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This study aims to empower farmer groups in applying appropriate technology to rice farming productivity in Sukajadi Village, Sadananya District, Ciamis Regency. The research methods used include field surveys and analysis of productivity data from farmers who apply this technology compared to those who do not. Primary data was collected through structured interviews with farmers and direct observation in the field during the research period. Data analysis was carried out by comparing rice production results, efficiency of using agricultural inputs, and farmer income before and after adopting appropriate technology. The research results show that the adoption of appropriate technology significantly increases rice productivity in terms of the number of harvests per hectare and reduces the costs of certain inputs such as fertilizers and pesticides. In addition, farmers who apply this technology also report better income increases compared to conventional methods. These findings support the importance of implementing appropriate technology in improving food security and the economy of farmers in rural areas such as Sukajadi Village. This research contributes to expanding understanding of the practical benefits of appropriate technology in the context of rice farming in Indonesia.

Fractal structures play a crucial role in improving material properties due to their unique self-similar geometries. These geometrical patterns exhibit repetition at multiple scales, which can enhance surface area, strength, and other mechanical characteristics. This study investigates the influence of fractal patterns on the crystal growth and mechanical performance of metallic materials, focusing on strength, toughness, and hardness. Using a combination of computer simulations and laboratory experiments, the research models metal crystal formation under controlled conditions, where fractal characteristics are introduced through diffusion-limited aggregation (DLA) and electrodeposition methods. The findings reveal that embedding fractal patterns into the crystal growth process can increase material strength by approximately 20% compared to conventionally structured metals. This improvement is attributed to the efficient stress distribution within the fractal geometry, which minimizes stress concentration points and enhances resistance to fracture. Additionally, materials with fractal-based microstructures exhibit better toughness and deformation resistance, improving durability under mechanical load. The study also examines the underlying mechanisms of these effects, emphasizing the role of fractal-induced microstructural control in optimizing material integrity. These results demonstrate the significant potential of fractal-based material design in engineering stronger, lighter, and more flexible metallic components. The research contributes to the broader understanding of how geometric complexity can be harnessed to develop advanced materials for applications in construction, automotive manufacturing, and flexible electronics, thereby supporting the development of next-generation high-performance materials.

The rapid urbanization and industrialization of cities have significantly contributed to the rising pollution levels, especially in urban rivers, where water quality is often compromised. Monitoring water quality in real-time is essential for mitigating the adverse effects of water contamination. This research aims to design and implement an Internet of Things (IoT)-based system for real-time monitoring of water quality in urban rivers, focusing on the continuous collection and analysis of environmental data. The system utilizes a range of sensors to measure critical water quality parameters, including pH, temperature, dissolved oxygen (DO), turbidity, and various contaminants, all of which transmit data wirelessly to a central server for further processing. The study evaluates the accuracy, reliability, and efficiency of the IoT system in detecting water pollution and its ability to deliver real-time insights. Findings demonstrate that the IoT system offers a higher level of precision and faster detection compared to conventional monitoring methods, making it an effective tool for real-time pollution detection and decision-making. Additionally, the integration of the IoT system with a user-friendly visualization platform enhances the accessibility of the data for stakeholders, enabling them to monitor the water quality effectively. The study suggests that IoT-based water quality monitoring systems present a sustainable long-term solution for urban water management, offering cost and time savings. Moreover, the research highlights the importance of cross-sector collaboration to support the development and deployment of IoT technologies and recommends further advancements in sensor technologies to monitor additional water quality parameters.  

This study aims to determine and describe the influence of student dance learning outcomes taught using the Cooperative Script learning model with the learning outcomes of students taught using the Conventional model in cultural arts learning at SMPN 2 Padang. This type of research is quantitative research with a quasi-experimental approach. The population in this study was all students in grade IX SMP N 2 Padang, totaling 242 students with samples using purposive random sampling. The research instrument uses pre-test and post test. Data were collected through observation, documentation and cognitive tests. Data were analyzed using normality test, homogeneity test, hypothesis test and independent test. The results showed that there was a significant difference between student learning outcomes before and after applying the Cooperative Script model. The increase in learning outcomes in the group using the Cooperative Script model was the average learning outcome from pretest (69.47) to posttest (87.80). In the group using the conventional model, the average increase in learning outcomes from pretest (69.33) to posttest (77.23). It can be seen that the experimental class using the Cooperative Script Model has a better performance compared to the control class for SMPN 2 Padang students, this can be seen from the average value on the experimental posttest is greater than the average posttest control which means there is a significant influence in using the Cooperative Script Model.

