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This study examines the dynamics of Buddhist religious counseling services in North Kalimantan Province in the post-pandemic period, particularly focusing on satisfaction levels and the distribution of counselors across districts. Using a quantitative approach with descriptive and correlational designs, the study involved a population of 9 Buddhist counselors and 3,993 congregants, with 98 selected respondents. Satisfaction levels were measured using the SERVQUAL framework, which evaluates service quality through five key dimensions. Findings show an overall satisfaction score of 3.65 (out of 5), categorized as “satisfied.” The highest rating was in the assurance dimension, reflecting public trust in counselor competence. However, empathy and responsiveness dimensions scored lower, especially in regions with few or no assigned counselors. A Pearson correlation analysis yielded a weak positive relationship (r = 0.214) between counselor-to-congregant ratios and satisfaction scores, emphasizing that equitable distribution is more crucial than sheer numbers. This research underscores the urgent need for needs-based distribution policies and hybrid service strategies that combine digital and in-person modalities. The results offer important policy implications, highlighting that spiritual service equity contributes to social cohesion and emotional well-being, especially in pluralistic and geographically dispersed regions.

The increasing poverty rate in West Bandung Regency has encouraged BAZNAS to introduce the Z-Mart programme, which provides business capital assistance as an effort to improve community income. The effectiveness of the programme is assessed based on its ability to achieve predetermined targets and comply with organisational regulations. This study adopts a quantitative approach, involving 151 mustahik as the population, with 61 mustahik selected as the sample to complete the questionnaire. The objective of this study is to evaluate the effectiveness of zakat fund distribution on mustahik income in the Z-Mart programme implemented by BAZNAS of West Bandung Regency. Data analysis using SPSS version 25.0 indicates that the independent variable (X) contributes 59.8 per cent, and that the effectiveness of zakat distribution has a significant effect on mustahik income (R-square = 0.357). Regression analysis reveals that a one-point increase in distribution effectiveness contributes to a positive increase of 0.814 points in mustahik income. The t-test results show that the calculated t-value (5.725) exceeds the critical t-value (1.671), indicating acceptance of the alternative hypothesis and rejection of the null hypothesis. Therefore, this study concludes that the distribution of zakat funds through the Z-Mart programme is effective in improving the income level of mustahik in BAZNAS of West Bandung Regency.

This study aims to analyze the influence of product quality on consumer satisfaction in the Kipang Sisera Panyabungan Business. The research method used is a quantitative approach with data collection techniques through observation, interviews, and questionnaire distribution to 96 respondents who are customers of Kipang Sisera. The data obtained were analyzed using validity, reliability, and regression analysis tests with the help of SPSS 25. The results of the validity test showed that all items in the questionnaire were valid with a rtable value of > (0.1689), while the results of the reliability test using Alpha Cronbach showed a value of > 0.60, which means that the research instrument is trustworthy. The results of the partial regression test (t-test) showed that product quality had a positive and significant effect on consumer satisfaction with a significance value of 0.000 < 0.05. The determination coefficient (R²) test showed that product quality contributed 62.9% to consumer satisfaction, while the rest was influenced by other variables that were not studied in this study. These findings indicate that improving product quality, both in terms of taste, packaging, and quality consistency, is very important in maintaining consumer satisfaction and the sustainability of Kipang Sisera's business in the midst of market competition.

The development of small and medium enterprises (SMEs) and household industries is often regarded as the economic foundation of a region. However, much of the existing research in Indonesia remains focused on quantitative descriptive analysis, while providing limited attention to spatial dynamics and interregional disparities. This study aims to critically evaluate the spatial distribution patterns of SMEs and household industries at the regency and city levels, with particular emphasis on clustering tendencies, unequal distribution, and their relationships with regional characteristics. A spatial analysis approach is employed to identify spatial autocorrelation and industrial clustering patterns, which is complemented by a structural analysis of infrastructure availability, market accessibility, and regional institutional capacity. The findings indicate that the distribution of SMEs and household industries is not geographically random, but rather forms clusters that are predominantly concentrated in areas with higher levels of accessibility and economic activity. This condition reflects spatial inequality that may exacerbate development disparities between regencies and cities. Furthermore, the results reveal that uniform industrial development policies are insufficient to accommodate the diverse spatial characteristics across regions. Therefore, this study underscores the importance of formulating spatially informed and context-sensitive policies for the development of SMEs and household industries in order to promote more balanced and sustainable regional industrial development.

