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The National Strategic Program stipulated in Presidential Regulation (Perpres) Number 109 of 2020 concerning the Acceleration of Implementation of the National Food Estate Strategic Project, which was implemented in Gadabung Village, Pandih District, Pulang Pisau Regency was implemented well, so that the community felt the direct impact in the form of a harvest area of 1,205 Ha in a bumper harvest with New Superior Varieties of Inbred and Hybrid rice. The success of Gadabung Village as part of the development of the national strategic food estate project has had a positive impact on making the area charming in the form of vast expanses of rice fields, so that the village can be developed into a tourist village. Based on this, the aim of this research is that the Regional Government of Pulang Pisau Regency makes public policies that can be directly operational, by developing the potential resources owned by the government of Gadabung Village, Pandih Batu District. This research uses a qualitative approach, the data displayed is generally in the form of actual and accurate sentence descriptions and connects the problems studied with a qualitative approach. Researchers go out into the field to research the object of study and hold direct interactions with the community with the aim of obtaining in-depth information about this matter, conducting in-depth interviews and observations. Research Results Based on documentation data, Central Kalimantan Food Estate Development activities, especially in Gadabung Village, were carried out through programs and activities, namely area planning and development of facilities and infrastructure, human resource development and farmer corporations experiencing increased capacity and business diversification. This is a form of sustainability effort for upstream-downstream agricultural businesses based on areas and agro-ecosystem suitability clusters. Increasing the welfare of the people in Gadabung Village will be better by becoming a tourist destination, because the scenery in the area is very beautiful with the support of available natural resources, traditional arts and culture of local people and immigrants (transmigration), both ethnic Dayak, Banjar, Javanese, Sunda, where people live in harmony, safety and peace. The conclusion from the results of this research is that Gadabung Village is a village where the National Strategic Program has been implemented which has succeeded in meeting its objectives, namely making Gadabung Village one of the rice barns in Central Kalimantan, with rice fields stretching across thousands of hectares, and the community feels the direct impact on improving welfare. infrastructure becomes better, the village's potential can become a support for becoming a tourist destination or tourist village.  

Structural transformation is an important process in the economic development of a country. In Indonesia, the plan to move the National Capital City (IKN) from Jakarta to Nusantara in East Kalimantan is one of the strategic steps in accelerating structural transformationThe methodology used in this study is a qualitative and quantitative approach. The results of the study show that the acceleration of structural transformation through the development of IKN has a significant impact on the formation of a new economic base and increasing Indonesia's competitiveness. The formation of a new economic base in IKN can be seen from the emergence of technology and innovation-based industrial clusters. The impact on national competitiveness can be seen from the increase in productivity and innovation capacityThe analysis of the acceleration of structural transformation through the development of the IKN shows a fundamental change in Indonesia's economic base. The development of IKN as a smart forest city accelerates structural transformation through three main mechanisms. The impact on the formation of a new economic base can be seen from the shift in the economic structure in the IKN area and its surroundings. Structural transformation is also reflected in changes in the composition of the workforce and investment patterns. The impact analysis on Indonesia's competitiveness shows a significant increase in several dimensions

Mathematics anxiety can reduce students' ability to understand and solve mathematical problems, thus affecting their overall attitude towards mathematics. Mathematics anxiety, a psychological factor that can affect students' learning achievement in mathematics learning in high school, makes it the most challenging subject in school. This study aimed to identify the effect of mathematics anxiety on students' learning achievement at the high school level and to analyze strategic factors that can help reduce mathematics anxiety for students. This study used a quantitative method with an ex post facto research type with a correlational design. The population was grade X high school students in South Tangerang, with a sample size of 84. The side technique used cluster random sampling. Data collection used an instrument in the form of a mathematics anxiety and learning achievement questionnaire. Data analysis was carried out through partial correlation and multiple correlation with a significance level of 0.05, and the prerequisite test analysis used normality, linearity, and multicollinearity tests. The results showed that mathematics anxiety influenced by self-efficacy factors, classroom climate, and academic support from parents and peers significantly affected students' learning achievement in high school. Schools can facilitate a more conducive learning environment to minimize mathematics anxiety and improve learning outcomes. Implementing a learning program that is psychologically responsive and adaptive to students' needs is expected to improve students' mathematics achievement significantly..  