BRI Bank BRI Agent has become an integral part of the Indonesian government's efforts to increase financial inclusion across the country. This research investigates the risks, role and impact of BRILink agents in expanding access to financial services for the community, especially in remote areas and difficult to reach by conventional financial institutions. Through a qualitative approach involving in-depth interviews and secondary data analysis, this study describes various important aspects related to BRILink agents, including the distribution network, services provided, challenges faced, and their impact on financial inclusion. The findings show that BRILink agents have succeeded in expanding the reach of banking services, facilitating financial transactions, and increasing financial literacy among previously underserved communities. However, challenges such as limited technological infrastructure, high operational costs, and lack of awareness of the benefits of financial services are still obstacles that need to be overcome. Based on the results of this research, it is recommended that the government, regulators and other related parties continue to support and improve the BRILink agent ecosystem through supportive policies, structured training and continuous technological innovation. Thus, BRI Bank BRI agents have significant potential in realizing wider and more sustainable financial inclusion in Indonesia.

Learning using text or conventional media makes it difficult for students to understand the material presented by the teaching staff. So now students use the YouTube application as a support in their learning activities. This research aims to find out more about the benefits of YouTube media for students and the use of YouTube social media as a place to share learning material. This research uses a descriptive method with a qualitative approach and this research uses data collection techniques including library research. The data used in this research is secondary data. The results of the research show that students who use YouTube as a mass communication medium make it very easy to find the information or knowledge they need and it is easier for students to understand the material contained in videos compared to material delivered directly by teachers or lecturers either online or face to face because of videos. on the YouTube application can be played back at any time to re-study the teaching material presented.

The National Police Research and Development Center (Puslitbang Polri) is a police institution that operates in the field of research, especially those related to the performance of police and community organizations. Supporting elements in the fields of research, study, implementation and development at the National Police Headquarters level which is under the National Police Chief. In the development process, competent and always motivated Human Resources (HR) are needed, one solution is to create a computerized system to increase employee motivation, namely the best employee assessment decision support system. The process of evaluating the best employees at the National Police Research and Development Center is still carried out conventionally so it is less objective and effective. To overcome this problem, a good system is needed. The aim of this research is to make an assessment of the best employees at the National Police Research and Development Center, because there is no system that can help the Head of the National Police Research and Development Center and the Head of the Human Resources Subdivision to determine the best employee assessment. This research aims to find out the best employees using data from 8 employees at the National Police Research and Development Center. The method used is Simple Addtive Weighting (SAW) with 4 attributes. The results of the research were that 1 was selected as the best employee and received a salary bonus.

The problem at Maharani Private High School is that teachers or educators still use conventional methods so that students become passive in class and students' low understanding of the subject of geography, lithosphere material, which still contains many concepts, makes students feel bored, lazy, and this affects the results. learning and obtained by students whose grades do not meet the standard criteria for maximum completeness. The minimum standard for completion criteria (KKM) in geography subjects at Maharani Private High School is 75. This classroom action research aims to 1) find out the application of the jigsaw type cooperative learning model, 2) to find out the development of class X students' learning outcomes regarding lithosphere materials and types of rocks after using a jigsaw type learning model. The method used in this research is classroom action research or PTK using a jigsaw type cooperative learning model for class X students with research subjects of 20 students. The location of this research is Maharani Private High School for the 2022/2023 academic year, Weliman District, Malaka Regency, East Nusa Tenggara Province. This classroom action research was carried out in two cycles consisting of four stages including planning, observation, implementation and reflection. This research data was analyzed qualitatively descriptively. The results of this research show that using the jigsaw type cooperative learning model can improve the learning outcomes of class X SMA students on lithosphere material. The research results obtained for the first cycle of student learning outcomes were 6 students who completed with a percentage of 30% and as many as 14 students who did not complete or 70% of the 20 students, meanwhile, in cycle II the students who completed experienced an increase, namely 19 students. or as many as 95% and 1 student who did not complete or only 5% in cycle II. It can be concluded that using the jigsaw type learning model can significantly improve student learning outcomes in geography subjects on lithosphere material at Maharani Private High School for the 2022/2023 academic year.