Poverty is still a major problem in regional economic development in Jambi Province, although economic growth has been relatively stable in recent years. This condition shows that economic growth has not been fully followed by an equitable distribution of development results. This study aims to analyze the influence of economic growth and income inequality on the poverty rate in Jambi Province. The research uses a quantitative approach with district/city panel data for the 2015–2024 period sourced from the Central Statistics Agency. The analysis was carried out using the panel data regression method to test the relationship between economic growth variables, income inequality, and poverty levels. The results of the study show that economic growth measured through the growth rate of Gross Regional Domestic Product (GDP) has a negative effect on the poverty rate, meaning that increasing economic growth can reduce the number of poor people. On the other hand, income inequality measured by the Gini Ratio has a positive effect on poverty levels, which means that the higher the income inequality, the greater the poverty rate. These findings indicate that poverty reduction strategies not only require sustainable economic growth, but must also be accompanied by income equity policies so that the benefits of development can be felt more inclusively by all levels of society.

Public service reform in Indonesia increasingly emphasizes inter-agency collaboration as a mechanism to enhance administrative efficiency, service integration, and responsiveness to citizens’ needs; however, in many regions, including West Kotawaringin Regency, collaborative practices remain fragmented due to uneven human resource (HR) capacities, inconsistencies in standard operating procedures (SOPs), and limited technological integration across institutions. This study aims to examine the current state of HR collaboration, identify key barriers and enabling factors, and propose an integrated and adaptive HR collaboration model to strengthen public service delivery. Using a qualitative multi-case study approach, data were collected through semi-structured interviews with leaders and operational staff from multiple regional government agencies and analyzed using NVivo 15 to generate thematic coding and visual tools such as word clouds, hierarchy charts, and project maps. The findings indicate that current collaboration is largely transactional and administrative, exemplified by the physical co-location of agencies at the Public Service Mall (MPP) without effective systemic interoperability. Three critical themes emerged: gaps in HR distribution, competencies, and role clarity; structural and behavioral constraints including sectoral ego, SOP discrepancies, and limited digital integration; and opportunities to enhance collaboration through shared digital dashboards, inter-agency forums, and cross-functional HR mobility. Based on these results, the study proposes a three-pillar Integrated and Adaptive HR Collaboration Model comprising comprehensive digital integration, flexible HR competency sharing, and inclusive service co-creation involving community stakeholders, offering both theoretical contributions to collaborative governance and practical guidance for regional governments seeking to improve public service effectiveness.

This study aims to examine business models in the gypsum sector by utilizing the Business Model Canvas (BMC) framework. The gypsum business is one of the fields that is growing rapidly in line with the increasing need for residential construction, building renovation, and aesthetic and functional interior design. However, to be able to survive and compete in an increasingly competitive market, gypsum business actors are required to have a business model that is structured, adaptive, and value-oriented for customers. This study uses a qualitative approach with a descriptive type of research. Data collection was carried out through in-depth interviews and direct observation of Nury Gipsum's business located in Klaten Regency. The results show that all nine elements in the Business Model Canvas, namely key partners, key activities, key resources, value offerings, customer relationships, distribution channels, customer segments, cost structure, and revenue streams, have been optimally implemented. Thus, the Business Model Canvas has proven to be effective in providing a comprehensive overview of business operations and can be a strategic basis for decision-making and gypsum business development in the future.

The Indonesia Pintar Program (PIP) is an educational assistance program for students from underprivileged families, but determining the eligibility of recipients still faces obstacles in the form of subjectivity and data imbalance. This study aims to classify the eligibility of high school students receiving PIP in Jambi City using data mining methods. The SMOTE technique was applied to overcome class imbalance, and Gain Ratio feature selection was used to determine important attributes. The dataset used consisted of 19,596 student data with a training data distribution of 70% and testing data of 30%. The classification process used the Naïve Bayes, Decision Tree (J48), and Random Forest algorithms with the Use Training Set, 5-Fold, and 10-Fold Cross Validation testing schemes. The results show that SMOTE improves model performance, but feature selection in some cases reduces accuracy. Overall, Random Forest without feature selection provides the best results with an accuracy of 93.33% and is recommended as the most effective model for objectively determining PIP recipient eligibility.

