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Land rights disputes arising from overlapping land certificates remain a complex agrarian law issue frequently encountered in Indonesia. This phenomenon reflects weaknesses in the land administration system, particularly in data collection, land measurement, and certificate issuance. Such disputes create conflicts, legal uncertainty, and reduced public trust in the land registration system. In practice, these disputes are generally resolved through civil litigation procedures in the District Court. This study aims to comprehensively analyze civil procedural law in resolving land rights disputes involving overlapping certificates and to examine the evidentiary strength of land certificates in judicial proceedings. This research employs a normative legal method using statutory and conceptual approaches, supported by primary and secondary legal materials. The findings indicate that dispute resolution begins with the filing of a lawsuit, followed by mediation, court examination, and the evidentiary process as the most crucial stage in determining lawful ownership. Land certificates serve as strong evidence; however, they are not absolute, as they may be challenged if administrative or substantive legal defects are identified. Judges play a central role in assessing certificate validity by considering land history, physical possession, good faith, and compliance with legal procedures. Nevertheless, the effectiveness of dispute resolution still requires improvement through better land administration, enhanced data accuracy, and stronger institutional integration.

Inclusive education aims to provide equal learning opportunities for all students, including those with special needs, within regular educational settings. However, mathematics learning in inclusive classrooms remains challenging because mathematical concepts are often abstract and require logical reasoning that may not be easily accessible to learners with diverse cognitive characteristics. Ethnomathematics has emerged as an alternative approach by integrating cultural practices, local wisdom, and students’ daily experiences into mathematics instruction, creating more meaningful and accessible learning environments. This study aims to analyze the development, implementation patterns, opportunities, and research gaps related to ethnomathematics in inclusive mathematics learning. A literature review method was employed by examining scientific publications from 2020–2025 obtained from Google Scholar, Scopus, ERIC, Springer, and ProQuest databases. Data were analyzed through content analysis involving reduction, classification, interpretation, and synthesis. The findings indicate that ethnomathematics has been implemented through cultural artifacts, digital teaching materials, and project-based contextual learning. The approach supports inclusive learning through multi-representational access, instructional adaptations, scaffolding strategies, and collaborative teaching practices aligned with Universal Design for Learning principles. Furthermore, ethnomathematics enhances students’ motivation, conceptual understanding, mathematical literacy, and cultural identity. Nevertheless, studies focusing on disability-specific adaptations and long-term learning outcomes remain limited and require further investigation.

This study aims to analyze public sentiment toward the hashtag #KaburAjaDulu, which has circulated widely on the social media platform X (formerly Twitter). The hashtag reflects the growing anxiety among the public, especially younger generations, regarding socio-political issues in Indonesia. The data were collected using web scraping techniques, focusing on user-generated tweets that contain the hashtag. A comprehensive text preprocessing phase was conducted to clean the raw data by removing irrelevant elements such as URLs, emojis, numbers, and punctuation. The research applies a hybrid classification approach using a combination of Support Vector Machine (SVM) and Random Forest algorithms to categorize sentiment into three classes: positive, negative, and neutral. The performance of the model was evaluated using metrics such as accuracy, precision, recall, and F1-score to determine the effectiveness of the classification. The study aims to demonstrate that combining algorithms can improve classification performance compared to using a single algorithm. This research contributes to the field of sentiment analysis and provides valuable insights for researchers, policymakers, and social observers in understanding public opinion trends in digital media.

This research was designed to explore the extent to which public beliefs influence the implementation of Digital traceability  systems in the halal industrial sector. The approach used was quantitative with a survey method, where questionnaires were distributed to 60 respondents who were consumers of halal products in Indonesia. Data were analyzed using simple linear regression via Microsoft Excel. Research findings indicate that public confidence has a positive and significant influence on the adoption of Digital traceability  systems, with a regression coefficient of 0.476 and a significance level of 0.000 (<0.05). In addition, the coefficient of determination (R Square) value of 0.219 indicates that public confidence contributes 21.9% to the implementation of the Digital traceability  system, while the rest is determined by other factors that were not researched. These findings confirm that public trust is an important element in encouraging acceptance of digital technology, especially in the halal industry which relies heavily on transparency and consumer confidence. Thus, implementing a Digital traceability  system that is supported by information openness and easy access to technology can be an effective strategy to strengthen consumer trust while expanding technology adoption.

