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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 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.  

Automatic motorcycle spare part sales have increased along with the high use of automatic two-wheeled vehicles in the community. To support optimal sales strategies and stock management, customer purchasing pattern analysis is required. This study uses the FP-Growth algorithm to identify association patterns between automatic motorcycle spare part products that are frequently purchased together. FP-Growth was chosen because of its ability to efficiently find frequent itemsets without the need to generate candidate itemsets as in the Apriori algorithm. Transaction data is processed to form an FP-Tree which is then extracted to find relationships between items. The analysis results show combinations of products that frequently appear together, such as brake pads and engine oil, which can be used as a basis for compiling sales packages, product placement, and product recommendations. By implementing the FP-Growth algorithm, spare part stores or workshops can improve service and efficiency in sales management.

Posyandu (Integrated Health Post) is a public health facility that plays a vital role in providing health services for toddlers and pregnant women. However, data management and reporting often face challenges, such as limited access to information and errors in data recording. Therefore, this study aims to develop a Web-Based Posyandu Payolaumbu Service Information System using the CodeIgniter Framework to improve efficiency and accuracy in data management and reporting. In the development phase, a system requirements analysis and web-based application architecture design were conducted. The system implementation uses the CodeIgniter Framework as a framework to produce a faster, more efficient, and more reliable application. Proposed features include recording health data for toddlers and pregnant women, immunization schedules, weighing, and health reports. The results show that the Web-Based Posyandu Payolaumbu Service Information System can improve efficiency in recording and reporting health data. Users, including posyandu officers, midwives, and administrators, can easily access and manipulate data in real-time. Furthermore, this system helps improve service quality by providing more accurate and complete information on toddler health. In conclusion, the implementation of the Web-Based Posyandu Payolaumbu Service Information System using the CodeIgniter Framework provides significant benefits for data management and health services at Posyandu Payolaumbu. Suggestions for further development include maximizing system utilization, developing additional features, routine maintenance, and ongoing evaluation based on user feedback. With these steps, it is hoped that this system can contribute more effectively to improving the quality of health services at Posyandu and supporting comprehensive public health efforts.

This study conducts a Systematic Literature Review (SLR) of 20 empirical and conceptual articles published between 2020 and 2025 to examine the influence of city branding on tourism interest and consumer behavior, with a particular focus on the city of Balikpapan. The synthesis reveals that city branding significantly shapes tourist perceptions through key elements such as destination image, brand identity, brand personality, and digital communication. Destination image consistently emerges as the primary mediator linking city branding to visit intention, while experiential and emotional branding further strengthen tourists’ cognitive, affective, and behavioral responses. The findings also highlight the growing importance of digital media and e-WOM in amplifying city branding strategies, especially in the post-pandemic tourism landscape. Despite strong branding potential rooted in cleanliness, safety, and Balikpapan’s strategic role as a supporting city for the new capital (IKN), gaps remain in digital branding, differentiation, and identity storytelling. The review emphasizes the need for more integrated, innovative, and data-driven branding approaches to enhance the city’s competitiveness and attract greater tourism engagement.

This study aims to analyze the application of the franchising system on business performance in the beverage franchise business through a case study of Mitra Minuman Siap Saji. The approach used is qualitative with a case study design, with data collection techniques in the form of in-depth interviews, operational observations, and supporting documentation. The results show that the implementation of standardized Standard Operating Procedures (SOPs), franchisor support in the form of training, raw material supplies, and periodic monitoring contribute significantly to improving business stability, product quality consistency, and customer satisfaction. However, there are limitations in flexibility and several communication obstacles that have the potential to affect the effectiveness of the partnership. The relatively strict contract structure also impacts partners' perceptions of local innovation space, although it is generally still viewed as providing business security and business model clarity. These findings emphasize that a balance between franchisor control and partner autonomy, accompanied by open communication and fair contract design, is a key factor in creating sustainable business performance in a franchising system.

This study aims to map the intellectual structure and research trends in entrepreneurial innovation using bibliometric analysis based on Scopus data. A total of 891 documents published between 1972-2025 were analyzed through Bibliometrix and Biblioshiny, employing techniques such as bibliographic coupling, co-authorship, and thematic mapping. The results reveal four major clusters: (1) innovation theory and entrepreneurial development, (2) business model innovation and digital transformation, (3) regional innovation systems and policy frameworks, and (4) sustainability and green entrepreneurship. Emerging themes include artificial intelligence (AI), generative AI applications, and digital entrepreneurship education, indicating a shift toward multi-level and interdisciplinary integration. Influential documents and authors were identified, highlighting their role in shaping the knowledge base. The findings suggest that entrepreneurial innovation research is evolving toward digitalization, sustainability, and policy-driven ecosystems, offering opportunities for longitudinal and mixed-method studies. This study contributes by providing a comprehensive overview of the field, identifying gaps, and proposing future research directions to strengthen theoretical and practical advancements.