Stunting and wasting are nutritional problems in toddlers that remain a double burden of malnutrition in Indonesia and have an impact on the quality of health and future human resource development. Monitoring the nutritional status of toddlers is generally carried out using anthropometric indicators, but the use of this data is still limited to descriptive analysis. This study aims to apply the K-Means algorithm in clustering infants vulnerable to stunting and wasting based on anthropometric indicators, so that groups of infants with different levels of nutritional vulnerability can be identified. The dataset used consists of infant data with variables of gender, age (months), height (cm), and weight (kg). The research stages included data preprocessing, encoding categorical variables, data normalization, determining the optimal number of clusters using the Elbow and Silhouette Score methods, and analyzing the characteristics of each cluster. The evaluation results showed that the optimal number of clusters was four. Each cluster has different anthropometric characteristics and distributions of stunting and wasting status, ranging from groups with relatively normal nutritional conditions, groups with a tendency toward overnutrition, to groups that are vulnerable to acute and chronic malnutrition. These clustering results provide a more comprehensive and segmented mapping of toddlers, which can be used as a basis for formulating more targeted and data-driven nutrition policies and interventions.

Budget efficiency is an important issue in state financial management because it is directly related to government spending priorities and their impact on public service programs. Discussions about budget efficiency policies are widespread on social media platform X, generating diverse public responses, thus necessitating an automated approach to understand public opinion trends more quickly and objectively. This research aims to analyze the sentiment of Indonesian people toward budget efficiency policies and compare the performance of the Naïve Bayes and Support Vector Machine (SVM) algorithms in classifying sentiment. The research data used 10,909 Indonesian-language tweets sourced from a public dataset, which were then processed thru the preprocessing stages including cleaning, case folding, normalization, tokenization, stopword removal, and stemming. Sentiment labeling is performed automatically using the Indonesian Sentiment Lexicon (InSet) approach to categorize data into positive, negative, and neutral sentiments. Feature extraction was performed using Term Frequency–Inverse Document Frequency (TF-IDF), and then the data was divided into training and testing sets with an 80:20 ratio. Model performance evaluation was conducted using a confusion matrix and the metrics of accuracy, precision, recall, and F1-score. The research results show that sentiment distribution is dominated by negative sentiment at 56.78%, followed by positive sentiment at 37.40%, and neutral sentiment at 5.83%. In the classification stage, SVM performed best with an accuracy of 86%, while Naïve Bayes achieved an accuracy of 74%. These findings indicate that SVM is more optimal for sentiment classification on social media text data and can be utilized to more effectively support the analysis of public response to budget efficiency policies.

This research examines the influence of road infrastructure development on local economic growth in Medan City, emphasizing its role in improving accessibility and supporting economic activities. Road infrastructure is a vital component of regional development, as it facilitates the movement of goods and services, reduces transportation costs, and enhances connectivity between economic centers. Well-developed road networks can stimulate business expansion and encourage investment by creating a more efficient economic environment. The study employed a descriptive quantitative approach using field surveys involving 20 respondents, including business actors, local residents, and government representatives. Data were collected through structured questionnaires and analyzed descriptively to capture perceptions regarding the economic impact of road infrastructure development. The results indicate that improvements in road quality, capacity, and connectivity have a positive influence on local economic growth. Respondents reported increased trade activities, improved access to markets, higher investment opportunities, and rising community income levels as direct benefits of improved road infrastructure. However, the study also identified several challenges that may hinder long-term economic outcomes. Traffic congestion, uneven infrastructure development across areas, and inadequate routine maintenance were highlighted as significant issues. These problems can reduce efficiency and limit the sustainability of economic gains. Therefore, continuous government commitment, effective maintenance strategies, and equitable distribution of infrastructure development are essential. Strengthening coordination among stakeholders is also necessary to ensure that road infrastructure development supports inclusive and sustainable local economic growth in Medan City.