This study was motivated by the discovery that some students of SMPN 1 Batang Kapas, especially students of class VIII, were less active in participating in PAI learning when teachers or tutors provided learning materials because the teacher focused on only one strategy, which caused students to get bored about learning easily. In this, a good strategy is needed to overcome this problem, and the strategy that is considered capable of overcoming this problem is the role-playing strategy. Thus, this study aims to determine the effect of role-playing strategies on the active learning of PAI for students of class VIII of SMPN 1 Batang Kapas. The research used in this study is experimental research with a quantitative approach. The population in this study consisted of all students of class VIII of SMPN 1 Batang Kapas, consisting of 4 classes with a total of 116 students. The sample in this study used a cluster random sampling technique and two classes were obtained as samples, with class VIII.I as the control class and class VIII.II as the experimental class. Data were collected through a questionnaire and analyzed using the independent sample t-test. Based on the results of the conducted research, the results show that the role-playing strategy has an effect on students' active learning, which is proven by the results of the independent sample t-test, namely at a sig-value of 0.002. < 0.05 and a calculated t-value > t-table, namely 3.213 > 2.00

This study aims to determine the role of the government in moderating the influence of economic needs, accessibility, business capital on the existence of street vendors in Bekasi City. This research is a quantitative research. The subjects in this study were street vendors in Bekasi City. The population in this study was 15,402 street vendors, based on data from  the Bekasi City Cooperative and Small Business Office. The results   of the validity test of the person correlation  are that all variables count > rtabel, a(0.05) and the reliability test of all these  variables are above 0.600. The number of samples in this study was 390 street vendors. The sampling technique uses cluster sampling. |The data analysis technique used was multiple linear regression analysis and moderating regression analysis (MRA) using the help of IBM SPSS Statistics version 26 for windows.The aims of this research are as follows: (1) Economic needs affect the existence of street vendors in Bekasi City with a parameter coefficient value of 0.179 with a significant level of 0.000<0.05 (2) Accessibility has an effect on the existence of street vendors in Bekasi City with a parameter coefficient value of 0.211 with a significant level of 0.000 < 0.05 (3) Business capital has an effect on the existence of street vendors in Bekasi City with a parameter coefficient value of 0.184 with a significant level of 0.000 < 0.05 (4) The role of the government as a moderating variable (economic needs *existence of street vendors) is able to moderate the effect of economic needs on the existence of street vendors in Bekasi City with a parameter coefficient value of 0.129 with a significant level of 0.034 < 0.05 (5) The role of the government as a moderating variable (accessibility*existence of street vendors) is able to moderate the effect of accessibility on the existence of street vendors with a parameter coefficient value of 0.183 with a parameter coefficient value of 0.183 with a significant level of 0.005 < 0.05 (6) The role of the government as a moderating variable (capital*existence of street vendors) is able to moderate the effect on the existence of street vendors with a parameter coefficient value of 0.222  with a significant level of 0.019 < 0.05

Background: Elementary school students have limited knowledge about healthy food, and the benefits of choosing healthy snacks. They do not understand the nutritional value of various types of food or the impact of consuming unhealthy snacks on their health. Students are often exposed to unhealthy snacks around them, such as fast food, snacks and sodas, and other less nutritious snacks.  Objective: This study aims to encourage changes in students' knowledge and consumption attitudes, namely replacing unhealthy snacks with healthy snacks that are beneficial to their health. Method: This study uses a pre-experimental method, with a One Group Pre Post Test design to measure students' initial abilities before and after participating in learning activities. The population of this study was all students of SDN 38 Bora, Palopo City in 2024, totaling 151 students. The sampling method used was the Cluster Random Sampling Technique as a sampling technique, because the population was quite large, and this sampling technique is often used in various studies in the health sector, 21 respondents were obtained. Results: The study showed that the average knowledge before and after was 5.90 while the average attitude before and after was 27.76, the knowledge value p value = 0.000 ≤ 0.05 then H0 was rejected using a 95% confidence level. While the attitude value p value = 0.001 <0.05. Conclusion: there is an influence of the use of Video Learning Media on knowledge and attitudes about healthy snacks for students of SDN 38 Bora, Palopo City.    