The development of social media, especially TWITTER, has become one of the main means for people to express opinions and criticism on various issues, including the performance of law in Indonesia. This study aims to analyze public sentiment towards the performance of law based on TWITTER user comments using the Naïve Bayes algorithm. The research data consists of 1004 comments collected from several videos related to legal topics. The analysis process includes the stages of data crawling, pre- processing (text cleaning, normalization, and tokenization), labeling sentiment into positive, negative, and neutral, and testing the Naïve Bayes model. The results show that the Naïve Bayes algorithm is able to classify sentiment with an accuracy level of 93.73%. The distribution of sentiment from 1004 comments shows that the majority of public opinion is (negative/positive/neutral), which indicates that public perception of the performance of law is still (critical/positive). These findings are expected to be input for related parties to understand public opinion and improve the quality of legal performance in

Social media X (Twitter) has become the main platform for the Indonesian public to express opinions, including on the trend of 'kabur aja dulu' (let's just run away for a bit). This research aims to classify the sentiments of the public using the Naïve Bayes and Support Vector Machine (SVM) methods, and to compare the accuracy of both in sentiment analysis. Data was collected via the Twitter API with the hashtag #kaburajadulu, resulting in 2,067 tweets, which, after the cleansing process and manual labeling, left 385 data points. The analysis process followed the CRISP-DM stages, which include business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Model evaluation was conducted using a confusion matrix with accuracy, precision, and recall metrics. The classification results show that 82% of tweets have a positive sentiment and 18% negative. The Naïve Bayes algorithm achieved an accuracy of 86.49%, slightly lower than SVM, which reached 88.05%. In conclusion, Support Vector Machine is more effective in sentiment classification on public opinion data. This research contributes to the digital mapping of public opinion and recommends the development of automatic labeling methods as well as the exploration of advanced algorithms in the future.

QRIS (Quick Response Code Indonesian Standard) has become a widely used national digital payment standard. User satisfaction with this service needs to be monitored continuously to ensure its sustainability. This study aims to predict the level of QRIS user satisfaction based on their experiences and perceptions expressed organically on the Twitter social media platform. The method used is sentiment analysis with the Naive Bayes classification algorithm implemented using RapidMiner software. The research data was obtained from Twitter user comments collected through web scraping techniques. The text data then went through a preprocessing stage that included cleansing, stopword filtering, stemming, and tokenizing to be prepared as features ready to be processed by the model. The data was divided into training (80%) and testing (20%) subsets for model training and validation. The results showed that the Naive Bayes model was able to predict user satisfaction sentiment with an accuracy of 80.99%. These findings indicate that the model is highly accurate in identifying satisfied comments and sufficiently sensitive in detecting dissatisfaction. This study concludes that sentiment analysis of Twitter UGC data using Naive Bayes is an effective and efficient approach for predicting QRIS user satisfaction in real time. The practical implication of this study is to provide an automatic feedback system for service providers to monitor public sentiment and take targeted corrective actions.

The enactment of Indonesia's Law Number 20 of 2025 on the Code of Criminal Procedure (KUHAP 2025), effective January 2, 2026, introduces a paradigmatic shift in the coordination between investigators and public prosecutors: Article 58 mandates active coordination from the investigation stage, fundamentally departing from the sequential-passive model of the former KUHAP, while Article 70 imposes a strict seven-day deadline for indictment drafting after case files are declared complete. This study examines two interconnected questions: (1) how the legal framework governing investigator–prosecutor coordination is structured under KUHAP 2025 and related legislation; and (2) how that framework is implemented in practice at the Purwakarta District Prosecutor's Office. A normative–empirical mixed-method design was employed, integrating statutory, conceptual, and case-study approaches. Data were gathered through in-depth interviews with prosecutors and investigators at Purwakarta District Prosecutor's Office and Purwakarta Police Resort, case document analysis, and field observation. The theoretical framework combines Lawrence M. Friedman's Legal System Theory and Soerjono Soekanto's Law Enforcement Theory. Findings reveal that KUHAP 2025 delivers substantial normative advancement yet harbours three critical regulatory gaps: the absence of binding technical protocols for implementing mandatory active coordination, the lack of uniform and measurable case-file completeness standards, and no formal mechanism for resolving institutional disagreements on legal interpretation. On the ground, coordination at Purwakarta still operates under the old sequential-passive pattern despite the new law: case-file returns (P-19) remain frequent, driven primarily by absent expert testimony, insufficient factual narration in examination records, and mismatches between charged articles and legal facts. A Friedman–Soekanto diagnostic reveals simultaneous dysfunction across all three legal system components substance, structure, and legal culture with the entrenched 'waiting culture' between the police and the prosecution identified as the most resistant obstacle to reform.

