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Micro, Small, and Medium Enterprises (MSMEs) play a strategic role in promoting economic growth and improving community welfare, particularly at the regional level. In Nagekeo Regency, the ikat weaving craft sector represents an important local economic potential that also carries significant cultural value. However, weaving entrepreneurs still face several challenges, including limited business capital, restricted market access, and low utilization of digital technology for product marketing. This study aims to analyze the role of the Department of Cooperatives, Industry, and Trade of Nagekeo Regency in empowering MSME actors, particularly ikat weaving groups. The research employs a qualitative approach with a descriptive research design. The study involved 18 informants consisting of local government officials, MSME actors, and institutional partners selected through purposive sampling. Data collection techniques included observation, in-depth interviews, and documentation, while data analysis was conducted through data reduction, data presentation, and conclusion drawing. The findings indicate that the department performs facilitative, educative, and technical roles in empowering weaving groups through production training, digital marketing assistance, provision of business facilities, and technical guidance on product innovation. These programs contribute to improving weavers’ skills, product quality, and market opportunities, although their implementation still faces limitations related to budget constraints and uneven program coverage.

This study aims to develop a storytelling-based learning media in the form of a YouTube video to support students’ understanding of narrative text based on their learning needs. This study employed a Research and Development (R&D) design using the ADDIE model, focusing on the stages of analysis and development. The data were collected through a questionnaire as part of the needs analysis to identify students’ responses toward listening and repetition activities, as well as the difficulties they face in understanding narrative texts. The results show that students generally respond positively to listening and repetition. However, they still experience difficulties in understanding the storyline and vocabulary. The findings also indicate that students need learning support in the form of audio, visual elements, and vocabulary assistance. Based on these findings, a learning product was developed in the form of a YouTube-based digital storytelling video entitled “Learn Narrative Text Through Fun Storytelling (Listen, Repeat & Retell)”. The video integrates storytelling, repetition, vocabulary explanation, and speaking practice to support students’ comprehension. Due to time limitations, this study was limited to the development of a prototype and has not yet included expert validation. Therefore, future research is recommended to conduct validation to evaluate the feasibility and effectiveness of the developed product.

This study aims to analyze the fluctuations in chili production in Kabanjahe District, Karo Regency, which affect market price instability and uncertain supply. One approach applied in this study is the Single Exponential Smoothing (SES) method to forecast chili production. SES was chosen for its simplicity, ease of implementation, and its ability to generate accurate predictions even when the data lacks significant seasonal patterns. The data used is secondary data on chili production obtained from official publications by the Karo Regency BPS for the period of 2020–2024. The analysis results show that a smoothing parameter (α) of 0.8 produced the lowest Mean Absolute Percentage Error (MAPE) of 3.08%. These findings indicate that applying a higher α makes the model more responsive to recent data changes, thus yielding more accurate forecasts. This study demonstrates the effectiveness of the SES method in forecasting chili production in areas with significant seasonal fluctuations.

The performance of asphalt mixtures is strongly influenced by the composition of their constituent materials, particularly aggregate size and mixing temperature during production. In many tropical and subtropical regions, asphalt pavements frequently experience rutting, reduced stability, and changes in viscoelastic properties due to high environmental temperatures and heavy traffic loads. These conditions can significantly affect pavement durability, making it essential to produce asphalt mixtures that meet established technical standards. This study aims to analyze the effect of variations in aggregate size distribution and mixing temperature on the Marshall characteristics of Asphalt Concrete Wearing Course (AC-WC) mixtures. The research employs the Marshall test method to evaluate the load-bearing capacity and stability of hot asphalt mixtures and to assess their compliance with ASTM/SNI standards. The results indicate that mixtures with standard aggregate gradation achieve stability values of 985 kg at 120°C, 1055 kg at 140°C, and 1107 kg at 160°C. As mixing temperature increases, flow values decrease, while the Marshall Quotient (MQ) increases, indicating improved stiffness. Higher temperatures also enhance compaction, reducing VIM and VMA while increasing VFA. Conversely, non-standard aggregate gradations result in several parameters failing to meet ASTM/SNI requirements, confirming that standard gradation produces superior asphalt performance.

This study was designed to create a visual communication medium in the form of a video mapping depicting the institutional change process from the Nahdlatul Ulama Institute of Technology and Science (ITSNU) Pasuruan to the Nahdlatul Ulama University of Pasuruan (UNU Pasuruan). This institutional status change represents a strategic moment that needs to be communicated to the public through a creative and engaging media approach. The research approach used the Research and Development (R&D) method, referring to Sugiyono's development framework, which consists of ten stages: identification of potential and problems, data collection, product design, design validation, design refinement, product testing, product refinement, implementation trials, final product revisions, and mass production (if necessary). Data collection techniques included in-depth interviews, field observations, documentation studies, and validation by media and content experts. The research output is a video mapping product, approximately 7 minutes in length, that has undergone a validation process and is deemed suitable as a means of communicating institutional change. This product is expected to serve both as a visual archive and as a more effective and communicative institutional promotion instrument.

