This study explores into exploring the execution of Equilibrium Theory-Based Gender Equality (ETBGE) in Boja Village to enhance family welfare, employing a non-doctrinal (empiric) approach through observation and surveys. Gender equality is crucial for holistic development, especially in rural areas, as it promotes socioeconomic progress. Drawing on Equilibrium Theory, which advocates for equal This study delves into how gender equality principles can be effectively applied at the community level to enhance access to resources and opportunities. Through systematic observation and comprehensive surveys in Boja Village, the study evaluates gender dynamics, resource allocation, decision-making processes, and overall family welfare. Analysis of empirical data, including demographic profiles, economic indicators, and social structures, aims to uncover existing disparities and challenges in achieving gender equality objectives. The findings offer insights into the effectiveness of ETBGE principles in Boja Village, identifying successful areas and those needing further intervention. The study concludes by proposing practical recommendations and strategies to empower Boja Village residents, particularly women, enabling them to participate in decision-making, access resources equitably, and enhance the welfare of their families and the community.

This study aims to analyse the financial feasibility of the ground coffee production business undertaken by coffee farmers and processors by applying local innovations at the cultivation, post-harvest handling, and coffee processing stages in the coffee production centre of Garut Regency. This study used a quantitative approach to provide a comprehensive understanding of the feasibility of the ground coffee business with local innovations applied by coffee farmers and processors in Garut Regency. Local innovations in coffee production include pruning techniques, grafting, solar dryer dome technology for herbal coffee making, the use of local roasting machines, and the utilization of coffee waste into value-added products such as ceramics, organic fertilizer, and dodol. Quantitative analysis of coffee processing business feasibility based on NPV value of Rp 38,394,163, Gross B/C 1.08, Net B/C 1.25, IRR 17.73 percent, payback period 7.7. These results showed that the business carried out by ground coffee processors in the production centre area is feasible. These results of the sensitivity analysis show that an increase in the price of coffee fruit raw materials at a limit of 16.67 percent and a decrease in ground coffee production at a limit of 11.37percent still produces a positive value and the business is still feasible. These results of the switching value analysis explain that the tolerance limit for the increase in the price of coffee fruit raw materials can be tolerated if the rise is no more than 26.66 percent and the decrease in ground coffee production does not exceed 7.023percent if it exceeds within 1 year then the business is not feasible.

Sri Lankan Cassava Mosaic Virus (SLCMV) has emerged as a significant threat to cassava production in Southeast Asia since its initial detection in Cambodia in 2015, with recent outbreaks in Vietnam and Thailand and its first detection in Australia in 2024. This viral disease, transmitted by the whitefly Bemisia tabaci and infected planting materials, poses a substantial risk to Indonesia's cassava industry. Studies from affected countries demonstrate yield losses of 16-33% and starch content reductions of 22-38% in infected plants. This review analyzes SLCMV's current status and potential impacts on Indonesian cassava production and proposes management strategies based on regional experiences. We identify critical risk factors, including widespread vector presence and informal planting material exchange networks. Recommended preventive measures include strengthening quarantine systems, implementing enhanced surveillance programs, developing rapid diagnostic capabilities, and establishing clean seed certification systems. Our findings emphasize the urgent need for coordinated action to protect Indonesia's cassava industry from this emerging pathogen.

The supervision and enforcement of the advocate code of ethics in Indonesia continue to face various challenges, impacting the effectiveness of the existing regulatory framework. The number of ethical violations committed by advocates has been increasing, from 120 cases in 2018 to 345 cases in 2023, with the most prevalent infractions including conflicts of interest, abuse of authority, and gratification. One of the primary factors contributing to the weak enforcement of the code of ethics is the limited oversight system, which remains confined to advocate organizations without the involvement of independent institutions. This study aims to analyze the effectiveness of the advocate supervision system in Indonesia, compare it with best practices in other countries, and identify measures that can be implemented to enhance accountability and transparency within the profession. The research employs a normative legal method with a comparative law approach and empirical studies. The analysis is conducted on existing regulations, case reports on violations, and interviews with key stakeholders, including advocates, clients, and legal observers. The findings reveal that only 40% of reported violations result in strict sanctions, while merely 10% of advocates found guilty of ethical misconduct face license revocation. Additionally, a survey of 500 respondents indicates that only 35% of the public is aware of the complaint procedures against advocates who breach ethical standards, highlighting the low level of transparency in the supervision system. This study contributes to the discourse by recommending the establishment of an independent institution to oversee advocates' compliance with ethical standards, as well as the increased utilization of digital technology in the supervision system. With more transparent and accountable oversight reforms, it is expected that ethical violations within the legal profession can be minimized, thereby strengthening public trust in Indonesia’s legal system

