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Musi Rawas Utara Regency is categorized as an underdeveloped, frontier, and outermost (3T) region that still faces serious challenges in human development, particularly within the education dimension. Although the Human Development Index (HDI) indicates an upward trend, the School Enrollment Rate (SER) and the mean years of schooling at the secondary education level remain relatively low and lag behind other regions. This condition is influenced by limited access to secondary education, household economic vulnerability, and disparities in the quality and distribution of educators in remote areas. This policy paper aims to analyze secondary education issues as a primary obstacle to increasing the HDI of Musi Rawas Utara Regency and to formulate effective and sustainable policy alternatives. The method used is a qualitative descriptive analysis through a literature study, utilizing data from the Central Bureau of Statistics (BPS), regional planning documents, as well as relevant national regulations and policies. The analysis was conducted using a SWOT approach to identify the strengths, weaknesses, opportunities, and threats of the regional education policy. The results of the study show that improving the HDI requires integrated, affirmative, and region-based education policies. Three main policy alternatives recommended include expanding and equalizing access to secondary education, strengthening educational assistance and social protection for vulnerable families, and sustainably distributing and improving teacher quality. The implementation of these policies is expected to increase the SER, extend the mean years of schooling, and strengthen the quality of human resources as a foundation for sustainable development in Musi Rawas Utara Regency.

Lake Rawa Pening is one of Indonesia’s priority lakes facing serious ecological pressure due to the rapid proliferation of water hyacinth. This study aims to classify and map the distribution of water hyacinth in Rawa Pening Lake during the 2021–2025 period and to analyze the seasonal distribution patterns of water hyacinth. Sentinel-2 imagery processed on the Google Earth Engine platform was classified using the Random Forest algorithm combined with hybrid sampling and spectral indices (NDVI, NDWI, MNDWI, and SRI). Classification accuracy assessment showed high performance with an Overall Accuracy of 97.45% and a Kappa coefficient of 0.949. The results indicate significant spatial-temporal fluctuations, with the highest coverage recorded in March–April 2021 (855.75 ha) and the lowest in May–June 2022 (108.44 ha). Seasonal-Trend Decomposition using Loess (STL) revealed consistent seasonal patterns, with peak expansion occurring during the rainy season, particularly in January–February. Although initial implementation of lake management policies reduced coverage, subsequent increases suggest that control measures remain insufficiently sustainable. This study demonstrates the effectiveness of cloud-based satellite monitoring for evaluating lake management policies and supporting evidence-based environmental management strategies.

Stroke remains one of the leading causes of mortality and disability worldwide, including in Indonesia. The increasing prevalence of stroke and Years Lived with Disability (YLD) reflects its growing health burden. This study aimed to analyze trends in stroke prevalence and YLD in Indonesia during 2021–2023 using data from the Global Burden of Disease (GBD). A quantitative descriptive design with an ecological and time-trend approach was employed. Secondary data were obtained from the GBD Results Tool and analyzed using R version 4.4.1. The analysis focused on major geographical regions across Indonesia. The results showed a gradual increase in both stroke prevalence and YLD during the study period. Java recorded the highest prevalence and YLD, while Maluku and Papua showed lower prevalence but greater variation in YLD. These trends were associated with urbanization, unhealthy lifestyles, hypertension, diabetes, and unequal access to healthcare and rehabilitation services. Pearson correlation analysis demonstrated a very strong association between stroke prevalence and YLD (r > 0.99) across all years. The findings highlight increasing stroke burden and regional disparities, emphasizing the need for equitable healthcare access, risk factor control, and strengthened post-stroke rehabilitation programs.

Colorectal cancer and paralytic ileus are significant health concerns worldwide, including in Indonesia, where their prevalence and mortality rates have shown concerning trends. This study aims to compare the prevalence and mortality of paralytic ileus and colorectal cancer in Indonesia using data from the Global Burden of Disease (GBD) for the years 2019, 2021, and 2023. A secondary data analysis was conducted using GBD 2023 data, focusing on prevalence, incidence, and mortality rates for both conditions across 34 provinces in Indonesia. The study employed a time-trend analysis to observe the changes in disease burden over the specified years, along with examining the differences in disease characteristics based on sex, age groups, and regions. Results indicated that colorectal cancer has a higher burden of disease, with significantly higher prevalence and mortality rates compared to paralytic ileus. This highlights the urgent need for enhanced prevention, early detection, and management strategies for colorectal cancer in Indonesia. The findings emphasize the importance of integrated healthcare policies to address both conditions effectively, focusing on regions with the highest disease burden. Further research is recommended to explore the underlying risk factors and to evaluate the effectiveness of current healthcare interventions.