This research examines the influence of the Webtoon platform on the creativits and literary marketing of Gen – Z in Indonesia, with a focus on the increasingly common trasition of digital content to physical books. The research background is grounded in the rapid growth of Webtoon as a platform for illustrated stories accessed by millions of young users via mobile devices, enabling affordable creative expression, but often encountering adaptation challenges to print formats due to differences in distribution and monetization. The primary objective is to analyze how Webtoon shapes the creative processes of young writers and their literary marketing strategies. The research method is qualitative, involving in-depth analysis of 10 popular Webtoons on the Webtoon platform that have been adapted into physical books, with emphasis on narrative elements, visuals, community interactions, and marketing patterns. Findings reveal that Webtoon fosters creativity through collaboration features and instant feedback, resulting in more dynamic original stories, while the transition to physical books enhances market visibility by 20-30% via digital promotion, although hindered by copyright complexities and production costs. The implications of this research underscore the importance of collaboration between traditional publishers and Webtoon to establish a hybrid literary ecosystem that sustainably supports Generation Z talent.

The development of digital technology has encouraged businesses to utilize social media as an effective marketing tool, particularly in the fashion industry targeting Generation Z. In addition to digital promotional strategies, product quality is also an important factor influencing consumers’ purchase decisions. This study aims to analyze the effect of social media marketing and product quality on purchase decisions among consumers of Jims Honey Kaliwungu Branch. This research employed an explanatory type with a quantitative approach. The sample consisted of 100 respondents selected using purposive sampling. Data were collected through questionnaires and analyzed using validity testing, reliability testing, multiple linear regression, t-test, F-test, and the coefficient of determination with the assistance of SPSS. The results show that social media marketing has a positive and significant effect on purchase decisions, with a t-value of 2.293 greater than the t-table value of 1.984 and a significance value below 0.05. Product quality also has a positive and significant effect on purchase decisions, with a t-value of 6.631 greater than the t-table value of 1.984 and a significance value below 0.05. Simultaneously, social media marketing and product quality have a significant effect on purchase decisions, with an F-value of 25.994 greater than the F-table value of 3.09 and a significance value below 0.05. The coefficient of determination of 0.349 indicates that both independent variables contribute 34.9% to purchase decisions. These findings confirm that product quality has a more dominant influence than social media marketing in encouraging purchase decisions among consumers of Jims Honey Kaliwungu Branch.

This study aims to describe the concept of Immersive Commerce based on Augmented Reality (AR) in increasing consumer confidence in E-Commerce transactions and to design a conceptual prototype design framework for an AR E-Commerce system with a clear technical flow. The research method uses a literature study through a comprehensive review of AR-based E-Commerce implementations and needs analysis from the perspective of consumer problems and business opportunities. The main problem identified is consumer hesitation in purchasing products online due to limited visualization that relies solely on product photos, causing fears about differences in shape, size, and quality of goods. The research results produced a conceptual framework that includes an integrated system architecture with a frontend layer (AR visualization engine), backend layer (product database and 3D asset management), and integration layer, as well as a systematic user flow design from the discovery to the decision phase. Based on simulations using literature data, the designed framework has the potential to increase customer engagement by up to 169%, conversion rates by up to 11 times, and reduce product return rates by up to 50%. The benefits of this research include digital dimensions through E-Commerce technology innovation, social dimensions by increasing consumer trust and reducing product fraud, and environmental dimensions through the potential reduction of product returns. This conceptual prototype provides a foundation for digital innovation, social trust building, and environmental sustainability through reduced product returns.

This study discusses the four pillars of digital transformation that are currently changing the business landscape in Indonesia, namely the digital ecosystem, digital twin technology, open innovation framework, and agile transformation. This study aims to identify and explain the key concepts underlying digital business innovation and its impact on business development in the modern era. The method used is a literature study with descriptive analysis of various primary and secondary sources related to digital innovation. The findings show that the application of these four pillars drives operational efficiency, increased cross-sector collaboration, accelerated product and service innovation, and increased business competitiveness. The implications of this study emphasize the importance of adopting a holistic digital strategy for companies to survive and thrive in an increasingly competitive and dynamic market. By understanding and implementing these pillars of digital transformation, Indonesian businesses can leverage the latest technologies to create innovative and sustainable business models.