Puskesmas Kosambi employs Non-PNS staff whose discipline, particularly regarding attendance and work location, needs to be evaluated. The previous manual attendance system was found to be ineffective in monitoring staff discipline. This study aims to develop a mobile-based attendance system equipped with GPS radius and selfie photo features to improve the accuracy and management of attendance. The GPS radius feature ensures that staff can only clock in within the designated area, such as the Puskesmas area, while the selfie photo feature verifies the identity of the staff member clocking in. This study involved 24 Non-PNS staff members and used the K-Means Clustering algorithm to group staff based on their discipline levels. The results showed that the system was effective in improving staff discipline, with 11 employees categorized as highly disciplined, 10 as moderately disciplined, and 3 as lowly disciplined. The implications of this study suggest that the implementation of a mobile-based attendance system can improve attendance monitoring and enhance work discipline at Puskesmas Kosambi.

Indonesia is a country with a high level of disaster vulnerability, influenced by tectonic activity and its tropical climate. This study uses the K-Means clustering method to identify and group disaster-prone areas based on the level of vulnerability. The data used included average temperature (Tavg) and rainfall (RR) which were processed using Python. The analysis process includes data collection, pre-processing, determination of key features, and evaluation of clustering quality using the Elbow and Silhouette Score methods. The results of the grouping show two main patterns, namely flood-prone areas and drought-prone areas. These findings are expected to support the government in more effective and data-based disaster mitigation planning.  

This research aims to determine the influence of applying problem solving learning methods on student learning outcomes in the class X Islamic Cultural History subject. The type of research used is quantitative research using a Pre-Experimental design (one-group-pretest-posttest Design). The population in this study was 253 and the sample in this study was 53. The sampling technique used by researchers was Cluster Sampling. The research results obtained based on the results of the paired samples t-test analysis obtained a sig value. (2-tailed) of 0.000 with a significance level of α=0.05, which means 0.000 <0.05, so Ha is accepted and Ho is rejected. Meanwhile, it is known that the data df=31, the significance level α=0.05, the t-count value = 24.002 and the t-table = 2.021 so it can be stated that the t-count value is greater than the t-table meaning 24.002>2.021 with a correlation level of 0.960 . So Ha is accepted and Ho is rejected, meaning the influence of problem solving learning methods on student learning outcomes in SKI subjects in class is -0.041 (experimental class posttest = 84.84 and control class posttest = 59.05) which means the average score for the experimental class posttest is higher than the control class posttest. Thus it can be concluded that the problem solving method influences student learning outcomes in the SKI class X MAN 3 Banyuwangi subject.

From simple analytical cost accounting, it has now reached an integrated system to meet the needs of managers regarding the measurement of enterprise performance and the need to make the best decisions. The field of using costs in decision-making has become multifunctional and has expanded into all branches of activity, including non-productive ones. The purpose of this research is to see how motivated are the concerns of research in the academic world related to the field of costs and their usefulness in decision-making based on scientometric analysis with the help of two software tools, namely OpenAlex and VoSviewer. From the scientometric analysis undertaken, the conclusion emerges that research in the field of the use of costs in decision-making developed rapidly after 2014, with the number of journals in the economic field doubling between 2015-2024. However, there is an interconnection between the terms of one cluster and the terms of another cluster, which demonstrates the fact that the issue of costs and decisions cannot be reduced only to the field of management accounting, it requires a holistic vision and cooperation between various fields, the basis remaining however, the level of the economic field.

Indonesia, based on natural resource potential, has great potential to achieve beef self-sufficiency. The contribution of this sector is not only limited to meeting food needs in the form of beef, but also includes economic aspects such as providing employment opportunities, industrial raw materials, and increasing the income of local farmers. This shows that the development of this sector has great potential in supporting food security and improving community welfare. Therefore, research was conducted on performance indicators that could influence the performance of the cattle farming sector in Indonesia in 2022 using cluster analysis. Cluster analysis is a statistical method that identifies groups of samples based on similar characteristics. Cluster analysis has two methods, namely hierarchical and non-hierarchical. This research focuses on classifying regions in Indonesia into groups based on similar characteristics. In this research, cluster analysis assumptions will be tested, namely the multivariate normal distribution test, conducting cluster analysis using hierarchical and non-hierarchical methods, characterizing the data in each cluster, then drawing conclusions and suggestions from the research results. Based on the research results obtained on data characteristics, it was found that variables tend to have a variety of data. Hierarchical cluster analysis uses the single linkage method which has an optimum number of clusters of 4. The highest number of cluster members is in cluster 1. Then cluster 1 shows the highest performance in the cattle farming sector. In non-hierarchical cluster analysis using the k-means method which has an optimum number of clusters of 5. The highest number of cluster members is in cluster 4. Then clusters 2, 3 and 4 show higher performance in the cattle farming sector compared to clusters 1 and 5 .