This study aims to analyze the trends in the prevalence of ischemic heart disease (IHD) in Indonesia from 2019 to 2023 based on data from the Global Burden of Disease (GBD) study, with a focus on gender differences between males and females. The data used in this study includes detailed prevalence data for IHD based on province and gender. The analysis reveals that the prevalence of IHD is higher in males than in females, with greater fluctuations observed in females, particularly after menopause. Although there are significant differences in the prevalence across several provinces, risk factors such as smoking, obesity, hypertension, and diabetes contribute significantly to the increasing prevalence of this disease. However, the differences in prevalence between provinces and genders are not always statistically significant, indicating that other factors such as access to healthcare, lifestyle, and socio-economic factors also influence the distribution of this disease. This study provides valuable insights for the development of gender-based heart disease prevention policies and introduces more targeted interventions.

This study examines the financial performance of PT Unilever Indonesia Tbk during the 2023–2025 period by evaluating key financial indicators, namely the Current Ratio (CR), Debt to Equity Ratio (DER), Return on Assets (ROA), and Return on Equity (ROE). The study aims to assess the company's financial condition and analyze the impact of its business transformation strategy on financial performance. A descriptive quantitative approach was employed using secondary data obtained from the company's published annual financial reports. Data analysis focused on comparing financial ratio trends over the three-year period to evaluate liquidity, solvency, and profitability performance. The findings indicate that the company's financial performance experienced fluctuations during the business transformation process. Liquidity and solvency gradually improved toward the end of the observation period, reflecting stronger short-term financial capability and a healthier capital structure. Profitability also demonstrated increased efficiency in utilizing company assets, although changes in equity returns indicated adjustments in capital management during the transformation process. Overall, the implementation of the company's transformation strategy contributed positively to strengthening financial performance and improving resilience in responding to changing business conditions and market competition. This study provides useful insights for management, investors, and other stakeholders in evaluating the effectiveness of corporate transformation strategies through financial ratio analysis and highlights the importance of maintaining financial stability to support sustainable business growth.

Literature reviews play a crucial role in scientific research because they serve to integrate previous research findings to build a conceptual framework that supports new research. However, in the practice of writing Classroom Action Research (CAR) articles, previous research is often presented descriptively without adequate conceptual synthesis. This study aims to systematically analyze the practice of citing prior research in the literature review of CAR articles as part of a systematic literature review. The study employs a Systematic Literature Review (SLR) approach following the PRISMA 2020 guidelines, which include the stages of identification, screening, eligibility assessment, and literature synthesis. Literature sources were obtained from various academic databases such as Scopus, Web of Science, Google Scholar, and Crossref using keywords relevant to classroom action research and literature reviews. Data analysis was conducted through thematic analysis to identify patterns and trends in the writing practices of previous research in the literature review of classroom action research. The results indicate that literature review writing in action research articles is still dominated by a descriptive approach that presents previous research sequentially without adequate conceptual integration and thematic synthesis. Furthermore, critical evaluation of prior research methodologies remains limited, meaning that literature reviews do not yet fully serve as a foundation for developing the theoretical framework of the research. The findings highlight the importance of applying a systematic literature review approach in writing PTK literature reviews to produce a more analytical, systematic, and integrated synthesis of the literature.

Online transportation has become an essential component of modern urban mobility, significantly transforming the way people travel while creating new challenges related to service quality, safety, customer satisfaction, sustainability, and its impact on conventional public transportation. This study aims to examine the development of research on online transportation through a bibliometric analysis combined with a Systematic Literature Review (SLR). Data were collected from the Scopus database using the keyword "Online Transportation" and filtered using the PRISMA framework, resulting in 90 eligible articles for analysis. The bibliometric analysis was conducted using VOSviewer to identify publication trends, leading contributing countries, author affiliations, journal sources, and the most frequently occurring keywords. The findings reveal that research on online transportation remains relatively limited despite showing a gradual increase in recent years. Indonesia emerged as the country with the highest number of publications, followed by the United States, China, Japan, Malaysia, and the United Kingdom. Frequently occurring keywords indicate that online transportation research is commonly associated with traffic management, drivers, passenger safety, customer satisfaction, service quality, employment, and user loyalty. These findings suggest substantial opportunities for future studies, particularly in the areas of regulatory frameworks, sustainable transportation, traffic safety, digital technology integration, and the development of intelligent transportation systems to support more efficient, inclusive, and sustainable urban mobility.

