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Pulmonary Tuberculosis (TB) is a contagious infectious disease caused by the bacterium Mycobacterium tuberculosis through droplets from patients diagnosed with TB. Based on the Global TB Report 2024, WHO reported that Indonesia ranks second in the world, where 81% of cases were confirmed and 90% of them had received treatment, where there was an increase in the number of cases compared to 2023 with 77% of confirmed cases and 88% of them received treatment. The increase in the number of pulmonary TB cases is inseparable from factors that determine the transmission of M. tb such as the concentration of organisms in the air related to ventilation and the length of time a person inhales contaminated air. To determine the relationship between ventilation conditions and home lighting to the incidence of pulmonary TB in the working area of ​​the Glugur Darat Health Center in 2025 This study is an analytical study with a cross-sectional study design. Sample selection used the consecutive sampling method with 56 patients who met the inclusion criteria. Of the 56 people who met the criteria, 30 people (53.6%) were pulmonary TB sufferers and 26 people (46.4%) were not pulmonary TB sufferers. The majority of respondents were male (38 people) and the highest number was found in the 18-59 age range (48 people) (85.7%). Regarding ventilation conditions, 34 people (60.7%) did not meet adequate ventilation requirements, and 29 homes (51.8%) did not meet adequate lighting requirements. There was a relationship between ventilation conditions and the incidence of pulmonary tuberculosis in the Glugur Darat Community Health Center work area, but there was no relationship between home lighting and the incidence of pulmonary tuberculosis in the Glugur Darat Community Health Center work area.

Cloud job-length prediction remains challenging when the target distribution is highly skewed and contains rare extreme values. This study proposes a log-transformed, regime-based machine learning framework for robust prediction of cloud job length, represented in million instructions (MI). The approach integrates sequential feature engineering, logarithmic target transformation, weighted learning, and regime-aware modeling to distinguish between normal and extreme job-length behavior. Using an ordered GoCJ-derived cloud job-length sequence of 1000 jobs, the dataset exhibits a heavy-tailed distribution, with a mean of 129,662 MI, a median of 93,000 MI, a 95th percentile of 525,000 MI, a 99th percentile of 900,000 MI, and a skewness of 3.695. The proposed model is evaluated against sequential baselines and stronger machine learning baselines, including Naive_Last, RollingMean_5, Global_Log_ExtraTrees, RandomForest, GradientBoosting, and MLP_Log. On the main test split, the proposed Regime_Log_ExtraTrees achieved the best RMSE of 206,255.66 and the least negative R² of −0.01062, while Global_Log_ExtraTrees remained competitive in terms of MAE, MedAE, and RMSLE. Additional walk-forward validation confirms that the regime-aware model consistently achieves the best mean RMSE and mean R² across temporal folds. Ablation results further show that regime-aware learning is the primary contributor to robustness, although accurate prediction of extreme jobs remains challenging. These findings indicate that log-transformed, regime-based learning provides a practical and more robust strategy for cloud job-length prediction under heavy-tailed workload conditions.

Presidential Regulation Number 10 of 2021 on Investment Business Fields introduces a fundamental transformation in Indonesia’s investment regulatory regime by replacing the previous negative list approach with a positive list system. This regulatory shift significantly affects the structure of investment liberalization, particularly in the industrial sector, which serves as the backbone of the national economy. This study aims to analyze the regulatory changes introduced by Presidential Regulation 10/2021 and examine their juridical and practical implications for the investment climate and industrial business actors. Using a normative juridical method through the analysis of legislation, policy documents, and academic literature, this research finds that the regulation enhances investment openness, expands foreign ownership, simplifies risk-based licensing, and strengthens legal certainty through the classification of priority business fields, mandatory partnerships with cooperatives/MSMEs, and conditioned business categories. However, its implementation still faces challenges, including the harmonization of sectoral regulations, regulatory–political dynamics, and the government’s supervisory capacity. Overall, Presidential Regulation 10/2021 has the potential to strengthen the attractiveness of the industrial sector and its integration into global value chains, yet its effectiveness strongly depends on consistent implementation and cross-sector policy alignment.   Keywords: Presidential Regulation 10/2021, investment regulation, investment liberalization, industrial sector, investment policy.  