Purpose: This research compared the accuracy level of six algorithms based on the ROC method and the Confusion Matrix evaluation on data regarding public sentiments towards electric cars.
Methods: Data collection was conducted for data sourced from TikTok. Next, the data underwent text preprocessing (data cleaning and case folding) and text processing (stemming, tokenizing, stopword removal, word frequency, word relation, TF-IDF, scoring, and labeling). Modeling was then conducted using supervised (labeled) algorithms consisting of the Support Vector Machine (SVM), Decision Tree, Naive Bayes, Random Forest, K-Neighbor, and Logistic Regression. Finally, an evaluation was conducted (confusion matrix and ROC).
Result: The results revealed that the Decision Tree algorithm with the Confusion Matrix and ROC evaluation obtained the highest result of 87%. The algorithm with the lowest result is KNN, which has an accuracy of 56%. The classification result for the neutral sentiment has a percentage of 57.1%, followed by negative sentiment at 26.8% and positive sentiment at 16.1%. The KNN algorithm is suitable for large and low-dimensional data, SVM is suitable for data with many features and clear separation between classes, and Naive Bayes is efficient for large datasets with many low-quality features. Additionally, the Random Forest algorithm could overcome overfitting and unbalanced data. Logistic regression is also suitable for linear data without assuming a certain distribution. The Decision Tree algorithm is good for complex data as it provides a visual explanation of predictions. In this study, the Decision Tree algorithm obtained high results because it has the best characteristics and is a linear technique.
Novelty: This study found that based on the ROC method and the Confusion Matrix evaluation conducted, the Decision Tree algorithm is more accurate than the other algorithms studied.

The role of the financial sector in the economy is very large and continues to grow to meet people's needs. Financial technology or (fintech) is a term used to describe innovation that occurs in the financial sector. The use of financial technology in micro, small and medium enterprises (MSMEs) in Tembalang District aims to measure how the application of financial technology has an impact on the growth and competitiveness of MSMEs in the area. This research involves a survey of a number of small and medium enterprises (MSMEs) that have adopted various fintech services, such as technology-based financial management and digital payments. This research was conducted to identify changes in operational efficiency, access to capital, and competitiveness of MSMEs in Tembalang District. The results of this research are expected to provide an in-depth picture of the extent to which the use of fintech has supported the growth and demand of MSMEs in Tembalang District as well as provide policy recommendations to increase the role of fintech in supporting the MSME sector.

This research was conducted at PKBM Berdikari Surakarta and focuses on the self-confidence levels of package A students, as self-confidence is very important for the learning process of students, especially at the elementary school level. The self-confidence of students is crucial for their personal and academic progress, influencing their ability to interact with others and develop their own potential. These findings highlight the need for environmental support to enhance students' self-confidence in both academic and social contexts.

The Al-Qur'an Tahfidz program at SDIT Al-Iman aims to equip students with Al-Qur'an reading and memorization skills. This study employs the Countenance Stake evaluation model to assess program effectiveness. Results indicate the program successfully achieved its objectives through structured planning, systematic monitoring, and tailored improvement measures. The program positively impacts students' confidence and Al-Qur'an reading abilities. Recommendations for enhancement include increased parental involvement, digital monitoring systems, technology-based learning methods, and teacher training.

The research aimed to optimize the Problem-Based Creative Learning (PBCL) model to enhance higher-order thinking skills (HOTS) in natural science learning. The research used the Delphi method, which involved seven experts in education from various disciplines contributing to a cycle of Delphi. The Delphi cycle consisted of two cycles, and data analysis involved using the Aiken V statistical equation. The Delphi study results highlighted agreement on the characteristics of the PBCL model, which included (1) syntax, (2) social system, (3) principles of reaction, (4) support system, and (5) the impact of learning. The research findings highlight the potential of PBCL as an innovative learning model in natural science learning, emphasizing its effectiveness in improving aspects of analysis, evaluation, and creation as part of HOTS. The study contributes a learning model framework for educators to strengthen natural science education and cultivate insightful and adaptive students in the 21st century.

POAC (Planning, Organizing, Actuating, Controlling) is a management framework used to improve effectiveness in various sectors, including education. In modern education management, the implementation of POAC plays a crucial role in achieving the goals of efficient and quality education. Planning helps set the long-term vision and strategy of the educational institution. Organizing ensures that human and material resources are managed effectively. Actuating involves leadership and motivation to ensure that all parties are active in the educational process. Control is carried out through periodic evaluation and monitoring to ensure the achievement of goals. Research shows that the proper implementation of POAC can improve learning quality, operational efficiency, and student satisfaction. The application of POAC in modern education management is an important strategy in creating educational institutions