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Welfare for the poor is the most important topic in improving citizens. Islam as Ad-diin has offered several teachings for humans that apply universally with two dimensional characteristics, namely happiness and well-being in life in this world and in the hereafter. In the concept of the modern world, welfare is a condition where a person can fulfill basic needs, be it the need for food, clothing, shelter, clean drinking water as well as the opportunity to continue education and have adequate work that can support the quality of life so as to have a social status that leads to the same social status as other citizens. ZIS as an extension of the government in helping the needs of the poor with the aim of improving the welfare of the community who initially as zakat recipients turned into zakat givers, so that later the funds used will be evenly distributed and felt by the wider community. as well as purifying assets that may be accidentally mixed with assets that are forbidden for consumption. The urgency of ZIS in Sidowungu is one of the main elements of effective and efficient zakat management in order to realize the welfare of the community. As for the discussion of this article about the welfare pattern for the poor as the process of distributing ZIS funds in Sidowungu Village. The method used in this article is a quantitative approach. The subjects of this study were 165 poor people in Sidowungu Village, while the sample size was 65 poor people using probability sampling. The results of the study, processed using the PASW SPSS 23 for Windows program, showed that partial test results for H0 were rejected and H1 was accepted if the calculated t value was greater than the table t value or the sig value was less than 0.05. This means that the distribution of funds partially affected the welfare of the poor in Sidowungu Village. The magnitude of the influence between variables can be seen from the coefficient of determination of 0.079, meaning that 79.0% of the welfare of the poor in Sidowungu Village was influenced by the distribution of ZIS funds, while the remaining 21.0% was influenced by other variables not included in this study.

Depression is one of the mental health problems that often arise in patients with chronic diseases, such as diabetes mellitus, hypertension, and chronic kidney failure. This condition not only impacts the patient's quality of life, but also affects the treatment process and the burden on the family. However, mental health literacy in the community is still low, so targeted preventive and curative efforts are needed. The Community Service Program (PKM) aims to improve people's mental health through educational interventions with scientific booklet media that are easy to understand and apply. The activity method is carried out in a participatory manner, including the preparation stage, socialization, educational implementation, and evaluation. Education is provided to the community with a focus on preventing depression through a healthy lifestyle, stress management skills, and early intervention efforts by seeking professional support. Evaluation is carried out through pre-post tests, observations, and group discussions. The results of the activity showed an increase in public knowledge about depression, a change in attitudes to be more open in expressing feelings, as well as practical skills in relaxation, maintaining sleep patterns, and building social support. Participants also better understand the importance of seeking professional help when depressive symptoms are getting worse. The conclusion of this PKM is that the scientific booklet has proven to be effective as a preventive and curative educational intervention medium, and can be an innovative strategy in improving the mental health of people affected by chronic diseases.

This study aims to analyze the effect of the implementation of the Intelligent Tutoring Sistem (ITS) based on Artificial Intelligence (AI) on improving the understanding of mathematical concepts, especially in fractional and basic geometry materials, in Class V students of SD Negeri 2 Badran, Temanggung Regency. The research method used was a quasiexperimental experiment with a Non-equivalent Control Group Design. The research sample consisted of 48 students who were divided into two groups, namely the experimental group (n=24) who received learning with the help of AI-based ITS, and the control group (n=24) who received conventional learning with lecture methods and practice questions. The research instrument is in the form of a test of understanding of mathematical concepts that has been validated by experts and tested for reliability. Data were analyzed using parametric statistical tests of the Independent Sample t-test and N-Gain Score to measure the improvement. The results showed that there was a significant difference in understanding of mathematical concepts between the experimental group and the control group. The average post-test score of the experimental group (82.45) was significantly higher than that of the control group (70.12) with a p< value of 0.05. N-Gain analysis showed that the improvement in conceptual understanding in the experimental group was in the "moderate" category (g=0.56), while the control group was in the "low" category (g=0.32). These findings indicate that AI-based ITS is effective in improving students' understanding of mathematical concepts. The advantages of the system lie in its ability to provide instant feedback, personalize materials according to learning pace, and present interactive materials, thus helping to better construct students' conceptual understanding. It is recommended that schools consider the integration of ITS technology as a supplementary tool in mathematics learning at the elementary level.