This study aims to design and build a population distribution application in Demak Regency in 2025 using a Geographic Information System (GIS) approach. The study focuses on three main variables: population, population density, and population growth rate per sub-district. The author used the research method of collecting data and references that can later strengthen the results of this study and the application design using the waterfall model. Non-spatial data, namely data in the form of population information, was obtained from the Central Statistics Agency of Demak Regency, while spatial data is data related to regional administrative boundaries. Data processing was carried out using QGIS 2.18 through the stages of joining attributes, classification using the Natural Breaks (Jenks) method, and thematic map creation. The results show that population distribution is uneven. Demak Kota, Karangtengah, and Sayung sub-districts have the highest number and density, while coastal sub-districts such as Wedung and Bonang have low densities. The highest population growth rate is in Karangtengah sub-district at 0.8%. The application of GIS has proven effective in visualizing population distribution and supporting spatial-based regional development planning.  

Tebing Tinggi City, which has a strategic position in North Sumatra, is experiencing changes in population growth that need to be predicted for development planning purposes. The purpose of this study is to forecast the population of Tebing Tinggi City in 2030 by applying the Double Integral method, and visualize the results in 3D using GeoGebra. The method used is a quantitative approach with a case study, where the population density function is created based on secondary data from the Central Statistics Agency (BPS) of Tebing Tinggi City for the period 2010 to 2024. Data on area and population per sub-district are used to develop a population growth model calculated using the double integral. The forecast results show that the population of Tebing Tinggi City is estimated to reach 26,038 people in 2030, with varying growth rates in each sub-district. 3D visualization through GeoGebra is able to depict the distribution of population density in an interactive geometric form, thus facilitating the understanding of complex mathematical concepts. The conclusion of this study is that double integrals can be applied effectively to predict population size, and GeoGebra serves as a very useful visual aid in presenting the results of multivariable calculus analysis.

This study aims to examine and analyze the effects of product quality and distribution channel on repurchase intention, with customer satisfaction and customer trust serving as mediating variables. The research employed a quantitative method with a causal-explanatory approach. The study population consisted of customers at the Weber building materials manufacturing company in East Java, with a sample of 275 respondents selected using purposive sampling. Data were collected via questionnaires and assessed using a Likert scale. The data analysis was conducted using the Structural Equation Modeling (SEM) technique with Partial Least Squares (PLS) software. The findings of the study reveal the following: 1) Product quality has a significant positive effect on customer satisfaction; 2) Product quality has a significant positive effect on customer trust; 3) Product quality has a significant positive effect on repurchase intention; 4) Distribution channel has a significant positive effect on customer satisfaction; 5) Distribution channel has a significant positive effect on customer trust; 6) Distribution channel has a significant positive effect on repurchase intention; 7) Customer satisfaction has a significant positive effect on customer trust; 8) Customer satisfaction has a significant positive effect on repurchase intention; 9) Customer trust has a significant positive effect on repurchase intention.

This study aims to examine and analyze the effects of product quality and distribution channel on repurchase intention, with customer satisfaction and customer trust serving as mediating variables. The research employed a quantitative method with a causal-explanatory approach. The study population consisted of customers at the Weber building materials manufacturing company in East Java, with a sample of 275 respondents selected using purposive sampling. Data were collected via questionnaires and assessed using a Likert scale. The data analysis was conducted using the Structural Equation Modeling (SEM) technique with Partial Least Squares (PLS) software. The findings of the study reveal the following: 1) Product quality has a significant positive effect on customer satisfaction; 2) Product quality has a significant positive effect on customer trust; 3) Product quality has a significant positive effect on repurchase intention; 4) Distribution channel has a significant positive effect on customer satisfaction; 5) Distribution channel has a significant positive effect on customer trust; 6) Distribution channel has a significant positive effect on repurchase intention; 7) Customer satisfaction has a significant positive effect on customer trust; 8) Customer satisfaction has a significant positive effect on repurchase intention; 9) Customer trust has a significant positive effect on repurchase intention.

This study examines the video content production process at Digital Hub Sinar Mas Land as a visual communication strategy to support branding for a digital innovation area. The background of this research stems from the increasing need for organizations to produce creative and informative content as social media becomes a primary channel for information distribution. The study aims to describe the stages of pre-production, production, and post-production, and to identify challenges that affect the effectiveness of video content creation. A qualitative descriptive method was used through active participation, observation, interviews, and literature review. The findings show that concept planning, scriptwriting, and storyboard development form the foundation of successful production. The production stage emphasizes camera techniques, talent coordination, and visual consistency aligned with communication goals. The post-production stage focuses on technical editing to strengthen the audiovisual message structure and prepare content for publication. Key challenges were found in storyboard development, talent performance during filming, and audio processing that required detailed adjustments. The results highlight the importance of thorough planning and coordinated teamwork to ensure that video content effectively supports branding strategies.

