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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.

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 growth of information technology has driven changes in consumer behavior, one of which is through e-commerce platforms such as Shopee. This phenomenon has generated a large number of customer reviews, including those for local cosmetic products such as Wardah. These reviews serve as an important source of information for understanding customer perceptions and satisfaction levels. However, manual analysis of large and linguistically diverse datasets is inefficient and potentially subjective. This study aims to implement the multi-category Naive Bayes algorithm to classify the sentiment of Wardah product reviews on Shopee into three categories: positive, negative, and neutral. The data were collected using a web scraping technique and processed through a series of preprocessing stages including case folding, tokenization, stopword removal, stemming, and text cleaning. Subsequently, term weighting was performed using the TF-IDF method prior to classification. Model performance was evaluated using a confusion matrix as well as accuracy, precision, and recall metrics. The results indicate that the multi-category Naive Bayes algorithm achieved an accuracy of 86.00%, a precision of 86.63%, and a recall of 98.24%. This approach can assist business practitioners in objectively understanding customer opinions and support decision-making in business strategy and product development.

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.

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 investigates the decoupling phenomenon between ESG (Environmental, Social, and Governance) sustainability reporting and communal Tri Hita Karana (THK) sustainability practices in a Rural Bank in Bali. Through Ethnographic Content Analysis (ECA) of official documents from BPR Luhur Damai covering 2023–2025, this study identifies that the Sustainability Report (SR), prepared strictly according to Financial Services Authority Regulation (POJK) 51/2017, does not incorporate substantial THK practices, namely banten (ceremonial offerings) Rp131.6 million, dana punia (religious donations) Rp8.5 million, and monthly banjar (communal community unit) contributions, producing a Hindu religious expenditure to formal Social and Environmental Responsibility (SER) ratio of 10:1. Drawing on the Institutional Logics perspective, this study identifies four decoupling mechanisms: (1) cognitive, namely THK as taken-for-granted, not perceived as “sustainability”; (2) administrative, namely departmental silos between Compliance and General Affairs; (3) template, namely POJK 51/2017 provides no space for local wisdom; and (4) capacity, namely limited Human Resources (HR) and institutional capacity. These findings lead to the concept of “invisible sustainability,” that is, real sustainability contributions that are invisible to conventional reporting frameworks, and “cultural accounting gap,” that is, the absence of accounting categories for local cultural-religious contributions. The theoretical contribution is demonstrating that decoupling in Global South contexts is not merely symbolic compliance but results from structural misalignment between transnational and communal logics that renders local sustainability contributions institutionally invisible.

Based on the 2023 Indonesian Health Survey, the prevalence of overweight among adults reached 23.4% nationally and 24.5% in East Java Province. This condition highlights the need for food innovation, particularly high-fiber snacks suitable for overweight adults. This study aimed to develop cereal based on okara (soy pulp) flour and mung bean flour as an alternative high-fiber food product. Organoleptic testing was conducted on 30 semi-trained panelists evaluating color, aroma, texture, and taste using hedonic and hedonic quality tests. Data were analyzed using the Kruskal–Wallis test followed by the Mann–Whitney test, while nutrient content analysis was analyzed using One Way ANOVA followed by Duncan’s post hoc test. The results showed that in the hedonic test, color, texture, and taste parameters were significantly different (p<0.05), while aroma was not significantly different (p>0.05). In the hedonic quality test, color and taste showed significant differences (p<0.05), whereas aroma and texture did not (p>0.05). Overall, formulation 922 was the most preferred by panelists. The nutritional content of the cereal ranged from 407–410 kcal for energy, 76.44–77.53% carbohydrates, 8.91–9.66% protein, 6.80–7.30% fat, 5.20–5.51% moisture, 1.26–1.41% ash, and 9.72–10.90% total dietary fiber. The developed cereal is classified as a high-fiber food and has potential as a healthy snack for overweight adults.

The development of the digital economy has driven increased customer interaction through online chat services, making customer satisfaction a key factor in business success. Response speed and chat service quality are two important aspects in shaping the customer experience, but previous research has tended to examine them separately. This study aims to analyze the influence of online chat services and response speed on customer satisfaction partially and simultaneously. The method used is a qualitative approach with a literature review of 12 scientific articles from 2020–2025 obtained from academic databases such as Google Scholar and SINTA. The analysis technique used is descriptive-critical through the identification, comparison, and synthesis of previous research findings. The results show that online chat services have a positive effect on customer satisfaction, primarily through interaction quality such as information accuracy, ease of use, and problem-solving ability. Response speed has also proven to be an important determinant, where a fast response significantly increases customer satisfaction. However, speed without quality has the potential to decrease satisfaction. The discussion shows that the two variables have a complementary and inseparable relationship. Online chat services function as a medium for interaction, while response speed is a quality attribute that determines the effectiveness of the service. Therefore, the integration of both in one model is the main contribution of this research in filling the literature gap, especially in the context of e-commerce in Indonesia.