The development of Artificial Intelligence (AI) technology has provided new opportunities to enhance the quality of learning, particularly in elementary science education. One form of AI utilization is chatbots, which function as interactive learning media capable of encouraging students’ active participation. In science learning, questioning behavior is an important indicator of students’ cognitive engagement; however, many elementary school students tend to be passive in asking questions. This study aimed to examine the effect of using AI chatbots in science learning on students’ questioning behavior in Grade V of SDN Plalangan 03 Gunungpati, Semarang City. This study employed a quantitative approach with a quasi-experimental design. Data were collected through observation, questionnaires, and documentation. The data were analyzed to identify changes in students’ questioning behavior before and after the implementation of AI chatbots in science learning. The results indicated that the use of AI chatbots improved students’ questioning behavior in terms of frequency, confidence, and activeness in asking questions. AI chatbots provided a comfortable and flexible interaction space for students, which helped reduce psychological barriers in questioning. It can be concluded that the use of AI chatbots has a positive effect on students’ questioning behavior in elementary school science learning.

This study explores the integration of financial numeracy with local wisdom in mathematics education in Indonesia. By incorporating real-life financial scenarios, such as budgeting, saving, and investment calculations, into mathematics lessons, the research aims to enhance students' understanding of mathematical concepts while simultaneously improving their financial literacy. The study also emphasizes the importance of using local cultural and economic knowledge as a context for learning, making abstract mathematical concepts more relevant and accessible. The findings suggest that contextualizing mathematics education through local wisdom significantly improves student engagement, understanding, and practical application of mathematical knowledge. The integration of financial numeracy helps students make informed financial decisions and prepares them for future financial challenges. This research contributes to the development of a mathematics curriculum that combines financial literacy with local context, offering a more inclusive, relevant, and practical approach to education. The study’s findings contribute to the ongoing development of more inclusive, relevant, and practical educational frameworks that incorporate financial literacy into the mathematics curriculum.

This article delves into the application of gamification in Islamic Religious Education (IRE) for primary school students, focusing on its impact on motivation, emotional engagement, and learning psychology. It offers a systematic review of relevant studies, evaluating both the positive outcomes and challenges of using gamification in IRE. A thorough library research approach was used, drawing from academic journals, books, and conference papers. Key databases like Google Scholar, JSTOR, and ERIC were searched to identify studies published between 2010 and 2025. Studies that met specific criteria relevance to the topic, educational level, and a focus on gamification, motivation, emotional engagement, and learning psychology were selected. The findings suggest that gamification in IRE can significantly enhance student motivation, emotional engagement, and learning outcomes. Elements such as rewards, challenges, and interactive activities help create a positive learning environment, promoting better retention and understanding of Islamic teachings. Emotional engagement is particularly heightened when gamification is tailored to the cultural and religious contexts of the students, fostering a deeper connection to the material. The study emphasizes that incorporating gamification in IRE could enhance the overall educational experience for primary students, boosting their motivation and emotional involvement in learning. It also highlights the importance of designing gamified content that is culturally relevant and contextually appropriate to maximize the positive effects on student learning. The study recommends that educators, curriculum developers, and policymakers consider using gamification to improve the quality of Islamic education in primary schools.

Dysmenorrhea, which is common in adolescent girls, is a painful menstrual cycle that frequently interferes with daily activities, both in the classroom and in social situations. Dysmenorrhea is a common condition that needs particular care as a reproductive health concern, notably among young people. Both pharmacological and non-pharmacological approaches can be used to treat dysmenorrhea. The use of warm water compresses is a simple, inexpensive, and effective non-pharmacological approach. By increasing blood vessel dilatation, enhancing blood circulation, lowering muscular tension, and lowering pain perceptions, warm water compresses aid in alleviating dysmenorrhea symptoms. The objective of this study is to assess the impact of warm compresses on the severity of dysmenorrhea pain scales in teenage girls at the Buntalo Community Health Center. The design of this trial was pre-experimental, using a one-group pretest-posttest technique. Using a purposive sampling method, a sample of 20 respondents was chosen. The Wilcoxon test was used to conduct the data analysis. According to the data, there was a statistically significant reduction in pain intensity, with a Z value of -4.065 and a p-value of 0.000 (p < 0.05). The average pain scale decreased from 2.95 to 1.80. Based on these findings, it is reasonable to conclude that warm water compresses are helpful in alleviating dysmenorrhea pain in young women. One of the suggestions for non-pharmacological treatments to help alleviate dysmenorrhea symptoms in adolescents is anticipated to be the outcome of this research.