The quality of life and well-being of women in Indonesia can be measured through the Female Life Expectancy indicator. Data on Female Life Expectancy from 2022 to 2024 shows a nationally positive trend; however, a significant disparity persists across provinces, particularly between the Western and Eastern regions of Indonesia. The nation still faces challenges in ensuring an equitable quality of life for women, as evidenced by the national Female Life Expectancy (FLE) in 2024 at 74.21 years, which remains lower than ASEAN counterparts such as Singapore at 83.86 years. Furthermore, regional imbalances are reflected in the performance gap between D.I. Yogyakarta (77.4 years) and West Sulawesi (68.28 years). This study aims to analyze the effects of Women's Income Contribution, Access to Clean Water, the Number of Families Receiving Social Assistance, and Women's Mean Years of Schooling on Female Life Expectancy in Indonesia during the 2022–2024 period. The estimation method applied in this research is the Fixed Effect Model (FEM) via a quantitative panel data regression approach, spanning an observation area of 33 provinces (n=99). Based on the analysis, Female Life Expectancy is proven to be positively and significantly influenced by Women's Mean Years of Schooling and Access to Clean Water. These findings indicate that human resource quality and environmental conditions serve as dominant factors in driving up Female Life Expectancy. Therefore, government policy interventions should ideally focus on expanding educational access for women and ensuring the equitable distribution of clean water infrastructure.

Technological advances and increasing job demands have made work stress a major concern in modern industrial environments. Noise is one of the physical workplace factors that may contribute to work stress. This study aimed to analyze the relationship between noise exposure and work stress among workers in the spinning department of PT X. A quantitative cross-sectional design was employed, involving 80 workers selected through purposive sampling. Noise levels were measured using a sound level meter, while work stress data were collected through a standardized questionnaire. Data were analyzed using the Chi-Square test.Most respondents were over 35 years old (80%) and female (54%). The highest noise level was recorded in the spinning room (102.17 dBA), while the fiber preparation room had the lowest level (84.07 dBA). Most workers experienced mild work stress (86.25%), whereas 13.75% reported moderate to high stress. The Chi-Square test showed no statistically significant relationship between noise and work stress (p = 0.074). However, the Likelihood Ratio test indicated a significant positive trend (p = 0.021). These findings suggest that excessive noise exposure may increase work stress and highlight the need for effective noise control, hearing protection, and stress management programs in the workplace.

Evolving tourism trends indicate a transition among tourists from merely visual recreation (hedonic) toward transformative travel (eudaimonic), which is oriented toward self-reflection and the search for meaning in life. Museum Topeng Cirebon holds significant potential for transformative tourism due to its mask collection that is rich in life philosophies. The urgency of this research is to analyze these transformative tourism experiences to support the quality of tourists' intellectual experiences and the sustainability of local culture. This qualitative research employed thematic analysis with purposive sampling techniques, involving 70 respondents who completed a Google Form questionnaire, which was further supported by interviews and a literature review. The results from the pre-visit phase showed that initial motivations were dominated by hedonic tourism at 37.1%. During the visit, a transformation occurred; tour guides acted as human catalysts in building narrative engagement (62.9%), and the chronological, philosophical flow of the masks sparked an awakening of consciousness for 80% of respondents. In the post-visit phase, eudaimonic impacts were experienced by 91.4% of respondents, including an expanded worldview (37.1%) and a commitment to becoming agents of cultural change (27.1%). However, operational challenges remain, including inconsistent opening hours and a lack of digital self-information facilities.

The development of digital governance has accelerated the transformation of public financial management through e-budgeting, e-reporting, and integrated digital financial systems. However, studies discussing digital public financial management in cross-border areas remain fragmented and dispersed across disciplines. This study aims to systematically map the development of research on digital public financial management in cross-border contexts through publication trends, influential journals, active researchers, keyword patterns, countries, institutions, and research areas. This research employed a qualitative approach using a Systematic Literature Review (SLR) and bibliometric analysis based on 48 Scopus-indexed articles published between 2020 and 2026. The findings indicate that publications increased significantly after 2023, reflecting growing scholarly interest in cross-border digital finance and governance. The literature is dominated by economics and finance perspectives, while public financial governance and fiscal accountability in border areas remain underexplored. In addition, knowledge production is still concentrated in a limited number of countries and institutions, particularly in Europe. This study contributes by providing an intellectual mapping of the field and identifying opportunities for future research integrating digital governance, public financial management, and border studies.

The development of technology in the digital era has significantly altered consumer behavior, particularly for Generation Z, who are known as digital natives. This group possesses unique characteristics, highly relying on social media to seek product information before making purchasing decisions. This study aims to analyze digital marketing management strategies through social media in enhancing brand engagement and loyalty among Generation Z consumers, as well as to identify the key determinants of its success. The research method employed is descriptive qualitative, utilizing literature review as the data collection technique across prior scientific sources. The analysis reveals that the implementation of digital marketing strategies based on visual content and short-form videos on platforms such as TikTok and Instagram is proven to be highly effective in capturing the audience's attention rapidly. In addition to content format, collaboration with highly credible influencers and the application of authentic, responsive two-way communication serve as the main pillars in building emotional proximity and trust among young consumers. Operationally, this strategy offers cost efficiency and a broader market reach. The conclusion of this study emphasizes that the optimal integration between management information systems and interactive, adaptive communication approaches toward digital trends is the main key to winning the market and sustaining the long-term loyalty of Generation Z.