This study aims to analyze the influence of Corporate Image and Service Quality through Customer Satisfaction on Customer Loyalty at Semen Indonesia distributors in Gresik using the Structural Equation Modeling (SEM) approach. The study population consisted of 102 customers, all of whom were sampled. The results indicate that Corporate Image and Service Quality have a significant influence on Customer Satisfaction. Both variables were also shown to have a significant influence on Customer Loyalty. However, unlike several previous research findings, Customer Satisfaction did not have a significant influence on Customer Loyalty. This finding indicates that in the context of the cement distribution business, customer loyalty is not formed solely from satisfaction, but is more influenced by other factors such as consistent service quality, a strong corporate image, competitive pricing, and long-term business relationships. This study emphasizes the importance of strengthening image and improving service quality as key strategies for maintaining customer loyalty.

ABSTRACT Background: Imminent Premature Delivery (PPI) is a situation where there is a threat to pregnancy caused by regular uterine contractions accompanied by cervical changes at a gestational age of less than 37 weeks. In Indonesia, based on the 2018 Basic Health Research, the prevalence of premature birth reached 29.5% of 1000 live births. At Ngoerah Hospital, Denpasar, the incidence of PPI from 2020 - 2024 based on data reached 642 out of 4,196 (15.30%) total deliveries. Objective: The aim of this study was to determine the incidence of Imminent Premature Parturition at Ngoerah Hospital, Denpasar, from 2020 to 2024. Method: The type of descriptive research with a total sampling technique, namely all pregnant women who had received conservative treatment at Ngoerah Hospital, Denpasar from 2020-2024, amounting to 642 people. The type of secondary data taken from data from 2020 to 2024. Results: The distribution of PPI patients included hemoglobin levels of 8-11 g / dl, namely 100%, mothers aged 21 - 35 years, namely 75%, working mothers, namely 73.9%, KPD, namely 68.8%, infection, namely 15.6%, preeclampsia with severe symptoms, namely 10.1%, twin pregnancies, namely 14.3%, and pregnancy spacing <18 months, namely 0.8%. Conclution: The most influential factor in the occurrence of PPI is low HB levels combined with the mother being relatively young and actively working.

Zakat Fitrah is one of the obligations in Islam aimed at purifying the soul and strengthening social solidarity among Muslims. This study aims to analyze the level of public awareness in paying Zakat Fitrah in RT 05, Ngolorog Hamlet, Mojopuro Village, Jatiroto Subdistrict, Wonogiri Regency. The method used includes in-depth interviews with community leaders and field observations. The results show that residents have a high level of awareness regarding the obligation of Zakat Fitrah, yet there are still obstacles such as a lack of understanding of the procedures for payment and distribution. Factors such as education, income, and socialization by religious leaders play a significant role in enhancing awareness. The conclusion of this study recommends improving educational programs and zakat campaigns by the village government and religious institutions to encourage better compliance, thereby contributing to social welfare in the area. This research is expected to serve as a reference for developing zakat programs in rural regions.

This study examines the role of officially appointed amil zakat in enhancing transparency and accountability in zakat governance in Mojopuro Village, Wonogiri Regency. Prior to this initiative, Mojopuro had no Zakat Collection Unit (UPZ), resulting in zakat practices that were traditional, undocumented, and lacking institutional oversight. Through a series of mentoring activities and seminars conducted from 8–18 September 2025, capacity-building efforts were directed toward prospective amil zakat, village officials, and religious leaders, focusing on zakat regulations, principles of transparency, and both vertical and horizontal accountability. The implementation methods included material delivery, group discussions, and consultative sessions, which ultimately led to the formal appointment of official amil zakat by the Wonogiri Regency BAZNAS. The findings demonstrate that the presence of official amil significantly improved the structural management of zakat, enhanced participants’ understanding of transparency and accountability, and strengthened coordination among amil, village administrators, and religious figures. These results indicate that village-based institutional mentoring can foster a transformative shift from traditional zakat practices toward professional, transparent, and accountable governance. This study thus offers a community-based empowerment model that can be replicated in other villages to improve zakat distribution effectiveness and build public trust in formal zakat institutions.