Food security is a complex issue closely related to various aspects such as agriculture, nutrition, health, and the environment. In the context of global development, food security is an integral part of the Sustainable Development Goals (SDGs), particularly Goal 2: Zero Hunger. This study aims to analyze the implementation of food security policies in supporting the achievement of the SDGs and to identify the factors that hinder the successful implementation of these policies. This research uses a qualitative approach with a literature study method, examining various secondary data sources including books, journal articles, laws and regulations, official government reports, mass media, and relevant online publications. The results show that the Indonesian government has undertaken various efforts to achieve food security through strengthening regulations, starting from Law Number 18 of 2012, Government Regulation Number 17 of 2015, and Presidential Regulation Number 125 of 2022. These efforts are supported by increased budget allocation, local wisdom-based food diversification programs, food estate programs, and strengthening national food reserves through cross-sectoral coordination. However, the implementation of these policies still faces four structural constraints, namely high population growth, the conversion of agricultural land, the impact of climate change on agricultural productivity, and low interest among the younger generation, which threatens farmer regeneration. The implications of this study indicate that the successful implementation of food security policies in supporting the achievement of the SDGs requires comprehensive, sustainable strategies and effective cross-sector collaboration.

The role of ports as crucial nodes in the global supply chain positions the maritime sector as one of the most dynamic industries worldwide. This research analyzes the strengthening of business law support maritime sector integration to enhance port operational efficiency and the role of business law instruments in realizing the principle of fair competition within ports. This research employs a normative legal approach focusing on the study of existing legal norms and regulations governing port management and maritime integration. The strengthening of business law in the maritime sector plays a crucial role in improving port operational efficiency. A strong and well coordinated business law framework will create ports that are more efficient, competitive, and adaptive to the changing demands of the global market. Several key principles must be developed. First, rules on information disclosure and accountability to ensure transparency in port governance. Second, prohibitions against abuse of dominant positions and oversight of vertical integration to prevent anti-competitive practices. Third, clear contractual norms and governance structures for public private partnerships (PPP), including proportional risk-sharing mechanisms to ensure fairness and efficiency in infrastructure development. Fourth, multi-level governance alignment across national and regional authorities to prevent incentive distortions.

Digital revolution and the disruption of the global labor market have made public organizations, especially vocational training institutions, even more complicated. This study seeks to examine the impact of dynamic skills on institutional resilience, with innovative leadership serving as a mediating variable. The study employed a quantitative methodology, utilizing data collected from 180 employees at the Medan Vocational and Productivity Training Center (BBPVP). We used Structural Equation Modeling based on Partial Least Squares (SEM-PLS) to look at the data. The findings indicate that dynamic capabilities exert a positive and significant influence on institutional resilience, underscoring the necessity for an organization to identify, capitalize on opportunities, and adapt to change. Dynamic qualities also have a big effect on inventive leadership, which is very important for making organizational change happen. Innovative leadership demonstrably influences institutional resilience and serves as a partial mediator between dynamic capabilities and institutional resilience. This research offers a theoretical advancement by synthesizing institutional theory, dynamic capacities, and innovative leadership to elucidate public organizational resilience. In practical terms, the findings of this study have significant significance for enhancing the adaptive capacity of vocational training institutions in the context of digital disruption.