Risk factors for melasma have been identified at several points such as the use of birth control pills, cosmetics, sun exposure, estrogen therapy, decreased thyroid and ovarian function, ovarian tumors, nutrition, drugs that are classified as phototoxic or photoallergic, and epilepsy drugs. This article aims to determine the incidence of melasma and its risk factors. This study uses articles collected from the Google Scholar database. The data collection step uses the keyword "Risk Factor Melasma" according to the title and keyword criteria. The articles used are publications in the 2018-2023 year range. The stages of analysis are carried out using VOSviewer software for visualization and trend analysis in the form of bibliometric maps. The bibliometric approach was applied to identify publication patterns, research developments, and relationships among topics related to melasma risk factors. Based on the visualization results, 100 selected documents were published within 5 years, from 2018 to 2023. The findings provide an overview of the main research trends and contribute to a better understanding of the incidence of melasma and the factors associated with its occurrence

Maternal hypertension remains one of the major contributors to maternal morbidity and mortality in Indonesia and globally. This study aimed to analyze the prevalence, mortality trends, and geographical disparities of maternal hypertension in Indonesia during the 2022–2023 period. The research employed a descriptive design using secondary data obtained from official reports of the Indonesian Ministry of Health, national health surveys, and Maternal Perinatal Death Notification (MPDN) data. Data analysis was conducted descriptively by examining prevalence rates, maternal mortality due to hypertension, regional distribution, and temporal trends across provinces in Indonesia. The findings showed a slight but consistent decline in both the prevalence and mortality rates of maternal hypertension from 2022 to 2023 in most provinces. However, significant regional disparities remained evident. Provinces in eastern Indonesia, including Papua Barat, Nusa Tenggara Timur, Maluku, and several provinces in Sulawesi and Kalimantan, consistently recorded higher prevalence and mortality rates compared to provinces in Java and Bali. Meanwhile, provinces with better healthcare infrastructure and maternal referral systems demonstrated lower mortality outcomes. The study also revealed a strong association between high prevalence and increased maternal mortality, indicating the importance of healthcare accessibility, antenatal care quality, and emergency obstetric services in reducing maternal health burdens. These findings emphasize the need for region-specific maternal health interventions, improved healthcare distribution, early detection programs, and strengthened referral systems to reduce maternal hypertension disparities and improve maternal health outcomes in Indonesia.

This study aims to explore the phenomenon of using a second Instagram account among Generation Z as a strategy for impression management and privacy protection. Amidst the dominance of a culture of show-off and hegemonic aesthetic standards on primary accounts, Generation Z tends to experience aesthetic fatigue and social pressure due to scrutiny from diverse audiences (context collapse). Using Erving Goffman's Dramaturgy theory, this study examines how individuals construct distinct identities on the front stage and back stage. The research method used is descriptive qualitative. Data were collected through in-depth interviews with five Generation Z informants who have multiple accounts, as well as passive participant observation of their digital activities. The sampling technique used was purposive sampling, while data analysis followed the Miles and Huberman model, which includes data reduction, data presentation, and drawing conclusions. The results show that the primary account functions as a highly curated front stage to maintain professional and social reputations. Conversely, the second account functions as a back stage that allows Generation Z to engage in emotional catharsis, honest self-disclosure, and identity experimentation through unique names (pseudonyms). The use of a second account is a strategic response to reclaim personal authority over their life narratives from the pressure of algorithms and public judgment. The study concludes that second accounts are not just a technological trend, but rather a self-defense mechanism for Generation Z to maintain authentic space and maintain mental health amidst massive digital transparency.

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.

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, particularly TikTok, has played a significant role in shaping beauty trends and constructing ideal facial standards among young generations. The TikTok Beauty phenomenon not only provides diverse makeup references but also reinforces specific visual representations that influence perceptions of beauty. This study aims to examine the relationship between the TikTok Beauty phenomenon, the process of facial standardization, and its implications for the development of makeup techniques. A qualitative approach was employed through content analysis and literature review. Primary data were obtained from observations of popular TikTok videos under the hashtags #beautytrend, #makeup, and #tiktokbeauty, while secondary data were drawn from scholarly literature on beauty standards, social construction, and social media algorithms. The findings indicate that TikTok strengthens certain beauty standards such as fair skin, slim facial contours, and a flawless appearance which in turn influence techniques like complexion layering and visual manipulation. However, the platform also provides space for more inclusive and diverse beauty narratives. This study recommends enhancing aesthetic literacy to ensure that makeup practices prioritize diversity and the unique characteristics of each individual.

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.