Primary Healthcare Facilities (Fasilitas Kesehatan Tingkat Pertama, FKTP) represent the first level of contact in the healthcare system and play a central role in infection prevention and control. Despite mandatory Infection Prevention and Control (IPC) training in Indonesia, evidence regarding its effectiveness in improving cognitive abilities among primary healthcare workers remains limited. This study aimed to evaluate the effectiveness of IPC training in enhancing the cognitive abilities of healthcare workers in FKTP. A quasi-experimental study with a one-group pretest–posttest design was conducted involving 91 healthcare workers who participated in IPC training across three cohorts in 2024. The training was delivered online through a Learning Management System and consisted of structured learning modules accompanied by a pre-test and a final quiz. Cognitive improvement was assessed using paired samples t-tests, while the magnitude of training impact was evaluated using Cohen’s dz effect size. The results showed statistically significant improvements in cognitive scores across all cohorts (p < 0.001), with mean score increases ranging from 16.10 to 23.35 points. Effect size analysis revealed large to very large effects, with an overall Cohen’s dz of 1.19, indicating substantial and practically meaningful cognitive gains. In conclusion, IPC training was effective in improving cognitive competence among FKTP healthcare workers. These results reinforce the value of well-structured training programs as an essential component of efforts to strengthen infection prevention capacity in primary healthcare settings.

Advancements in modern technology have reshaped people’s lifestyles, including how individuals carry out their daily activities. These changes have influenced individuals to make less realistic decisions in an effort to align themselves with their desired lifestyle. This study aims to examine whether college students with certain lifestyle tendencies are more likely to engage in impulsive buying when shopping online. The study involved 392 college students residing in Surabaya, East Java, selected through a random sampling technique. Data were collected using a Google Form–based questionnaire containing measurement instruments developed by the researcher: (1) the Impulsive Buying Scale (15 items; α = 0.858) and (2) the Lifestyle Scale (22 items; α = 0.898). Multiple linear regression was used to analyze the data.The findings reveal a significant positive relationship between lifestyle and impulsive buying. The strongeran individual’s consumerist lifestyle tendency, the more likely they are to make impulsive purchases.  

This study aims to analyze hematocrit values ​​using a micro method with capillary blood samples in pregnant women with anemia at the Sidodadi Kisaran Barat Community Health Center. This study is a descriptive study with a cross-sectional approach involving 15 pregnant women as respondents. Data collection was carried out through hematocrit laboratory examinations and data collection of respondent characteristics. The results showed that 60% of respondents had hematocrit levels below normal values, while 40% of respondents had hematocrit levels within normal limits. Low hematocrit levels in pregnant women are influenced by several factors, including age, education level, employment status, and level of knowledge about anemia during pregnancy. This condition has the potential to increase the risk of pregnancy complications if not optimally managed. Therefore, it is recommended that health workers continue to increase educational efforts regarding anemia prevention, the importance of regular pregnancy check-ups, and encourage pregnant women to maintain a balanced nutritional consumption pattern and adequate iron intake to support maternal and fetal health.

Overburden stripping operations in the coal mining industry require optimal performance of loading and hauling equipment to achieve production efficiency. This study aims to evaluate the performance of loading and hauling equipment using the Match Factor method in overburden stripping operations at PT Bumi Artlantis Raya. The results indicate that the equipment combination achieved a Match Factor of 0.85, reflecting moderate compatibility with a potential efficiency improvement of 15%. The actual productivity of Excavator 4002 reached 137.02 bcm/hour (91.35% of the 150 bcm/hour target), while Excavator 4004 exceeded the target with a productivity of 195.73 bcm/hour (130.49% of the target). In contrast, dump truck productivity remained relatively low (Mercedes dump truck: 35.58 bcm/hour; Hino dump truck: 35.40 bcm/hour), primarily due to waiting time during loading and disposal activities. Statistical analysis reveals a strong negative correlation between cycle time and productivity (R² = 0.9929). The optimal cycle time to achieve a Match Factor of 0.80 is 969 seconds, corresponding to an optimal hauling distance of 5.38–6.725 km. Although mechanical availability and physical availability were high (94–100%), the use of availability and effective utilization were relatively low due to an imbalance between loading and hauling equipment. This study concludes that improving equipment coordination, increasing bucket fill factor, enhancing haul road conditions, and implementing preventive maintenance are essential to achieving more optimal operational efficiency in overburden stripping activities.

