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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 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 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 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.