Improving the quality of Human Resources (HR) is a major challenge in facing global competition. Education as the main means of improving the quality of HR in Indonesia is still faced with the problem of inequality of access and quality between regions. This inequality causes disparities in educational development between urban and remote areas. This study focuses on grouping provinces in Indonesia based on aspects of educational development in 2023, using cluster analysis. Secondary data from the Central Statistics Agency (BPS) is used as the basis for analysis, including variables of average length of schooling, Gross Participation Rate (APK), Pure Participation Rate (APM), number of senior high schools, and community literacy development index. This study uses hierarchical and non-hierarchical cluster analysis methods to group provinces in Indonesia. The results of the hierarchical cluster analysis using the average linkage method show the most optimal cluster with the formation of three clusters. The first cluster consists of 31 provinces, the second cluster consists of 2 provinces, and the third cluster consists of 1 province. Data characteristics show large variations in the number of senior high schools and relative homogeneity in the average length of schooling between provinces.

MSMEs are a supporting sector of the country's economy and are able to survive in various conditions that occur in Indonesia. MSMEs are able to contribute to increasing national income and also help in absorbing labor as a result of increasing the performance of these MSMEs. Many factors that influence performance between mental accounting and financial technology are mediated by financial inclusion. The results of a preliminary survey on MSMEs in Grobogan Regency show that the average performance of MSMEs is still fluctuating. The object of this research was carried out on MSMEs in Grobogan Regency with a final sample size of 158 using the cluster random sampling method. The analysis tool uses a regression equation test with a mediation test using the Sobel test. The results of the descriptive analysis show that the variables mental accounting, financial technology, MSME financial inclusion and MSME performance in Grobogan Regency are in the sufficient category (2.33 to 3.65), with financial technology with the highest average. The mental accounting and financial technology variables are proven to have a positive and significant effect on the financial inclusion of MSMEs in Grobogan Regency. Mental accounting, financial technology and MSME financial inclusion are proven to influence the performance of MSMEs in Grobogan Regency. MSME financial inclusion is proven to mediate the influence of mental accounting and financial technology on MSME performance in Grobogan Regency.

Maternal and child health issues are still a serious concern for the government today. The high maternal, infant and toddler mortality rates make KIA a top priority in the Ministry's program.Health problems at the Kalibobo Health Center are still the center of attention where in 2023 there were 2 child deaths including nutritional problems. Objective: To analyze the achievement of indicators of the nutritional health program, mothers and children against the healthy family index in Kalibobo Village, Nabire Regency. Method: Observational research is descriptive. Using the Community Diagnosis (Needs Assessment) method with a cross-sectional approach. The sample size120 familiesusing cluster random sampling method. The interview results were collected and data reduction, data presentation and conclusion drawing were carried out. Results: ANC examination 74% (national target 95%), complete basic immunization 89% (national target 90%), infants aged 0-6 months who received exclusive breastfeeding 67% (national target 60%) and toddlers whose growth was monitored 75% (national target 85%). Conclusion: Based on the 4 indicators evaluated, there are 2 indicators that can be said to be successful, namely the achievement of toddlers who received complete basic immunization and infants aged 0-6 months who received exclusive breastfeeding. Suggestion: to establish cross-sector cooperation in the community so that community knowledge, attitudes, and behavior can be better in utilizing existing health services, especially maternal and child health services.

The determination of outstanding students is based on different criteria, depending on the type of achievement that is to be measured. At SMK Migas Cepu, this assessment is typically based on the highest academic score from the class promotion exam. However, this method is considered less accurate and problematic in terms of grouping students. To address this issue, a clustering method using the K-Means algorithm can be applied. The purpose of this research is to build a K-Means model to determine outstanding students. The data used in this study comes from the report card ledger of class XI Machine A and B for the year 2022, which includes 71 students at SMK Migas Cepu. The RapidMiner tool was used to build the K-Means model and cluster the data based on student characteristics. The first test conducted using Excel resulted in two clusters: 35 outstanding students and 36 non-outstanding students. Meanwhile, the second test using the RapidMiner model produced two clusters with a distribution of 26 outstanding students and 45 non-outstanding students.