This study aims to examine the influence of tax awareness, tax knowledge, and tax morale on the level of individual taxpayer compliance. Income tax plays a strategic role as the primary source of financing for government expenditures in supporting national development. However, the level of taxpayer compliance in submitting Annual Tax Returns (SPT) continues to show a downward trend over time. This condition indicates a problem with compliance behavior influenced by various internal factors within taxpayers. Therefore, government efforts are needed to increase tax awareness, expand tax knowledge, and strengthen tax morale among the public. This study uses a quantitative descriptive approach with a random sampling technique. The research sample consisted of 30 individual taxpayers registered at the Kediri Pratama Tax Service Office (KPP Pratama). Data were analyzed using descriptive statistics, classical assumption tests, and hypothesis testing with the help of SPSS software. The results show that tax awareness, tax knowledge, and tax morale have a positive and significant effect on taxpayer compliance, both partially and simultaneously.

This study aims to design and develop an electrical installation panel by applying engineering safety principles in the water spray booth of a vehicle body painting system. Field observations indicate that electrical panels in painting rooms often do not meet safety standards, which can lead to short circuits and potential fire hazards. The research employed a Research and Development (R&D) method using a simplified Borg and Gall model consisting of nine stages, starting from problem identification to effectiveness testing. Expert validation results obtained a score of 87.5% (highly valid), practicality testing yielded 90% (very practical), and effectiveness tests showed an average current of 4.1 A, with both the MCB and emergency stop functioning optimally. The developed panel product is declared feasible to be used as a practical learning media for automotive electrical systems. Based on the test results, the panel product was declared suitable for use and can be used as a learning medium in automotive electrical practice, helping to increase understanding of the application of safety in electrical installations in the automotive industry.  

Mining operations rely heavily on the performance and reliability of heavy equipment used in the production process. One of the most important hauling units in open-pit mining is the dump truck, which functions to transport overburden and coal from the mining front to disposal areas. Due to high operational intensity, dump trucks require effective maintenance management to ensure equipment reliability and reduce unexpected downtime. However, maintenance activities are often carried out based only on routine service schedules without analytical planning based on historical data. This study aims to analyze the implementation of forecasting methods in maintenance management to improve the effectiveness of dump truck maintenance planning in mining operations. The research was conducted during field work practice at PT Putra Perkasa Abadi Jobsite BIB, Tanah Bumbu, South Kalimantan. The data used were historical maintenance records of dump truck units obtained from the maintenance department. The research method used a quantitative approach with time series forecasting analysis to identify maintenance patterns and estimate future maintenance needs. The results show that forecasting-based maintenance planning can help companies predict maintenance requirements more accurately and prepare maintenance resources more efficiently. Furthermore, the implementation of forecasting methods can reduce unexpected equipment failures and support operational efficiency in mining activities.

Employment agreements are essential legal instruments that regulate the rights and obligations of workers and employers in industrial relations, aiming to ensure legal certainty and balance. In practice, however, the implementation of employment contracts often faces challenges such as differing interpretations, unequal bargaining positions, and inconsistent application of labor regulations. These issues require an effective and constructive dispute resolution mechanism that can address contractual problems while preserving employment relationships. In the Indonesian labor law system, mediation is recognized as a key non-litigation mechanism facilitated by government-appointed mediators to help parties reach mutually acceptable solutions. This study examines the mediation mechanism for resolving employment agreement disputes in Indonesia and analyzes its role as an alternative to court proceedings that emphasizes deliberation, efficiency, and cooperation. Using a normative legal research method with statutory and conceptual approaches, the study analyzes relevant labor laws, mediation regulations, and legal doctrines through a comprehensive literature review. The findings show that mediation is conducted through structured stages, including dispute registration with labor authorities, mediator appointment, facilitated negotiations, and the formulation of agreements or written recommendations. Mediation effectively promotes consensual solutions, reduces procedural complexity, and encourages cooperative communication. It also supports the preservation of harmonious and sustainable employment relationships by prioritizing consensus over adversarial processes. Strengthening mediator competence and improving legal awareness among workers and employers are therefore crucial to optimizing the effectiveness of mediation in resolving employment agreement disputes in Indonesia.

