer compliance in Denpasar City. Specifically, the higher the public's understanding of tax sanctions and socialization conducted by the authorities, as well as the better the quality of service provided, the higher the level of taxpayer compliance in fulfilling their tax obligations. This study also shows a strong relationship between these variables in improving tax compliance. The theoretical implications of this study indicate that attribution theory and compliance theory can empirically support the idea that external factors such as sanctions and service quality, as well as educational processes through socialization, play a significant role in improving tax compliance. The practical implications of this study provide broader insights for researchers, the government, and related parties, and serve as a useful reference for stakeholders or future researchers interested in similar topics.

Taxpayer compliance plays a crucial role in increasing state revenue and supporting national economic development. This study aims to examine the relationship between tax morale, tax fairness, and tax complexity on the compliance of MSME taxpayers in Denpasar City. The research was conducted on MSME taxpayers who are actively registered with the Department of Cooperatives and MSMEs of Denpasar City. A purposive sampling technique was used to select a sample of 100 respondents from a total population of 29,949 MSME taxpayers in Denpasar. The data were analyzed using multiple linear regression. The results indicate that tax morale and tax fairness have a positive and significant relationship with MSME taxpayer compliance in Denpasar City. In contrast, tax complexity shows a negative but statistically insignificant relationship with taxpayer compliance. These findings provide empirical support for the Theory of Planned Behavior and Attribution Theory, highlighting the role of individual attitudes and perceptions in fulfilling tax obligations.

This study aims to analyze how socially constructed beauty standards shaped by media, popular culture, and the surrounding environment affect the social cognition of university students in evaluating peers who deviate from mainstream beauty norms. Within the campus environment, students often bring visual biases and prejudices toward others based solely on physical appearance, such as skin tone, body shape, and fashion style. This study adopts a qualitative approach with a case study method. Data were collected through in-depth interviews with four students from the State Islamic University of North Sumatra (UINSU) with diverse backgrounds.The results show that most students initially form judgments based on social schemas influenced by social media, past experiences, and peer environments. However, some participants demonstrated a shift in perspective after engaging in personal reflection, studying social psychology, and experiencing more diverse social interactions. They began to exhibit more empathetic attitudes and fairer judgments. This study highlights the importance of higher education in fostering critical awareness and promoting inclusive values and social sensitivity within academic environments.