This study aims to examine the influence of principal leadership and school culture on teacher discipline in public junior high schools (SMP Negeri) in Sembawa District, Banyuasin Regency. Teacher discipline is an important factor in supporting the effectiveness of the learning process and achieving educational goals. Therefore, understanding the factors that contribute to teacher discipline is essential for improving school performance. This study employed a quantitative research method with a purposive sampling technique. Data were collected through the distribution of questionnaires consisting of 66 statement items measured using a five-point Likert scale. The collected data were analyzed using statistical techniques to determine both partial and simultaneous effects of the independent variables on teacher discipline. The results indicate that principal leadership has a positive and significant partial effect on teacher discipline, as evidenced by a t-value of 5.127, which is greater than the t-table value of 1.9809. School culture also has a positive and significant partial effect on teacher discipline, with a t-value of 7.244 exceeding the t-table value of 1.9809. Furthermore, principal leadership and school culture simultaneously have a positive and significant effect on teacher discipline, as indicated by an F-value of 34.152, which is greater than the F-table value of 3.07. These findings suggest that strengthening principal leadership and fostering a positive school culture can significantly improve teacher discipline.

The rise of social media has created a digital public sphere that enables users to express their opinions on social and political issues openly and in real-time. One of the most discussed topics on social media platform X is the trending hashtag #IndonesiaGelap, which reflects public concern and criticism regarding various governmental and societal conditions. This study aims to conduct sentiment analysis on tweets containing the hashtag to determine the overall sentiment trend among users. The method employed in this research is the Naive Bayes classification algorithm, known for its simplicity and effectiveness in text classification. To enhance the model’s performance, Particle Swarm Optimization (PSO) is applied to optimize feature selection and parameter tuning. The dataset consists of public tweets collected via the Twitter API, followed by preprocessing, feature extraction using TF-IDF, and sentiment classification into three categories: positive, negative, and neutral. The results indicate that the integration of PSO significantly improves the classification accuracy of the Naive Bayes model compared to the baseline. The majority of tweets related to #IndonesiaGelap exhibit a negative sentiment, indicating widespread public dissatisfaction and criticism. This research is expected to contribute to a better understanding of public perception and serve as valuable input for stakeholders in addressing social issues in the digital age.

Given the important objectives that banks strive to achieve through financial stability and their role in ensuring its continuity and ability to face various economic challenges, many have expanded their policies beyond their traditional functions by adopting a range of additional practices and activities that contribute to strengthening their developmental role in society. Among the most prominent of these practices are corporate social responsibility (CSR) activities, which have become a crucial aspect of the work of contemporary financial institutions. In this context, this research highlights CSR practices in banks. It relied on a sample of nine Iraqi banks listed on the Iraq Stock Exchange, which are characterized by their continued banking operations and regular publication of their annual financial reports. The research period was set from 2014 to 2023, and included a set of statistical tests that incorporated a number of financial determinants as control variables to determine their contribution to enhancing the impact of CSR when included alongside it, and to define the nature of the relationship between the research variables. We have reached a number of conclusions, most notably that when regulatory variables are included in the analysis model, this effect becomes statistically insignificant, which indicates that banks’ interest in internal financial factors still outweighs their interest in social aspects.