This study examines the effectiveness of national legislative strategies in promoting corporate accountability for industrial pollution and social justice violations. It analyzes a comparative legal framework, focusing on laws, enforcement mechanisms, and corporate liability regimes in countries such as France, Germany, Norway, China, and Australia. The research evaluates how mandatory due diligence laws, judicial measures, and transparency mechanisms help hold corporations accountable for environmental impacts. It compares voluntary compliance models with mandatory legal frameworks, noting the limitations of voluntary agreements in driving substantial environmental changes. Findings show that countries with strong legal frameworks, like the EU and Australia, achieve higher corporate compliance and environmental performance, while voluntary measures struggle to produce meaningful results. The study emphasizes the need for stronger enforcement, higher penalties for violations, and enhanced public transparency. Additionally, it explores integrating environmental justice considerations, such as community participation and fair compensation, into national strategies. The study offers policy recommendations for improving corporate responsibility through better legislation, harmonizing laws across jurisdictions, and fostering collaboration among governments, corporations, and civil society. It also suggests future research directions, including examining the long-term impacts of environmental justice policies in different global contexts.

Children with emotional and behavioral difficulties are children who have trouble adjusting to their social environment. This can affect their academic and functional abilities in daily life. Children with emotional dysregulation and aggressive behavior are particularly vulnerable to experiencing a series of social problems due to their emotional and behavioral difficulties. Therefore, emotional and behavioral intervention is needed to help them develop new adaptive behaviors and reduce maladaptive behaviors. One intervention method that is often used to reduce children's abberant behavior is CBT, especially the CBT-AAC model, which focuses on three dimensions, namely anger management skills, problem-solving skills, and social skills. This study used the SSR (Single Subject Research) research model on a 15-year-old boy with behavioral problems (Conduct Disorder) with symptoms of aggressive dominance. The CBT program was implemented with a total of 5 meetings using various approaches that focused on the child's aggressive problems. The behavior frequency graph then showed a significant decrease in aggressive behavior and positive changes in the cognitive process.

Contemporary church ministry is often trapped in a seasonal pattern, with increased activity only during major events like Christmas and Easter, while stagnating at other times. This phenomenon indicates a fundamental problem in leadership patterns that are not poverty-oriented. This article analyzes the roots of seasonal church ministry through a qualitative-descriptive approach and theological reflection based on Osmer's framework. Literature reviews by Barna, Maxwell, Banks & Ledbetter, as well as the leadership principles of Jesus Christ, show that seasonality is eliminated by reactive leadership that lacks a long-term vision, minimal spiritual training, and a weak ministerial cadre system. As a solution, this article offers a sustainable leadership model that emphasizes a year-round discipleship vision, ministerial training and regeneration, systematic ministry evaluation, and the spiritual example of leaders. This model is believed to help churches experience stable growth, establish a consistent ministry rhythm, and present relevant evidence to the world. Thus, sustainable leadership is a strategic and theological approach to addressing seasonal ministry and strengthening the mission of the church today.

Suicide among adolescents is a serious mental health problem; however, not all adolescents with suicidal ideation progress to suicide attempts. Understanding the psychological factors that influence the transition from intention to actual behavior is essential for effective prevention efforts. This study aims to examine the role of the Theory of Planned Behavior (TPB) in understanding the transition from suicidal intention to suicide attempt behavior, as well as protective behaviors such as mental health help-seeking among adolescents. This study employs a literature review method with a quantitative correlational approach based on the TPB framework, using secondary data from scientific articles published between 2021 and 2025 and obtained through Google Scholar and PubMed. The findings indicate that suicidal ideation is the strongest predictor of suicidal intention but does not always lead to suicide attempts. TPB constructs, particularly perceived behavioral control (PBC), play a crucial role in determining whether intention develops into risky behavior or is redirected toward protective behaviors. In addition, positive attitudes toward mental health services and supportive social norms were found to strengthen adolescents’ intentions to seek help. In conclusion, TPB is a relevant theoretical framework for explaining both risk pathways and prevention pathways of adolescent suicide and has the potential to serve as a foundation for developing more effective prevention interventions.