This study aims to analyze the spatial pattern of poverty in Gorontalo Province in 2024 using global and local spatial autocorrelation approaches. The data used are the percentages of the poor population in each regency/municipality, obtained from the BPS. The analyses include descriptive statistical analysis, the Moran's Index test for global spatial autocorrelation, and the Local Indicators of Spatial Association (LISA) for local autocorrelation. The results show that poverty in Gorontalo Province tends to be unevenly distributed and exhibits a significant spatial pattern. The Moran's Index indicates positive spatial autocorrelation, where areas with high poverty levels tend to be adjacent to other areas with similarly high poverty levels. The LISA results identify Bone Bolango Regency as a High-Low area, meaning it has a high poverty rate but is surrounded by areas with low poverty rates. These findings highlight the importance of spatial approaches in formulating more targeted poverty alleviation policies.

This study examines the local wisdom values of the Javanese and Batak ethnic groups in maintaining harmony between humans and nature, as well as their relevance to shaping the spirituality of Generation Z. The research method used is descriptive qualitative with a library research approach. Data were obtained from books, scientific articles, and previous studies. The findings show that Memayu Hayuning Bawana and Habonaron Do Bona both emphasize balance and harmony among humans, nature, and God. These values can be applied by Generation Z to develop ecological spirituality rooted in local wisdom and aligned with modern challenges. This study contributes to strengthening the spiritual identity of young generations in the digital era through the revitalization of local wisdom values, The younger generation can find a more holistic and harmonious life guide, while strengthening their spiritual identity amidst the currents of globalization and digitalization. This research contributes to efforts to shape the character and spirituality of an environmentally conscious young generation, based on local wisdom.

The phenomenon of language globalization has brought a significant influence on the communication patterns and cultural identity of Generation Z, including those who adhere to indigenous belief systems. The global trend that emphasizes the dominance of foreign languages often leads to a decline in appreciation for local languages and the spiritual values embedded within them. This article aims to examine the role of multilingual literacy as a means of strengthening the spirituality of Generation Z adherents of indigenous beliefs in facing the challenges of language globalization. The research method used is a literature study by reviewing various theoretical sources and relevant research findings from the past five years. The results indicate that multilingual literacy not only enhances cross-cultural communication skills but also strengthens the spiritual awareness and cultural identity of Generation Z through the preservation of local languages and the interpretation of local values in a modern context. Therefore, multilingual literacy can serve as an effective strategy for developing a generation that is religious, has strong character, and remains rooted in its traditional beliefs amidst the rapid flow of globalization.

High dependence on the United States Dollar (USD) in international transactions has long been a challenge for economic stability in the Southeast Asian region, especially amidst global exchange rate fluctuations and geopolitical tensions. This study aims to analyze the effectiveness of Local Currency Settlement (LCS) cooperation in supporting intra-ASEAN trade stability. The main focus of this study is how local currency mechanisms can mitigate exchange rate risks and strengthen regional economic integration as part of a de-dollarization strategy. The research method used is descriptive qualitative with a literature review approach, relying on secondary data from central bank reports, ASEAN policy documents, and relevant academic literature. The results show that the implementation of the LCS framework, particularly in countries such as Indonesia, Malaysia, and Thailand, has provided more efficient transaction alternatives by reducing double conversion costs. However, its effectiveness still faces challenges such as low awareness among business actors, limited local currency liquidity compared to the USD, and the need for broader cross-border digital payment system integration. These findings imply the need for strengthened synergy between central banks in the ASEAN region and increased literacy for the private sector so that the economic stability benefits of LCS can be optimally achieved. This strategy not only strengthens monetary sovereignty but also encourages a more resilient ASEAN economic integration against external shocks.

The retention of customers in the retail banking sector is a critical economic imperative; however, predictive modeling is frequently hindered by severe class imbalance and the “Black Box” nature of complex algorithms. This study proposes a Heterogeneous Stacking Ensemble framework integrating XGBoost, CatBoost, and Random Forest base learners with a Logistic Regression meta-learner to forecast customer attrition. To overcome the pervasive “Majority Class Bias,” we introduce a “Dual-Imbalance Defense” that synergizes the Synthetic Minority Over-sampling Technique (SMOTE) with algorithmic cost-sensitive penalization. Furthermore, moving beyond standard accuracy metrics, the framework mathematically derives a dynamic classification threshold to guarantee a strict 0.90 recall rate, actively optimizing the capture of at-risk capital. Model opacity is addressed through the integration of a SHapley Additive exPlanations (SHAP) TreeExplainer. This cooperative game theory approach provides localized, patient-level “Reason Codes” for regulatory compliance and reveals global systemic vulnerabilities, including non-linear drivers such as the “Product Paradox.” Achieving a 0.90 recall rate and an AUC of 0.8654, this framework provides a statistically robust and operationally transparent tool for targeted customer retention.