The problem faced is the decline in the performance of a 650 liter/minute centrifugal pump due to wear on components, especially the impeller, rolling bearings, and mechanical seals in supplying process water and clean water in industrial production systems. The planning objective is to obtain a maintenance schedule for a 650 liter/minute centrifugal pump for the operational period of 2026 and the ratio between maintenance costs and profits generated by the machine. The maintenance planning method includes collecting maintenance data from previous maintenance periods, reviewing centrifugal pump specifications, applying the inspection, replace, repair, and overhaul (IRRO) approach, estimating the age and price of components that are expected to be damaged, estimating the cost and duration of dismantling and installing components that have been repaired in accordance with the provisions of the requirements for usable components or replacement parts, scheduling maintenance and repairs, estimating maintenance and repair costs for the 2026 period, and determining the ratio of maintenance costs to profits. The planning results are in the form of a maintenance schedule for the 2026 period worth IDR 4,290,000,-, a maintenance cost to profit ratio of 7.44% and the implications indicate that the machine is still suitable for use and prospective for operations in the next few years.  

The implementation of industrial engineering technologies, such as automation, the Internet of Things (IoT), artificial intelligence (AI), and lean manufacturing, has significantly transformed human resource (HR) capabilities in the production sector, particularly in response to the Industry 4.0 paradigm. This study aims to examine the relatively low level of technology adoption in Indonesia, estimated at only 6–20% of manufacturing companies, and its impact on the development of HR competencies. The analysis focuses on changes in technical skill requirements, including digital literacy, data analytics, and technology-based decision-making, as well as the shift in job roles from manual tasks to more strategic functions. This research employs a qualitative descriptive approach grounded in sociotechnical systems theory and the strategic alignment model. The findings indicate that existing skill gaps can be addressed through continuous upskilling and reskilling programs, supported by strengthened triple helix collaboration among government, industry, and educational institutions. The implementation of these strategies has been shown to increase productivity by approximately 30–72% and enhance the competitiveness of the national production sector in the global industrial landscape.  

Waste from used Polypropylene (PP) and High Impact Polystyrene (HIPS) plastic is problematic in its management. The purpose of this research is to obtain the fatigue life of a mixture of used PP and HIPS plastics in its pure plastic. The research method is through the stages of mixing pure PP and 50% volume of used PP, pure HIPS and 50% volume of used HIPS, injection molding of R.R. Moore standard fatigue test specimens for pure PP, pure HIPS, pure PP + used PP, and pure HIPS + used HIPS, checking the straightness and smoothness of the molded specimen surface, fatigue testing with increasing serial loads, analysis of the bending stress curve (S) against fatigue life (N). The results showed that mixing used PP and used HIPS in pure plastic affected the fatigue life at the test speed (n)=2100 rpm for recycled PP was 9.84% shorter than pure PP, and at n=1600 rpm for recycled PP it was 9.32% shorter than pure PP, while at n=2100 rpm for recycled HIPS it was 4.45% shorter than pure HIPS, and at n=1600 rpm for recycled HIPS is 4.77% shorter than pure HIPS, while the fatigue life of pure PP is 1627704 cycles and the fatigue life of pure HIPS is 1291636 cycles or the fatigue life of pure HIPS is 20.65% shorter than pure PP, the implication of which is that the addition of used PP and used HIPS reduces the fatigue life to 9.84% for PP and 4.45% for HIPS.

Currently, patients experiencing early symptoms of skin disease caused by the exanthema virus are unable to immediately consult a dermatologist due to the high cost and limited time available for specialists in hospitals. Therefore, the author needs to develop an expert system application that can address this issue. Through this application, users can consult with the system, much like an expert, to diagnose their symptoms and find solutions to their problems. This expert system is designed to provide answers based on whether the symptoms are correct or not, or to provide several recommended answer choices based on the symptoms. To diagnose skin disease caused by the exanthema virus, the author used the Case-Based Reasoning method. The CBR method is a weighting technique that compares new cases with previous cases. The diagnosis is based on data provided by the patient and expert, which is then analyzed using case-based reasoning and stored as a knowledge database in the expert system. Therefore, this expert system can help identify solutions for problems experienced by patients suffering from skin disease caused by the Exanthema Virus.

