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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.

This study aims to analyze the influence of brand image, word of mouth, and product quality on the purchase decision of Facetology skincare products. The study uses a quantitative method to obtain objective and generalizable results. The sample consisted of 100 respondents, who were individuals who had purchased or used Facetology skincare products. The sampling technique used was purposive sampling, ensuring that the selected respondents met criteria relevant to the research objectives. Data collection was conducted through the distribution of questionnaires to the selected respondents to gather the necessary information. The data analysis technique employed was Smart PLS 4.0, which efficiently and accurately measures the relationships between variables. This study emphasizes the importance of understanding the factors influencing purchase decisions in the skincare industry, particularly for the Facetology brand. The results of the study indicate that word of mouth has a positive and significant effect on the purchase decision of Facetology products. Additionally, brand image was found to have no significant effect on the purchase decision, while product quality had a positive and significant effect on the purchase decision of Facetology products. The implications of this study suggest that the company can leverage word of mouth as an effective marketing strategy and focus more on improving product quality to influence consumer purchase decisions.

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.

Digital transformation in the supply chain is the main driver of increasing industrial competitiveness in the modern era. This study aims to analyze the influence of supply chain digitalization on industrial production efficiency through information integration, process optimization, and strengthening collaboration between supply chain actors. The method used is a qualitative approach based on literature studies on various previous studies that discuss the application of digital technologies, such as the Internet of Things (IoT), big data analytics, blockchain, and Enterprise Resource Planning (ERP), in industrial supply chain management. The results of the study show that digitalization increases the visibility of supply chain activities in real-time, allowing companies to monitor the movement of raw materials, production processes, and distribution more accurately. Digital integration also strengthens the company's internal and external coordination, thereby accelerating decision-making and increasing the effectiveness of collaboration with supply chain partners. In addition, the application of digital technology encourages the optimization of production processes through automation, more precise planning of material needs, and reduction of uncertainty of demand and supply. A number of studies report a decrease in lead-time, operational cost efficiency, and improved product quality as a positive impact of digitalization. However, the literature also identifies implementation challenges, such as technology gaps, resistance to organizational change, and significant initial investment needs. Overall, this study concludes that supply chain digitalization is a crucial strategy to improve production efficiency, operational resilience, and company responsiveness to market dynamics, as well as provide a basis for the development of industrial digitalization strategies and advanced research.

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.

The purpose of writing this paper is to find out the role of sea toll ships in supporting logistics distribution in disadvantaged areas by PT. Subsea Lintas Globalindo Tanjung Perak Surabaya branch. The methods used in data collection are the field method through observation, as well as the library research method, to understand the extent of the sea toll ship operated by PT. Subsea Lintas Globalindo Tanjung Perak Surabaya Branch contributes to smoothing the flow of logistics distribution to disadvantaged areas, especially in Eastern Indonesia. The results of the study show that sea toll ships play a strategic role in reducing the disparity in the price of goods, increasing logistics accessibility, and supporting equitable development and economic growth in remote areas. The obstacles faced include uncertain weather factors, limited port infrastructure, and coordination that still needs to be strengthened between related institutions. Therefore, better synergy is needed between the government, ship operators, and other stakeholders, including the private sector and local communities, to optimize the benefits of the sea toll program in a sustainable manner, improve distribution efficiency, and support equitable distribution of welfare throughout Indonesia.

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.

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.

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 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.

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.

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 study aims to analyze the role of Village-Owned Enterprises (BUMDes) in improving community welfare in Tanarawa Village, Waiblama District, Sikka Regency, and to evaluate the implementation of BUMDes programs. Tanarawa Village has primary economic potential in the plantation and food crop sectors, managed largely by the community as farmers. BUMDes was established as an instrument for village economic empowerment with the aim of increasing Village Original Income (PAD), strengthening the local economy, and maximizing the utilization of natural resources and human resources. This study used a qualitative descriptive approach with data collection techniques including observation, interviews, and documentation. The results indicate that BUMDes Tanarawa is still in the development stage, although it has been able to contribute to community welfare through the provision of basic necessities, training, outreach, and consultations related to business management. The success of BUMDes is influenced by government support, quality leadership, community participation, and transparent and accountable management. However, limited understanding by the community and village officials, as well as obstacles in implementing outreach, are inhibiting factors that need to be addressed. This study confirms that BUMDes plays a strategic role in local economic empowerment, improving community welfare, and equitable distribution of village economic growth.

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.

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.

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.  

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 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.

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.

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.