Based on data from FAO (Food and Agriculture Organization of The United Nations), it has been predicted that the aquaculture subsector will become one of the most relied-upon resources in the future, especially in meeting food needs, fish-based nutritional needs, and empowering the global community's economy (FAO, 2016). Catfish is a type of freshwater fish that can grow and develop well because it can be cultivated in limited land areas (Marsela, 2018). The frequency of feeding is one of the important factors that need to be considered in catfish farming. To determine the effect of different feeding frequencies on the absolute weight of dumbo catfish, a study was conducted using an experimental design called the Completely Randomized Design (CRD), with 3 treatments and a total of 8 replications. The test treatments were as follows: Treatment 1 (feeding twice a day), Treatment 2 (feeding three times a day), and Treatment 3 (feeding four times a day). The results of the ANOVA test showed a significant value of 0.000 (P < 0.05), indicating a significant difference in each of the different feeding frequencies. The analysis of the Least Significant Difference (LSD) test at a 5% significance level also showed that the relationship between each treatment had a significant value of 0.000 (P < 0.05). The average absolute weight of the fish for Treatment 1 was 12.99 grams, for Treatment 2 was 15.03 grams, and for Treatment 3 was 17.03 grams. The highest growth in the absolute weight of dumbo catfish fry occurred in Treatment 3 (feeding four times a day).

Object detection plays a crucial role in intelligent transportation systems, particularly for outdoor traffic monitoring applications that require accurate and real-time performance under limited computational resources. Recent developments in YOLO-based architectures have introduced multiple model variants; however, their practical performance under constrained training conditions remains insufficiently explored. This study presents a comparative evaluation of YOLOv5, YOLOv7, and YOLOv8 for outdoor traffic object detection using a real-world dataset and identical experimental settings. The main objective of this research is to analyze the robustness and detection quality of different YOLO variants when trained with a limited number of epochs, reflecting practical deployment scenarios. All models were trained and evaluated using the same dataset, preprocessing pipeline, and hardware configuration to ensure a fair comparison. Performance evaluation was conducted using multiple metrics, including precision, recall, mAP@50, Precision–Recall curves, area under the curve (AUC), and peak F1-score. Experimental results indicate that YOLOv5 outperformed YOLOv7 and YOLOv8 in terms of overall detection stability and robustness. The merged Precision–Recall analysis shows that YOLOv5 achieved a higher effective AUC and superior mAP@50, reflecting better global detection performance. In addition, YOLOv5 exhibited a higher peak F1-score, indicating a more balanced trade-off between precision and recall. In contrast, YOLOv7 and YOLOv8 showed performance degradation under limited training conditions despite their more advanced architectures. These findings suggest that YOLOv5 remains a reliable and efficient solution for outdoor traffic object detection, particularly in resource-constrained environments. The study highlights the importance of comprehensive evaluation metrics and practical experimental settings when selecting object detection models for real-world applications.