This research aims to evaluate the legal aspects of both Islamic and conventional laws regarding the remuneration provided to preachers invited by Masjid Raya Aziziyah Secanggang. Preachers play a crucial role in guiding individuals towards goodness and deterring them from evil, as per the teachings of the Quran. The study has two primary objectives: to examine the remuneration system for preachers in the mosque and to analyze the perspectives of Islamic and conventional laws on this system. The research methodology employed is qualitative-descriptive with a field approach, utilizing interviews, observations, and documentation as data sources. The findings indicate that Masjid Raya Aziziyah Secanggang compensates preachers through two methods: direct payment without a formal agreement and through a written agreement. From an Islamic legal standpoint, remuneration for preachers can be considered a permissible (mubah) form of appreciation or gratitude. In terms of conventional law, the remuneration system aligns with the regulations outlined in the 2023 Job Creation Law. This research underscores the importance of maintaining compliance with both Islamic and conventional legal aspects and ensuring collective benefits to uphold a fair and justified remuneration system for preachers at Masjid Raya Aziziyah Secanggang. Mutual respect for rights and responsibilities is crucial to enhancing the quality of this remuneration system.

The development of Islamic economics with the application of sharia principles in economic activities is starting to be practiced in the field of sharia finance. This started with the establishment of sharia banking, then followed by the emergence of the sharia capital market as an investment tool to attract profits and seek capital. The Jakarta Islamic Index (JII) as the antithesis of the conventional capital market has challenges when carrying out investments using sharia principles, this is because securities in the form of shares are greatly influenced by macroeconomic aspects such as interest rates. So sharia share prices are very sensitive to the dynamics of interest rates. This research seeks to see the extent of the influence of interest rates on sharia sham prices at JII. The method used is VECM analysis to see long-term effects. The results of this research found that the interest rate variable did not significantly influence sharia stock prices in the long term, however the results of the VECM analysis found that there was a negative relationship, meaning that there was still an influence, although not significant. So sharia share prices can still be affected by changes in conventional interest rates.

The culinary diversity in Asia affects the interest of tourists to visit, this is a fascinating thing to explore. This study investigate the role of gastronomy tourism in expressing and communicating the identity of a region. This study use descriptive qualitative method, it explains how to understand research subject phenomena, behavior, perceptions, motivations, actions, and so on, holistically, and how to describe the results in the form of words and sentences (Moleong: 2010). Using the theory of gastronomic identity proposed by Harrington (2005), researchers analyze that Authenticity is the representation of traditional culinary traditions that reflect a region's historical and cultural foundations. Diversity includes the variety of ingredients, recipes, and culinary skills in a region, Innovation is the imaginative modification and advancement of conventional cooking techniques to suit modern preferences and fads. And sustainable food practices prioritize social responsibility and environmental friendliness in the case of five countries in Asia : China, Indonesia, India, Turkey, Kazakhstan. Gastronomy tourism can be found as a powerful tool for promoting a region's identity, both to locals and tourists.

In today's modern era, marketing is often referred to as the main influence of a business that produces goods or services. Marketing requires a variety of continuous development and strategy changes in order to maximize the potential for success and achieve sustainability. Regarding marketing strategy, if it is not able to control the existing growth, it will not only result in the downfall of the business but also the loss of customers and a decrease in the amount of revenue. The methodology used in this research is a qualitative descriptive method that aims to conduct a thorough investigation of conventional marketing WOM strategies. In this modern era, Bancreps chose a conventional marketing strategy for its business. Marketing carried out by Bancreps can be done more in-depth by using SWOT analysis theory. However, Bancerps to use digital platforms to reach a wider range of customers than just relying on traditional marketing strategies.

The apple cider vinegar fermentation process requires careful monitoring and control of variables such as pH, alcohol content, and amount of acetic acid.  This research adopts Fuzzy Logic Control by utilizing the MQTT communication protocol, pH, alcohol and water pump sensors, as well as solenoid valves and DC motors as actuators.  This Internet of Things (IoT) based solution provides real-time monitoring information on the fermentation process.  The results showed that the test system succeeded in maintaining a stable pH of around 3.9-4.0 during the initial stages of fermentation, while industrial data showed greater variations.  Alcohol content increased consistently in the test system, in contrast to the spike on day 7 in industry data.  At the formulation stage, the pH dropped to 3.68 in the test system, while the industry maintained 3.70.  At medium and slow mixing stages, the test system showed a significant decrease in pH and a consistent increase in alcohol.  At the harvest stage, the pH was lower in the test system compared to industrial, with slightly higher alcohol content.  Test results show that the implementation of this system can reduce the fermentation process time by up to 2 days faster compared to conventional methods.  This conclusion shows that IoT-based systems are able to provide better control and monitoring than conventional systems, so they have great potential for wider adoption in the apple vinegar fermentation industry to increase production effectiveness.