This study investigates the effect of total risk on firm performance and sustained growth among consumer non-cyclicals manufacturing companies listed on the Indonesia Stock Exchange (IDX) over the period 2019–2023. Total risk is operationalized through the systematic risk proxy (Beta/β), estimated via the Capital Asset Pricing Model (CAPM) framework as the covariance between individual stock returns and the market return divided by the variance of market returns, using the Jakarta Composite Index (JCI) as the market benchmark. Firm performance is measured through Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q, while sustained growth is operationalized following Gerson et al. (2025) as SG = b × ROE, where b denotes the earnings retention ratio. Panel data regression analysis is applied to 225 firm-year observations drawn from 45 companies, with model selection guided by the Chow and Hausman specification tests. The Fixed Effect Model (FEM) is adopted for ROA, ROE, and SG, while the Random Effect Model (REM) is applied for Tobin’s Q. Results indicate that systematic risk exerts a significant negative effect on ROA (β = −0.312; p < 0.01) and ROE (β = −0.278; p < 0.01), but is statistically non-significant for Tobin’s Q, suggesting that capital market pricing in Indonesia does not fully incorporate systematic risk information. Critically, systematic risk exerts the largest and most significant negative effect on sustained growth (β = −0.347; p < 0.01), revealing a dual transmission mechanism through which risk suppresses ROE while simultaneously inducing more conservative dividend policies, both of which constrain long-run growth sustainability. These findings carry important implications for corporate risk management strategy and empirically enrich the literature on risk, performance, and growth in emerging capital markets.

Village governance plays an important role in supporting the effectiveness of development planning and improving community welfare. This study aims to analyze financial management governance and the process of preparing the Village Revenue and Expenditure Budget (APBKal) in Kalurahan Poncosari, Bantul Regency, for the 2025 fiscal year. This research employs a qualitative approach using a case study method, involving in-depth interviews with key informants and documentation analysis of relevant regulations and financial reports. The results show that financial management in Kalurahan Poncosari has been implemented systematically through the stages of planning, implementation, administration, reporting, and accountability in accordance with applicable regulations. The planning process is conducted in a participatory manner through tiered community deliberations, such as hamlet-level deliberations and village development planning deliberations, involving residents. In addition, the use of digital systems such as E-RAB and Siskeudes supports transparency and administrative order. However, challenges remain, including limited budget flexibility due to mandatory programs from central and regional governments, limited human resource capacity, and shifts in community participation patterns. In conclusion, the governance of APBKal in Kalurahan Poncosari demonstrates compliance and accountability; however, improvements in administrative capacity and fiscal flexibility are needed to better respond to community needs.

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.

The Operational Aspect in Islam emphasizes that production activities must benefit humanity or be related to meeting human needs. For example, the selection of raw materials should not come from haram sources, the production process should be free from activities prohibited by Sharia, production should not be excessive, and there should be no waste. The Islamic view on human resources emphasizes that all workers are huan beings, not robots or business tools. A A Business Feasibility Study refers to an analysis of a business plan, both prior to its implementation and once the business is operating on a regular basis. The aim of this study is to evaluate the operational aspects and human resource management within the feasibility study of the Islamic-based convection business, Brand 57 Busana Pekalongan. This research employs a qualitative approach. The data were collected through field research, which involves conducting the study directly at the site where the phenomena related to the research problem occur. The techniques applied for data collection include observation, interviews, and documentation The result of this study indicate that the Brand 57 Busana pekalongan is feasible in terms of operational and human resource management aspects from a Sharia businesss feasibility study perspective because it has chosen a strategic location, good product quality, adequate production capacity, and technology utilization. In addition, the brand 57 Busana Pekalongan convection is deemed permissible for operational production activities from an Islamic perspective, such as production activities based on Islamic values and Maqashid Syariah. In the implementation of human resources management, the Brand 57 Busana Pekalongan convention has implemented job descriptions, a Muslim work ethic, a fair and decent salary distribution system.

This study aims to analyze the skills gap in the era of the Industrial Revolution 4.0 and the factors influencing it. The research employed a descriptive-analytical approach based on literature studies and the author’s analysis of the dynamics of formal education curricula and the development of industrial needs. The findings indicate that formal education curricula that are less adaptive to technological developments are the main factor causing the skills gap. In addition, the slow adaptation to technology in educational and industrial environments, as well as the unequal distribution of skills development across various regions in Indonesia, further widen the gap between graduates’ competencies and labor market demands. This condition affects the low readiness of the workforce in facing digital transformation and global competition. The study concludes that the skills gap is a strategic issue requiring serious attention from the government, educational institutions, and the industrial sector. Curriculum reform that is responsive to technological advancements, strengthening digital literacy, and ensuring equal access to training and skills development are essential steps to improve the competitiveness of Indonesian human resources. These efforts are expected to support poverty reduction, reduce social inequality, and achieve the long-term national development goals toward Indonesia Golden Vision 2045.

This study aims to analyze the effect of profitability, company size, and type of public accounting firm on Key Audit Matters (KAM), with audit fees as a moderating variable in manufacturing sector companies listed on the Indonesia Stock Exchange for the 2022–2024 period. This study used a quantitative approach with a purposive sampling method. Data were obtained from audited financial statements and annual reports published on the official Indonesia Stock Exchange website. The study sample consisted of 67 companies, with a total of 201 observations. Data analysis techniques used included descriptive statistical analysis, classical assumption tests, multiple linear regression, and Moderated Regression Analysis (MRA). The results showed that profitability had a significant negative effect on KAM disclosure, while company size had a significant positive effect on KAM disclosure. The type of public accounting firm showed a significant negative effect on KAM disclosure. Furthermore, audit fees did not moderate the relationship between profitability and KAM, but they did moderate the relationship between company size and type of public accounting firm on KAM disclosure. This study demonstrates that company and auditor characteristics play a significant role in determining the disclosure of Key Audit Matters in the independent auditor's report.