Penelitian ini mengkaji transformasi strategis manajemen risiko finansial melalui penerapan Digital Twins (DT) dengan pendekatan Systematic Literature Review (SLR). DT berevolusi dari sekadar model manufaktur menjadi sistem cerdas yang mampu memprediksi perilaku entitas finansial secara real-time. Hasil kajian menunjukkan bahwa DT mendukung kerangka Prevention, Preparedness, Response, Recovery (PPRR), memperkuat resiliensi rantai pasok, serta meningkatkan efektivitas stress testing perbankan sesuai regulasi Basel III. Selain itu, DT berperan dalam deteksi penipuan, akuntansi karbon, dan simulasi kebijakan makroekonomi. Studi ini menegaskan bahwa DT mampu meningkatkan akurasi prediksi risiko hingga 95% dan mengurangi downtime operasional sebesar 20%. Namun, keterbatasan standar global, integrasi data lintas sistem, serta hambatan regulasi masih menjadi tantangan utama. Agenda riset masa depan diarahkan pada pengembangan interoperabilitas global, integrasi teknologi AI, serta evaluasi ROI jangka panjang untuk memperkuat ketahanan finansial berbasis DT.

Object detection plays a crucial role in intelligent transportation systems, particularly for outdoor traffic monitoring applications that require accurate and real-time performance under limited computational resources. Recent developments in YOLO-based architectures have introduced multiple model variants; however, their practical performance under constrained training conditions remains insufficiently explored. This study presents a comparative evaluation of YOLOv5, YOLOv7, and YOLOv8 for outdoor traffic object detection using a real-world dataset and identical experimental settings. The main objective of this research is to analyze the robustness and detection quality of different YOLO variants when trained with a limited number of epochs, reflecting practical deployment scenarios. All models were trained and evaluated using the same dataset, preprocessing pipeline, and hardware configuration to ensure a fair comparison. Performance evaluation was conducted using multiple metrics, including precision, recall, mAP@50, Precision–Recall curves, area under the curve (AUC), and peak F1-score. Experimental results indicate that YOLOv5 outperformed YOLOv7 and YOLOv8 in terms of overall detection stability and robustness. The merged Precision–Recall analysis shows that YOLOv5 achieved a higher effective AUC and superior mAP@50, reflecting better global detection performance. In addition, YOLOv5 exhibited a higher peak F1-score, indicating a more balanced trade-off between precision and recall. In contrast, YOLOv7 and YOLOv8 showed performance degradation under limited training conditions despite their more advanced architectures. These findings suggest that YOLOv5 remains a reliable and efficient solution for outdoor traffic object detection, particularly in resource-constrained environments. The study highlights the importance of comprehensive evaluation metrics and practical experimental settings when selecting object detection models for real-world applications.

English is an international language that plays a vital role in education and technology; therefore, students are required to master reading comprehension skills, especially narrative texts, to face the challenges of globalization. This study, entitled "Improving Students' Reading Comprehension of Narrative Texts Through Storytelling Activities Using Webtoons in Grade I of MA Daruttholibin Watumalang," aims to improve students' reading comprehension of narrative texts through storytelling activities using Webtoons as a learning medium. This study employed a Classroom Action Research (CAR) design conducted in two cycles, each consisting of planning, action, observation, and reflection. Data were collected using descriptive qualitative methods through interviews, tests, and classroom observations. The research procedure began with a pre-test, followed by the implementation of treatment and post-tests in each cycle. The findings indicate that the use of storytelling supported by Webtoons effectively improved students' reading comprehension. This improvement was reflected in students' increased learning motivation, better understanding of narrative text elements, and improved ability to accurately retell stories.

As the foundation and official ideology of the Indonesian state, Pancasila plays a crucial role in guiding the management of national affairs and the overall conduct of state life. The core principles of Pancasila divinity, humanism, unity, democracy, and social justice reflect the character, identity, and collective values of the diverse Indonesian people. The purpose of this study is to examine in depth the function of Pancasila as a state ideology and the significance of implementing its principles in contemporary and evolving society. Through the exploration and analysis of various scholarly sources, including books, academic journals, and official state documents, this research employs a qualitative approach using a literature review method. The findings indicate that Pancasila functions not only as the nation’s way of life but also as the philosophical foundation of the state and a unifying ideology within Indonesia’s heterogeneous society. Furthermore, the preservation of national identity, the strengthening of social cohesion and peace, and the ability to face the challenges of industrialization and globalization are highly dependent on the successful internalization of Pancasila’s values. Therefore, to achieve sustainable and inclusive national development, consistent and continuous efforts are required to enhance understanding, appreciation, and implementation of Pancasila’s values across all levels of society.