The Fréchet distribution is one of the commonly used Extreme Value Distributions (EVDs) in statistical modeling and heavy-tailed data analysis, where it plays an important role in describing product lifetimes as well as climatic and financial phenomena. The estimation of its two parameters, namely the shape parameter and the scale parameter, is traditionally based on the Maximum Likelihood Estimation (MLE) method. However, maximizing the likelihood function for this distribution involves numerical difficulties, which necessitates the use of numerical optimization methods. In this study, we propose the use of the Aquila Optimizer (AO), a recent metaheuristic algorithm inspired by the hunting behavior of eagles, as an efficient numerical tool for maximizing the likelihood function of the Fréchet distribution. The objective function was formulated as the negative log-likelihood function (-LogL), and the Aquila Optimizer was employed to obtain the optimal estimates of the distribution parameters. Several simulation experiments with different sample sizes were conducted to compare the performance of the proposed method with a conventional approach represented by the Nelder–Mead method, using the Mean Squared Error (MSE) criterion. The simulation results demonstrated that the Aquila Optimizer outperformed the Nelder–Mead algorithm in many cases, although the superiority was slight. The results also showed that both algorithms were consistent, as their MSE values decreased with increasing sample size. In addition, a practical application was carried out using real data, and the results of the survival function estimation indicated a good fit.

Rice plants (Oryza Sativa L.) are the main staple food commodity in Indonesia, as most of the Indonesian population relies on rice as their primary food. One of the causes of low rice production in Indonesia is that farmers generally cultivate rice improperly, such as in land preparation or land selection. Land suitability in rice cultivation greatly affects crop productivity. A process that can support decisions regarding rice land suitability is the development of a Decision Support System (DSS) website using a combination of the Simple Additive Weighting (SAW) method and the Technique for Order Performance of Similarity to Ideal Solution (TOPSIS). This combination is performed by taking the average (µ) of the final results from the SAW and TOPSIS methods. The final scores of each method are calculated separately, and then the average (µ) of these two results is taken to obtain the final ranking of the alternatives. The data used to determine the suitability of rice land is based on five criteria: soil type, soil pH, rainfall, temperature, irrigation and water supply. The alternative data used in the study includes six alternatives: Sungai Kunjang, Sambutan, Samarinda Utara, Palaran, Loa Janan Ilir, and Samarinda Seberang. The aim of this research is to provide information on alternative solutions to farmers or farmer groups in determining rice land suitability. The results of the combination of the SAW and TOPSIS methods show that the alternative with the highest final score is Samarinda Utara (A3), with a final score of 0.7337. Meanwhile, the alternative with the lowest final score is Sambutan (A2), with a final score of 0.4402.

Stunting is one of the chronic nutritional problems that remains a major challenge in health development in Indonesia. This condition not only affects children’s physical growth but also influences cognitive development, productivity, and the quality of human resources in the future. The government has developed various policies to accelerate the reduction of stunting through specific and sensitive intervention approaches implemented in an integrated manner across sectors. Semarang, as one of the urban areas in Indonesia, has also implemented these policies through various health, nutrition, sanitation, and community empowerment programs. This study aims to analyze the policies of specific and sensitive interventions in addressing stunting in Semarang and to identify factors influencing the effectiveness of their implementation. This research uses a qualitative approach with a policy study method through document analysis, observation, and interviews with relevant stakeholders such as the health office, community health centers, and other local government agencies. Data analysis was conducted descriptively by examining program integration, inter-agency coordination, and community participation in policy implementation. The results show that the implementation of specific and sensitive intervention policies in Semarang has been carried out through various programs such as maternal and child nutrition services, improved access to sanitation, health education, and family empowerment. However, several challenges remain, including suboptimal cross-sector coordination, limited resources, and varying levels of public understanding regarding stunting prevention. Therefore, strengthening policy governance, improving synergy among institutions, and enhancing community participation are necessary to ensure that efforts to accelerate stunting reduction can be implemented more effectively and sustainably.