This research explores the potential of local bio-composites made from bamboo and coconut fiber as sustainable building materials in Indonesia. The construction sector in Indonesia faces significant environmental challenges, particularly the high carbon emissions associated with conventional materials like concrete and steel. The primary objective of this research is to evaluate the environmental and economic benefits of substituting these traditional materials with bio-composites, using Life Cycle Assessment (LCA) and energy optimization simulations. The LCA methodology evaluates the environmental impact of bio-composites across their entire life cycle, comparing them with conventional materials in terms of carbon emissions, energy consumption, and waste. Energy optimization simulations focus on assessing the thermal performance and overall building efficiency when using bio-composites in construction. The main findings suggest that bio-composites exhibit a significantly lower carbon footprint and better thermal insulation properties than concrete and steel, contributing to reduced energy consumption in buildings. Additionally, the use of locally sourced materials like bamboo and coconut fiber offers economic advantages, such as lower transportation costs and support for local economies. The research concludes that bio-composites can serve as viable alternatives to traditional materials, providing both environmental and economic benefits. For successful adoption, the research recommends policy support, technological advancements, and educational initiatives to promote the use of bio-composites in Indonesia’s construction industry.

This study examines the impact of blended learning on student engagement and academic achievement in secondary schools during the recovery phase of the pandemic. A quantitative research approach was employed, utilizing a comparative design to assess the differences between blended learning and conventional learning models. Data were collected through student engagement surveys and academic performance records from secondary school students exposed to both learning models. The results indicated that students in the blended learning model exhibited significantly higher levels of engagement across behavioral, emotional, and cognitive dimensions compared to those in the conventional model. Academic achievement was also notably higher in the blended learning group. Statistical analysis, including t-tests and linear regression, revealed a strong positive correlation between student engagement and academic performance. The study concluded that blended learning significantly enhances student involvement and performance, particularly when supported by adequate technological infrastructure and teacher preparedness. These findings suggest that blended learning should be integrated as a permanent strategy in post-pandemic education to support student success and engagement. The study also emphasizes the importance of continuous teacher training and technological support in maximizing the benefits of blended learning.

The rapid growth of Internet of Things (IoT) and edge computing technologies has introduced new security challenges due to the distributed, heterogeneous, and dynamic nature of these environments. Conventional static security mechanisms, such as rulebased authentication and fixed trust models, are often inadequate for addressing evolving threats and abnormal behaviors in largescale IoT systems. To overcome these limitations, this study proposes a machine learningbased trust evaluation framework for enhancing security in distributed IoT environments. The proposed approach dynamically assesses the trustworthiness of IoT nodes by analyzing behavioral and interactionbased features collected at the edge layer. Machine learning models are trained to classify nodes into trusted and malicious categories and continuously update trust values in response to changing network conditions. Based on the predicted trust levels, adaptive security decisions are enforced to allow or restrict node participation in data sharing and computation processes. A quantitative experimental evaluation is conducted using simulated distributed IoT scenarios that include both normal and malicious behaviors. The performance of the proposed framework is evaluated using standard metrics such as accuracy, precision, recall, F1score, and detection effectiveness, and is compared against conventional static trust and rulebased security mechanisms. The results demonstrate that the proposed machine learningbased trust evaluation approach achieves significantly higher detection accuracy and robustness while maintaining low computational overhead. Overall, the findings confirm that integrating machine learning into trust management provides an effective and scalable solution for securing distributed IoT systems under dynamic and adversarial conditions.