This study discusses the practice of morning prayer as a form of lived religion within the school culture of a public elementary school. Morning prayer is understood not only as a formal religious activity, but also as a daily ritual that shapes students’ emotional experiences, religious habits, and social interactions. This study aims to explain the empirical practice of morning prayer, the social relationships formed through it, and its implications for religious education and school culture. The research employs a qualitative approach using school ethnography methods. Data were collected through observations, interviews with the principal, Islamic Religious Education (PAI) teachers, classroom teachers, and students, as well as documentation of the school’s religious activities. The findings show that students participate in morning prayer routinely every day before lessons begin, followed by the collective recitation of short surahs from Juz 30. The daily practice of morning prayer gradually becomes a habit for students in starting their learning activities, both at school and at home. Teachers perceive morning prayer as an opening activity for learning, as well as a means of fostering emotional calmness, discipline, and students’ religious character. Students also reported feeling calmer, happier, and more prepared to learn after praying. In addition, the presence of Juz Amma books, Asmaul Husna texts, the school prayer room (mushola), and the habituation of congregational dhuha prayer indicate the institutionalization of a religious culture within the school, even though these practices are not yet fully included in the official schedule. The findings indicate that morning prayer has become part of students’ daily school experience. Through routine collective prayer activities, students gradually develop emotional readiness, discipline, and religious habits before learning begins.

This study aims to examine how nepotism can manifest through the role of informal institutions and its influence on administrative integrity within the bureaucracy. The method used is literature analysis by examining various related scientific references, such as books, journal articles, and research, which are then analyzed descriptively and analytically through identification, classification, and data integration. The research findings indicate that nepotism does not only arise from weaknesses in the official system, but is also strongly influenced by the existence of informal institutions such as personal networks, social norms, and organizational culture. This practice tends to persist within a system because it gains social recognition, making it difficult to overcome solely with regulations. The consequences include a decline in employee professionalism, weak accountability, and erosion of administrative integrity, which impacts on reduced public trust in government institutions. The implications of this study indicate that a comprehensive approach is crucial in bureaucratic reform, through strengthening the official system and changing organizational cultural values ​​to produce transparent, accountable, and dignified government management.

The rapid growth of digital technology and social media has reshaped communication practices, consumer behavior, and marketing approaches, particularly among Generation Z, who are widely recognized as digital natives. For this generation, social media serves as a major channel for obtaining information and exploring product references before making purchase decisions. In this environment, influencer marketing has emerged as a prominent promotional approach because it can foster audience interaction, emotional connection, and trust more effectively than conventional advertising. This study examines the role of influencer marketing in shaping the digital behavior of Generation Z in Indonesia. A qualitative literature review method was employed by analyzing secondary sources drawn from academic journals, books, and related publications. The findings indicate that influencer marketing has a meaningful influence on information-seeking behavior, decision-making processes, and the level of digital engagement among Generation Z. Influencers are commonly viewed as more credible, relatable, and authentic sources of information. Furthermore, the effectiveness of influencer marketing is determined more by credibility, authenticity, and the quality of interaction than by follower count alone. These findings suggest that companies should adopt digital marketing strategies that are more interactive, personalized, and relationship-oriented in order to engage Generation Z more effectively.

Public service institutions currently utilize digital technology to improve information accessibility for society. Satres PPA and PPO Polresta Banyumas has an important role in providing services, protection, and education related to violence cases against women and children. However, information regarding services, reporting procedures, and educational materials is still not fully accessible to the public. This study aims to design and develop a service and educational website for Satres PPA and PPO Polresta Banyumas using the Laravel framework. The research method used in this study is the Waterfall method, which consists of requirement analysis, system design, implementation, testing, and maintenance stages. The website was developed using Laravel, MySQL, and Bootstrap to support responsive interface design. The results show that the developed website is able to provide service information, educational articles, reporting procedures, and contact information effectively. System testing results indicate that all website features function properly according to user requirements. The website is expected to improve public access to information and increase awareness regarding the protection of women and children.