The retention of customers in the retail banking sector is a critical economic imperative; however, predictive modeling is frequently hindered by severe class imbalance and the “Black Box” nature of complex algorithms. This study proposes a Heterogeneous Stacking Ensemble framework integrating XGBoost, CatBoost, and Random Forest base learners with a Logistic Regression meta-learner to forecast customer attrition. To overcome the pervasive “Majority Class Bias,” we introduce a “Dual-Imbalance Defense” that synergizes the Synthetic Minority Over-sampling Technique (SMOTE) with algorithmic cost-sensitive penalization. Furthermore, moving beyond standard accuracy metrics, the framework mathematically derives a dynamic classification threshold to guarantee a strict 0.90 recall rate, actively optimizing the capture of at-risk capital. Model opacity is addressed through the integration of a SHapley Additive exPlanations (SHAP) TreeExplainer. This cooperative game theory approach provides localized, patient-level “Reason Codes” for regulatory compliance and reveals global systemic vulnerabilities, including non-linear drivers such as the “Product Paradox.” Achieving a 0.90 recall rate and an AUC of 0.8654, this framework provides a statistically robust and operationally transparent tool for targeted customer retention.

Vaname shrimp (Litopenaeus Vannamei) is one of Indonesia's fishery commodities with high economic value. Vaname shrimp production in Indonesia continues to increase. However, obstacles sometimes arise in cultivation activities, such as the emergence of shrimp diseases and poor water quality. High stocking density and shrimp feeding can cause a decline in water quality. In addition, pond water quality is influenced by pond location and the surrounding environment, such as agriculture, settlements, mangroves, and the sea. This causes ponds to have different water qualities. One of the diseases that often attacks shrimp farming is caused by the bacterium Vibrio sp. The abundance of Vibrio sp. bacteria is closely related to pond water quality and the environmental conditions around the pond. The methods used were TPC testing and multiple linear regression testing. Based on the results of the study, the abundance of Vibrio sp. bacteria in pond A was the highest at 8.3 x 102, and pond C had the lowest at 3.1 x 102. Water quality testing in three different ponds showed safe limits for cultivation, except for nitrite testing. Based on the simple linear regression test, the water quality parameters that significantly affect the abundance of Vibrio sp. bacteria are pH, temperature, and nitrite.  

Vaname shrimp is one of the export commodities with high economic value. Therefore, to meet increasing market demand, it is necessary to improve aquaculture productivity. However, the development of vaname shrimp farming in Indonesia faces several challenges, including the emergence of viral, fungal, and bacterial diseases (Astria et al., 2022). Vibrio sp. bacteria can cause bacterial infections and are opportunistic in nature. Vibrio sp. can attack shrimp at all stages and may lead to decreased production yields (Astria et al., 2022). Generally, farmers control bacterial diseases by adding antimicrobial compounds. However, bacterial disease control in vaname shrimp culture can also be carried out using hydrogen peroxide (Astria et al., 2022). This study examined the effect of different doses of hydrogen peroxide in suppressing Vibrio sp. bacteria using a Completely Randomized Design (CRD). The doses used were 7 ppm, 9 ppm, 11 ppm, 13 ppm, and 15 ppm, with five treatments and five replications. The results showed that the application of different doses of hydrogen peroxide had a significant effect based on the One Way ANOVA test (0.00 < 0.05). The lowest effectiveness was observed in treatment 1 (7 ppm), while the highest effectiveness was found in treatment 5 (15 ppm). Although hydrogen peroxide was able to reduce the number of Vibrio sp. bacterial colonies, the doses used in this study were not able to completely eliminate the colonies (0 cfu/ml).

The rapid development of the digital ecosystem has encouraged Micro, Small, and Medium Enterprises (MSMEs) in Ambon City to adopt online platform-based marketing strategies in response to changing consumer behavior that is increasingly digitally connected. This research focuses on MSME consumers in Ambon City who actively interact with local business products through digital platforms. The main problems identified include low digital marketing adoption by local MSME actors, limited empirical studies on Eastern Indonesia context, and the absence of an integrative analytical model that simultaneously tests three dimensions of digital marketing. This research aims to analyze the influence of digital marketing strategies encompassing social media marketing, paid digital advertising, and content marketing on consumer purchasing decisions of MSMEs in Ambon City. This study employs a quantitative approach with a survey design involving 100 respondents selected through purposive sampling, and data were analyzed using multiple regression analysis after passing classical assumption tests covering normality, multicollinearity, and heteroscedasticity. Results show that social media marketing has a significant effect with a regression coefficient of 0.387, paid digital advertising with a coefficient of 0.312, and content marketing with a coefficient of 0.274, all significant at the 0.05 level. Simultaneously, the three variables explain 67.1% of variation in consumer purchasing decisions with an F-count of 65.847. Social media marketing is proven as the most dominant dimension shaping consumer purchasing decisions of MSMEs in Ambon City. This research concludes that an integrated and contextual digital marketing strategy is a crucial instrument in driving MSME growth in Eastern Indonesia and recommends strengthening digital capacity of local business actors as a priority policy for regional MSME empowerment.Keywords: digital marketing; purchasing decision; MSMEs; social media; Ambon City