UMKM Terez Collection have experienced a downward sales trend and very drastically after the Covid-19 pandemic. The aim of the research is to determine the Terez Collection's marketing strategy and the obstacles faced in increasing its sales value. This type of qualitative descriptive research uses a purposive sampling method. Data collection methods are observation, interviews and literature study. Data analysis involves data collection, reduction, presentation, drawing conclusions and verification. The market segment being worked on is teenage women aged from teens to adults, lower middle class. Meanwhile positioning has not been carried out and understood well. The research results show that the product in consumer perception has good quality in its class, is varied and meets consumer wants. The pricing strategy is quite good and competitive. The promotional strategy is still conventional so that the distribution channel is still one channel, namely conventional. The location of production and management of UMKM in production centers is an added value. Distribution is carried out through wholesalers and retailers. The obstacle faced is that the owner does not understand digital marketing well, and has not taken advantage of opportunities through product innovation. Suggestions for local governments to facilitate and encourage the return of the Binong Jati knitting center, to help facilitate financing for product innovation and training. Terez Collection is advised to increase knowledge and carry out digital marketing as an effort to expand the market.

This study explores the development of low-carbon concrete by integrating industrial waste materials and CO₂-absorbing minerals to reduce carbon emissions in the construction industry. The research investigates various mix ratios involving fly ash, slag, and CO₂-absorbing minerals, aiming to optimize both performance and sustainability. Experimental methods included compressive strength testing, carbon emission measurement, and durability evaluation. The results indicate that low-carbon concrete formulations achieve up to 45% reduction in carbon emissions compared to conventional concrete, which uses Portland cement. Despite a slight decrease in compressive strength, the optimal mix reached 34 MPa, which is sufficient for structural applications. Durability testing revealed that concrete with CO₂-absorbing minerals showed improved long-term performance compared to other formulations. The findings highlight the potential of using industrial waste materials and carbon capture technologies to create more environmentally sustainable concrete while maintaining necessary structural properties. This study contributes to the growing demand for eco-friendly construction materials and supports the implementation of low-carbon concrete in large-scale industrial applications. Further optimization of mix ratios and long-term performance studies are recommended for broader adoption in the construction industry.

The rapid growth of cross-platform applications has significantly increased the volume and diversity of sensitive user data processed across heterogeneous and distributed environments. Personally identifiable information, device identifiers, behavioral data, and financial information are routinely collected to support personalization, analytics, and service optimization. While these practices enhance application functionality and user experience, they also introduce substantial privacy risks, including unauthorized data access, device fingerprint–based re-identification, cross-user data leakage, and large-scale data breaches. These risks are further amplified by distributed processing architectures and extensive third-party library integrations commonly used in modern cross-platform systems. This study aims to systematically analyze privacy issues in cross-platform applications by examining the types of sensitive data involved, identifying dominant privacy threats, and reviewing state-of-the-art privacy-preserving mitigation strategies. A systematic literature-based methodology was employed, focusing on recent Scopus-indexed journal articles, conference papers, and book chapters. The analysis synthesizes findings using thematic categorization and a conceptual research framework that maps sensitive data sources to privacy threats and corresponding mitigation mechanisms. The results indicate that privacy risks in cross-platform applications originate not only from external attacks but also from internal architectural weaknesses, such as flawed authorization logic and excessive data sharing across system components. Privacy-preserving techniques including differential privacy, federated learning, blockchain-based data governance, secure multi-party computation, and fine-grained access control mechanisms are shown to provide stronger privacy guarantees compared to conventional centralized approaches. However, these techniques also present trade-offs related to system complexity and performance. Overall, the study highlights the importance of adopting a multi-layered, privacy-by-design approach to ensure sustainable, trustworthy, and regulation-compliant cross-platform application development.

Malnutrition is a condition of lack of nutrition for a certain period of time so that the body will break down food reserves under the fat layer and organ layers. MPASI methods are divided into two, namely conventional MPASI, which is fed with a spoon, and the Baby Led Weaning (BLW) method, where the child eats with his own hands. The aim of this community service is that it is hoped that parents can increase their knowledge regarding Baby LED Weaning as an effort to improve the nutritional status of toddlers at the Pattingaloang Community Health Center. This research method uses an experimental design with a one group pretest-posttest approach. The study population was mothers who had toddlers aged at least 6-12 months. Sample collection used purposive sampling technique. results of intervention group research with a sample size of 20 children. The results of the study showed that the difference in the average knowledge score of the pretest and posttest groups was 16.5 with a p value = 0.0001 < α where it was concluded that there was an influence of LED Weaning education as an effort to improve the nutritional status of infants and toddlers at the Pattingaloang Community Health Center.