Public Wi-Fi services (Wifi_STAKat) at the State Catholic College of Pontianak continue to face technical issues, such as network speed and connection stability, as well as non-technical challenges, including the responsiveness of administrators to user complaints. This study aims to analyze user satisfaction based on the five Servqual dimensions and to map improvement priorities using the Importance–Performance Analysis (IPA) method. The relationship between Servqual and IPA is explained by mapping GAP values (perception–expectation) into the four IPA quadrants to determine the urgency level of service improvements. A 4-point Likert scale was used to avoid neutral responses and strengthen the clarity of respondents’ perceptions. The results show that all dimensions have negative GAP scores, particularly responsiveness and reliability, which are directly related to technical indicators (speed, stability, coverage) and non-technical factors (responsiveness to complaints, ease of access. The study recommends integrating an IT-based monitoring system and increasing network capacity to improve service quality.

This study aims to analyze the implementation of information technology in improving the quality of public services. The research method used is library research by collecting and analyzing various scientific sources, such as journals, books, research articles, and government documents related to information technology and public services. The results show that the implementation of information technology through online service systems, official websites, and administrative information systems is able to improve the effectiveness, efficiency, transparency, and accessibility of public services. Information technology also helps accelerate administrative processes, reduce data management errors, increase employee productivity, and strengthen communication between the government and the community. In addition, the implementation of information technology supports the realization of e-government and good governance through increased accountability and information transparency. However, the implementation of information technology still faces several challenges, such as limited human resources, inadequate technological infrastructure, unstable internet connections, and the low ability of some communities to use digital services. Therefore, it is necessary to improve employee competencies, develop technological infrastructure, and conduct public socialization to optimize the implementation of information technology in public services. Overall, information technology has proven to be a strategic solution in creating modern, effective, efficient, transparent, and community-oriented public services.

This study aims to analyze corruption as a form of abuse of power within the public bureaucracy and its impact on the quality of public services in Indonesia. This study employs a qualitative approach using a literature review method based on journals, books, and official reports. The results indicate that corruption within the bureaucracy persists in various forms, such as extortion, abuse of authority, and budget manipulation. Contributing factors include low integrity among public officials, weak oversight, and the complexity of bureaucratic procedures. The resulting impacts include a decline in service quality, inequitable access to services, and a loss of public trust in the government. Furthermore, corruption hinders bureaucratic effectiveness and slows down the national development process. These conditions demonstrate that corrupt practices not only harm state finances but also broadly affect public welfare. Therefore, efforts are needed through bureaucratic reform, strengthened oversight, and enhanced civil servant integrity to achieve transparent and accountable public services that support the establishment of good governance.

The rapid development of social media, particularly Twitter, has given rise to a new form of social violence known as cyberbullying. This study aims to explore the phenomenon of cyberbullying on Twitter using Ulrich Beck's Risk Society Theory as an analytical framework. The research approach used is a literature review. This study perceives cyberbullying on Twitter as a modern, systemic risk, shaped by anonymity, cancel culture, and the individualization of risk. It acknowledges that Twitter's structural features, such as pseudonymous accounts and the rapid dissemination of information, exacerbate the potential for cyberbullying, while simultaneously positioning individual users as both victims and potential perpetrators of digital violence. These findings reinforce Beck's thesis that risks in advanced modernity are self-produced, institutionally distributed, and difficult to regulate, clearly reflected in the uncontrolled spread of cyberbullying in digital public spaces.

Job analysis is a key component of human resource management that plays a role in determining the tasks, responsibilities, and competencies required for a particular job. In various organizations, job analysis serves as the foundation for HR planning, recruitment, selection, employee placement, and performance evaluation. However, research on job analysis remains scattered across various studies focused on specific organizational contexts, necessitating a literature synthesis to gain a more comprehensive understanding of research developments in this field. Therefore, this study aims to analyze the development of research on job analysis and identify its role and contributions to human resource management. This study employed a literature review method by searching for scientific articles in the Google Scholar database using the Publish or Perish (PoP) application with the keyword “job analysis.” The initial search yielded 30 scientific articles, which were then screened based on topic relevance, open access, and publication years ranging from 2020-2026, resulting in 16 articles selected for further analysis. The findings indicate that the literature on job analysis can be grouped into three main themes: the role of job analysis in human resource management, its contribution to improving employee performance and productivity, and its implementation in employee placement and organizational governance. Overall, job analysis has proven to be a strategic tool for enhancing the effectiveness of human resource management. Further research is recommended to examine the implementation of job analysis in greater depth across various organizational contexts to enrich the development of human resource management theory and practice.