The economy of a country, including Indonesia, is a system that encompasses all production, distribution, and consumption activities occurring within the country. In the economy, problems often arise that can affect the welfare of society. The problem formulation in this study is: How is the regulation and supervision of both internal and external banks carried out to prevent customer personal data leakage in credit agreements? And how is the responsibility of BPR Karya Sari Sedana towards the leakage of customer debtor data? The research method used is empirical legal research. The conclusion in the study is the protection of customer data against personal data leakage by understanding the forms of supervision from both internal and external parties conducted by the banking institution and referring to the OJK regulations that have been established, in order to minimize the recurrence of similar incidents and allow the public to conduct transactions safely without worrying about their personal data. Leaked by irresponsible individuals. The responsibility carried out by the banking sector currently, namely the Financial Services Authority Regulation Number 22 of 2023 concerning Consumer and Community Protection in the Financial Services Sector, also regulates consumer protection in the financial services industry. Forms in policies related to regulations in the banking world ensure that the public does not worry about their personal data.

Asthma is a heterogeneous disease characterized by chronic inflammation of the airways and respiratory symptoms such as wheezing, shortness of breath, chest tightness, and cough, which vary over time in both frequency and severity. This condition is accompanied by limitations in expiratory airflow, which can be either reversible or persistent. In asthma patients, especially those treated in the Emergency Department (ED), a common nursing problem is ineffective airway clearance due to mucus accumulation and bronchospasm. One strategy to address this is the administration of warm drinking water, aimed at improving airway clearance. The design used in this final nursing scientific paper is a qualitative case study with an intervention of warm water intake. The subjects of this study consisted of 3 asthma patients in the ED, and the intervention was conducted from January 3-11, 2026, at the Emergency Department of Charitas Hospital Km.7 Palembang. Airway clearance was measured before and after the intervention, which involved giving 200 ml of warm water at 38ºC, without a control group. After the intervention, all three patients showed improved airway clearance, indicated by more effective coughing, decreased sputum production, reduced wheezing, improved breathing patterns, and improved respiratory rate. The implementation of this evidence-based practice (EBP) is expected to provide additional information regarding the use of nonpharmacological therapy, specifically the administration of warm drinking water, in asthma patients with ineffective airway clearance.

The Low Voltage Main Distribution Panel (LVMDP) is a critical component in industrial power distribution systems, functioning to regulate, control, and distribute electrical energy to various production equipment. During operation, LVMDP panels often operate under high electrical loads, which may lead to temperature increases in their components. Undetected temperature rise can result in performance degradation, equipment failure, and even fire hazards. Therefore, an effective monitoring method is required to detect the condition of electrical components at an early stage. This study aims to analyze the temperature difference (ΔT) of LVMDP components using the Infrared Thermography method as part of predictive maintenance. The research employs a quantitative descriptive approach with data collected through direct observation from July 1 to July 31 at PT. Dongjin Indonesia. The data consist of hotspot and ambient temperatures measured from several panel components, which are then analyzed to calculate the temperature difference (ΔT) as an indicator of component operating conditions. The results indicate that the highest temperature difference is 26.5 °C in the capacitor bank, while the lowest is 4 °C in other components. All ΔT values are below the threshold limit of 50 °C, indicating that the LVMDP components are in safe operating conditions and do not require corrective actions. Thus, Infrared Thermography is proven to be an effective method for early detection of component conditions and can enhance the reliability and safety of industrial power distribution systems.

Extreme changes in water quality, whether in the form of temperature fluctuations, exposure to detergents, pH decreases due to acetic acid, or changes in salinity, have the potential to cause complex physiological disorders in tilapia. The research aims to analyze the physiological responses of tilapia to changes in water quality in extreme environments given exposure to Temperature, Detergent, Acetic Acid, and Salinity. This research was conducted at the Wet Laboratory of Achmad Yani University, Banjarmasin. The physiological parameters observed included fish behavior, respiratory frequency measured by the number of openings and closings of the operculum per minute, gill condition, and mucus production on the body surface. Exposure to extreme environments in the form of high temperatures, detergents, acetic acid, and salinity caused physiological disorders in tilapia with varying levels of response. Exposure to acetic acid had the most rapid and severe impact, characterized by damage to scales and fins, impaired movement to the point of fish capsizing, and unstable breathing, while detergent and temperature triggered changes in external organs, heart rate, and behavior. Salinity treatment primarily affected osmoregulatory function as seen from increased respiratory frequency and heart rate. All treatments showed that extreme changes in water quality can cause significant physiological stress in tilapia.