This study aims to analyze the impact of workload and role conflict on burnout in students of the Recognitive Learning of Past (RPL) program of the University of UKI. Burnout, a condition of mental, emotional, and physical exhaustion, can have a significant impact on the academic performance of RPL students who have generally had work experience. Using a quantitative approach, the study involved a sample of 66 RPL students selected through cluster sampling. The data is collected using validated questionnaires and analyzed using the double linear regression method. The results of the t test showed that the workload had a significant influence on burnout with a t count value of 9,252 > 1,669 t tables. Similarly, the conflict of roles proved to have a significant impact on burnotes with the t count of 11,392 > 1,669 t tabels. These findings indicated that both independent variables had a strong positive influence upon burnout, with the role conflict showing a greater influence. The results of this study emphasize the importance of workload management and role conflict resolution in the context of RPL education to prevent burnout, improve student academic success and improve the quality of work.

Poverty in Aceh Province is a significant challenge with variation between districts/cities due to differences in access to education, health, job opportunities, and infrastructure. This study aims to group districts/cities in Aceh based on poverty indicators in 2021 in order to produce a more targeted policy basis. The research data consists of 23 poverty indicators obtained from secondary sources. Cluster analysis is applied using hierarchical (average linkage) and non-hierarchical (K-Means) methods to identify poverty patterns between regions. The results of the hierarchical cluster show that there are two main groups, namely the first cluster has low poverty rates, higher education, strong purchasing power, and low unemployment, while the second cluster has the opposite characteristics. The non-hierarchical analysis (K-Means) produced five clusters with significant differences in poverty levels, labor force participation, education, and economy. These findings provide a basis for the Aceh government to design poverty alleviation policies that focus on the specific needs of each cluster to accelerate the improvement of welfare in all districts/cities in Aceh Province.

Indonesia is an agricultural country with great potential in the agricultural sector, both as a source of livelihood and as an economic driver. This sector has an important function in food security, improving farmers' welfare, and preserving the environment. Given Indonesia's regional diversity, it is important to develop policies that suit the agricultural characteristics of each region. This research uses the clustering method, a technique that groups data based on similar characteristics so that objects in one group (cluster) have high similarities, while between clusters they are different. This research applies the clustering method to group provinces in Indonesia based on agricultural sector factors in 2023, using hierarchical and non-hierarchical techniques. The results show that the optimum clusters obtained using both single linkage and K-Means formed five optimal clusters. The Java Island cluster shows high productivity, while Riau, East Kalimantan and North Kalimantan have quite high productivity with minimal labor. The largest clusters have a lot of unmanaged land, increasing employment opportunities. Significant variables influence grouping.

This research aims to analyze the best-selling products at Toko Hartati using the K-Means Clustering method. K-Means Clustering is an unsupervised learning algorithm that is effective in grouping data based on certain similar characteristics. In this context, the data used includes the number of sales, product prices, and product categories. Through this analysis, it is hoped that insight can be gained regarding products that have the best sales performance, as well as sales patterns that can be used as a reference in stock management and marketing strategies. The data used in this research includes sales transactions during a certain period, with the aim of identifying product clusters based on sales patterns. The analysis results show the existence of two main product groups, where the first cluster contains products with high sales numbers, which can be classified as best-selling products, while the second cluster includes products with lower sales. These findings provide valuable information for the management of Toko Hartati in determining more targeted marketing strategies and more efficient stock management. This research suggests using the K-Means Clustering method in data-based decision making to improve sales performance in retail stores.

Incident fever bloody globally increasing​ sharp. Death consequence fever bleeding in Indonesia from 725 cases in 2020 increased to 1,227 cases in 2022. Study aiming analyze factor affecting​ DHF incidents in the work area Sako Health Center Palembang in 2024. Research conducted in March 2024. Research design quantitative with cross sectional approach. Population that is all KK in the work area Sako Health Center has 9,584 people. A sample of 99 people was taken use cluster random sampling technique with Single-Stage Cluster Sampling. Research results influence knowledge (p value 0.011), influence attitude (p value 0.351), influence behavior clean bathtub (p value 0.603), influence condition container (p value 1.000), influence existence larvae mosquitoes (p value 0.035), influence use wire gauze (p value 0.054) and influence role government (p value 0.095) against DHF incidents in the work area Sako Health Center, Palembang. Multiple logistic regression test results obtained knowledge (p value 0.001), existence larvae mosquitoes (p value 0.022), use wire gauze (p value 0.014) and role government (p value 0.028). There is influence knowledge and existence larvae mosquito to DHF incidents. The most dominant factor to the incidence of dengue fever is knowledge. Recommended For increase effort prevention of dengue fever with do action prevention in a way real and sustainable.