This study aims to evaluate the implementation and impact of an English training workshop for early childhood education teachers in Surakarta. The study employed a program evaluation design using a qualitative descriptive approach involving twenty playgroup and kindergarten teachers. The workshop was conducted over four days and was designed based on a needs analysis obtained through a pre-test and preliminary interviews. Data were collected through pre-test and post-test results, reflective questionnaires, and semi-structured interviews. The qualitative data were analyzed using thematic analysis. The findings indicate that the workshop had a positive impact on participants’ English proficiency as well as their affective aspects, particularly their confidence in using English in the classroom. The thematic analysis identified three main themes: emotional responses, understanding of the material, and collaboration. Participants demonstrated increased enthusiasm, reduced anxiety, and improved self-confidence. Contextual and practical materials helped participants connect theoretical concepts with classroom practice. Furthermore, interactive activities and collaborative discussions strengthened professional engagement and peer learning. These findings confirm that structured and needs-based training is effective in supporting the sustainable professional development of early childhood education teachers and contributes to improving the quality of English instruction in the classroom.

Diabetes Mellitus is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action or both. Hyperglycemia is a medical condition in the form of an increase in glucose levels beyond normal limits which is a characteristic of several diseases, especially Diabetes Mellitus, in addition to various other conditions. Diabetes Mellitus is currently a global health threat. Classification is one of the techniques of data mining that can be used to help predict the results of the classification of types of diabetes using the naïve Bayes algorithm. Testing was carried out using 5 evaluation models including rapid miner with 3 options, namely use training set, 5 Fold Cross-Validation, 10 Fold Cross-Validation, and 2 other evaluation models, namely Microsoft Excel and Python. Testing data regarding Diabetes Mellitus has high accuracy in the excel evaluation model, which is 89.00% compared to other evaluation models. Meanwhile, the lowest accuracy is the Python evaluation model which obtains an accuracy of 86.36%. The Naïve Bayes algorithm can be said to be one of the most effective algorithms, both in terms of calculations and the final results, where the test can be used as a basis for diabetes mellitus considering the accuracy results are above 85%.

Micro, Small, and Medium Enterprises (MSMEs) play a crucial role in both the national and local economies, including in Banjar Regency. However, MSMEs often face significant challenges in managing human resources (HR), which can directly affect employee motivation levels. This community service activity aims to provide education and support to MSME actors in Banjar Regency regarding effective HR practices, with a focus on improving work motivation. The methods used include socialization, training, and guidance in implementing a simple yet effective motivation system. The results of the activity showed an increase in participants' understanding and application of better HR strategies. It is hoped that this will have a positive impact on the productivity and sustainability of MSMEs in Banjar Regency, as well as contribute more to the local economy. The guidance provided also helps MSME actors better understand the importance of motivation in creating a productive work environment, which in turn can increase the competitiveness of their businesses in an increasingly competitive market.

The purpose of this study is to investigate the factors that lead to poverty in different Indonesian regions between 2018 up to 2024. The Gross Regional Domestic Product per capita, the Human Development Index, and the Open Unemployment Rate are the independent factors used in this study, whereas poverty levels are the dependent variable. The Central Statistics Agency provided secondary data that was used in a quantitative manner. Using EViews 12 software, panel regression techniques were used to process the data. The study's conclusions show that, at a significance level of less than 0.05, economic and human development factors simultaneously significantly affect poverty rates across Indonesian regions. The coefficient of determination indicates that the variables in the model can account for the majority of the variations in poverty levels. These findings demonstrate how important a region's economic status and level of human development are to efforts to reduce poverty. It is anticipated that this research will help the government develop more effective and long-lasting methods for reducing poverty.

The use of protective equipment in the form of helmets is an important aspect of ensuring motorcycle rider safety. However, violations of helmet usage still frequently occur and are difficult to monitor continuously. This study proposes a real-time helmet detection system using the YOLOv8 object detection method. The YOLOv8n model was trained using a helmet and no-helmet image dataset that underwent data augmentation to improve the model’s robustness against variations in environmental conditions. The system was implemented using the Python programming language with the support of the Ultralytics and OpenCV libraries. The system input was obtained from a webcam with a resolution of 640×640 pixels, where each video frame was processed in real time to detect the Helmet and No Helmet classes. The system displays bounding boxes and class labels in real time and is equipped with a violation duration calculation mechanism. When a no-helmet condition is detected continuously, the system generates pop-up alerts and automatic notifications via the Telegram application. The experimental results show that the system is capable of detecting helmet usage and no-helmet violations in real time with stable performance. The integration of violation duration calculation helps reduce momentary detection errors and improves the reliability of identifying valid violations