Adolescence is a period of change or transition from childhood to adulthood, encompassing biological, psychological, and social changes. Adolescent girls experience menstruation every month, which puts them at risk of anemia, compounded by poor dietary habits and the failure to consume iron tablets. Rapid adolescent growth is linked to nutritional fulfillment or adolescent consumption of nutrients, one of which is iron consumption. Insufficient iron consumption can lead to anemia in adolescents. Strategies to address anemia in adolescent girls include improving dietary intake and providing iron tablet supplementation. Changing dietary patterns is an important long-term strategy, but cannot be expected to be successful quickly. Anemia is a global health problem, especially in developing countries, where an estimated 30% of the world's population suffers from anemia. Adolescent girls are ten times more likely to suffer from anemia than boys. Efforts to prevent anemia in adolescents through iron tablet supplementation are a strategic, specific intervention to prepare healthy mothers-to-be. The aim was to determine the effect of iron (Fe) tablet administration on increasing Hb levels in adolescent girls with mild anemia. This study was quantitative, with an experimental design. The population in this study were 55 young women at the Ibu Health Center in West Halmahera Regency. A purposive sample of 30 samples was taken. Data collection in this study was carried out by examining Hb levels before and after administering iron tablets 4 times in a row for 4 weeks. The results of the study were that there was no significant difference between Hb levels before and after administering iron tablets in young women at the Ibu Health Center in West Halmahera Regency. The average Hb level before administering iron tablets was 11.5 g/dL, and after administering iron tablets was 12 g/dL. The results of the paired t-test showed a difference before and after administering iron tablets (p value = 0.001), so the test has an effect on administering iron tablets (Fe) on increasing Hb levels in young women with mild anemia in the Ibu Health Center in West Halmahera Regency.

Hypertension is a global health issue and major risk factor for cardiovascular disease, requiring lifelong medication. In addition to pharmacological treatment, healthy lifestyle changes and non pharmacological therapies such as warm water foot soaks, can help prevent complications by inducing vasodilation to lower blood pressure. This study aims to describe nursing care for hypertensive patients, focusing on the application of warm water foot soaks to reduce blood pressure in an inpatient setting. Methods a descriptive case study approach was used three hypertensive respondents. The intervention involved 15 minute warm water foot soaks at a temperature of 39-40°C, conducted once daily for three days. Data were collected using digital sphygmomanometers and observation sheets, with measurements taken before and after the intervention. Results, after the therapy, all respondents showed an average reduction in blood pressure, with systolic pressure decreasing by 6,6 mmHg and diastolic by 2,3 mmHg. Respondents also reported felling more relaxed and experiencing lighter sensations in their legs. Conclusion, warm water foot soak therapy is an effective, safe, and cost efficient non pharmacological intervention for hypertensive nursing care, suitable for implementation by both nurses dan families.

The manufacturing industry in Indonesia has experienced rapid growth along with the increasing demand from society for various industrial products. This condition encourages manufacturing companies to improve productivity, product quality, and production process efficiency in order to compete in the global market. One of the efforts that companies can undertake is the consistent implementation of Standard Operating Procedures (SOP) at every stage of the production process. This activity aims to determine the implementation of SOP in the emboss production process at PT Nikomas Gemilang and to examine its influence on the work efficiency of operators. The method used in this activity is a qualitative descriptive method with a participatory approach. Data collection was carried out through observation, direct work practice, and documentation during the implementation of the internship program (Kuliah Kerja Praktik/KKP). The results of the activity indicate that the implementation of SOP in the emboss production process has been carried out through several stages, namely the preparation stage, machine operation stage, and production result evaluation stage.