Tulungagung Regency has the potential for culinary tourism that can be developed, one of which is traditional culinary. Although the Tulungagung Regency Government has presented a "Halal Culinary Area" and a "Pinka Culinary Tourism Area", the area has not fully provided an interesting visual and functional experience. Therefore, it is necessary to design a space that facilitates traditional culinary MSMEs as well as an educational and recreational place. This design carries the theme of contemporary tropical architecture by considering local climatic conditions, through the application of wide openings, cross ventilation, wide trellises, and the use of natural materials, as well as expressive styles with the shape of a rooster roof and the basic shape of an elliptical building as a symbol of adaptation to climate change and the economy in the business environment. The facilities in this design include traditional restaurants, educational bales, wiyata offices, prayer rooms, playgrounds and other supporting facilities that can attract the interest of the community and introduce traditional Tulungagung culinary.

The development of sustainable tourism facilities is one of the important efforts in increasing the attractiveness of destinations while preserving the environment. This study aims to analyze the implementation of ecological concepts in the development of glamping facilities in the Pearl Beach tourist area. The method used is a descriptive qualitative approach, with data collection through field observations, interviews with managers and tourists, and literature studies related to ecotourism principles and sustainable design. The results of the study show that the application of ecological concepts in glamping facilities in Mutiara Beach includes the use of environmentally friendly materials, integrated waste management, the application of energy efficiency, and designs that integrate the natural landscape without damaging the coastal ecosystem. The application of this concept not only improves the comfort and experience of tourists, but also contributes to increasing environmental awareness and strengthening the positive image of tourist destinations. In addition, this ecologically-conceptual glamping development model is expected to be a reference for the development of sustainable tourism facilities in other coastal areas, which prioritizes nature preservation and the welfare of local communities.

The rapid development of digital streaming platforms such as Netflix has generated a large volume of content data with diverse characteristics, thereby requiring effective analytical methods to understand emerging patterns and trends. This study aims to classify Netflix content into two main categories, namely movies and television shows, and to analyze genre trends and content characteristics using a data mining approach with the Naive Bayes algorithm. The dataset used in this study is the Netflix Shows dataset, consisting of 8,809 content entries, with the primary features analyzed including genre, rating, and country of production. The research process begins with data exploration and preprocessing stages, including data cleaning, handling missing values, and transforming categorical features to enable effective model construction. Subsequently, the dataset is divided into training and testing sets to objectively and systematically build and evaluate the Naive Bayes classification model. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics to assess the model’s ability to accurately distinguish between Netflix content types. The experimental results demonstrate that the Naive Bayes algorithm is able to classify Netflix content into Movie and TV Show categories with accuracy, precision, recall, and F1-score values of 100%, respectively. The confusion matrix indicates that no misclassification occurred, suggesting that genre, rating, and country of production features provide a very clear separation between content classes. These findings indicate that the Naive Bayes algorithm can achieve exceptionally high classification performance with optimal evaluation results. The results further reveal distinct differences in characteristics between movies and television shows based on genre and production attributes. Therefore, this study is expected to contribute to the development of content recommendation systems and strategic content management within the streaming industry.

The rapid development of the sea transportation industry produces a massive and complex volume of transaction data, requiring strategic management to support managerial decision-making. This research aims to implement the Executive Information System on SeaPass in order to evaluate the performance of ship ticket sales. The research method uses data visualization with a two-level drill-down mechanism, which allows the presentation of information hierarchically from general summaries to specific details. The methodological stages include needs analysis, user interface (UI) design using Figma, front-end implementation with HTML, CSS, and JavaScript, database integration, and system testing through Black Box Testing. The results showed that the SIE implementation successfully integrated operational data, including schedules, ships, and manifests, into an interactive dashboard. The two-level drill-down feature provides the ability for executives to identify operational anomalies and market fluctuations in real-time. In conclusion, the system significantly enhances executive data analysis capabilities, transforming complex transaction data into accurate strategic information, thereby supporting more precise business decision-making and adaptive to the dynamics of the marine transportation market.

Diabetes Mellitus is a chronic disease that requires early detection to prevent serious complications. This study aims to implement the Artificial Neural Network (ANN) algorithm with the Backpropagation method to predict the risk of diabetes. The dataset used is the Pima Indians Diabetes Dataset, consisting of 768 medical records with 8 feature attributes. This study employs the Multi-Layer Perceptron method with an architecture of 8 input neurons, two hidden layers, and 1 output neuron. Model evaluation is conducted using a Confusion Matrix to measure accuracy levels. The test results show that the model is capable of predicting diabetes diagnosis with an accuracy rate of 76.62%. Based on these results, it can be concluded that the Backpropagation algorithm is effective as an alternative method for early detection of diabetes, although further development is needed to improve the model's sensitivity to positive cases.