The songkok industry in Lamongan has quite a large economic potential, but still faces various challenges in increasing competitiveness, especially in facing increasingly tight market competition. Some of the main obstacles found are lack of innovation, limited access to wider markets, and low utilization of technology in production and marketing. This study aims to explore strategies to increase the competitiveness of local songkok products through a creative economic empowerment program using the Chambers Theory perspective. The research method used is a qualitative approach with data collection techniques in the form of in-depth interviews, field observations, and literature studies. Data analysis was carried out descriptively qualitatively with three main stages, namely data reduction, data presentation, and drawing conclusions. The results of the study indicate that the creative economic empowerment program plays a significant role in improving craftsmen's skills, encouraging innovation in design, and expanding the marketing reach of songkok products. By applying analysis based on Chambers Theory, this empowerment contributes to increasing power within (craftsmen's confidence and awareness), power to (individual capacity to innovate and develop businesses), power with (collaboration between craftsmen in the community), and power over (ability to face competition and external constraints). Based on these results, it can be concluded that empowering the creative economy is an effective strategy in increasing the competitiveness of Lamongan songkok products. Therefore, close cooperation is needed between the government, the artisan community, and the private sector in order to create a sustainable creative industry environment.
 
 

In educational research, identifying variables and determining data sources are essential components in designing a systematic and accurate study. Research variables refer to the elements that are observed and measured within a study. These variables can include student achievement, motivation, teaching strategies, or learning environment conditions. Generally, variables are categorized as independent, dependent, control, or moderator variables. The independent variable is the influencing factor, while the dependent variable is the outcome. Control variables are held constant to avoid interference, and moderator variables affect the strength or direction of the relationship. The process of identifying variables begins with formulating the research problem and objectives. By reviewing theoretical frameworks and previous studies, researchers can focus their investigation on measurable aspects. For instance, in a study about the effectiveness of online learning on student performance, the independent variable is online learning, while the dependent variable is student achievement. Beyond identifying variables, researchers must also determine the appropriate types of data sources. Data sources are generally divided into two categories: primary and secondary. Primary data are collected directly from research subjects, such as through interviews, observations, or questionnaires. Secondary data, on the other hand, are obtained from existing sources like documents, books, journals, or official reports. The choice of data source must align with the research approach—quantitative, qualitative, or mixed methods. In quantitative research, primary data such as test scores or survey responses are used to measure variables numerically. In qualitative research, in-depth interviews and observations are commonly used to explore meanings and context. Using both types of data in combination can enhance data validity through triangulation. Ultimately, researchers must ensure the validity and reliability of their data, while also maintaining ethical standards in data collection and reporting. By understanding how to identify variables and select appropriate data sources, educational research can yield credible findings that contribute meaningfully to educational theory and practice.

This study aims to analyze the marketing strategy implemented by Bika Ambon Nasywa, a traditional cake producer located in Sunggal Deli Serdang, Medan City, North Sumatra. A qualitative descriptive approach was used in this study, with data collection techniques through in-depth interviews, observations, and documentation analysis. Data analysis was carried out using the SWOT (Strengths, Weaknesses, Opportunities, Threats) framework to identify internal and external factors that influence the marketing of Bika Ambon Nasywa products. The results of the study indicate that the main strength of the product lies in its distinctive taste and the quality of the raw materials used, while weaknesses include limited product and packaging innovation. Opportunities that can be utilized include increasing consumer interest in traditional culinary and the development of information technology for digital marketing. Threats faced include competition with similar products and changes in consumer preferences. Based on this analysis, it is recommended that Bika Ambon Nasywa increase product innovation, improve packaging design, and utilize digital platforms such as social media for promotion in order to expand market share and increase sales.

Patient interest in herbal inpatient services at RSU Holistic Purwakarta has decreased compared to conventional services, despite the hospital's strengths in integrative approaches and competent medical professionals in the herbal sector. The low level of public literacy, lack of effective promotion, as well as the absence of a clear service package are the main challenges affecting patients' decision-making to choose herbal services. Therefore, this study aims to analyze the factors that influence patients' purchase intention towards herbal inpatient services and formulate appropriate marketing strategies to increase patient interest. To formulate the proposed strategy, the researcher conducted an internal and external analysis. The internal analysis included Marketing Mix (7P) evaluation and STP (Segmenting, Targeting, Positioning) analysis. External analysis includes consumer analysis, PESTLE, and competitor analysis. This research uses a mixed method, with a quantitative approach as the main method and qualitative as a complement. Quantitative data was collected through distributing questionnaires to 220 respondents who fit the population criteria. The questionnaire was designed based on the constructs of the 7P Marketing Mix theory and the Theory of Planned Behavior (TPB), which includes attitude, subjective norms, and perceived behavioral control. Data were analyzed using the Structural Equation Modeling-Partial Least Squares (SEM-PLS) method to test the relationship between research variables. The results showed that product, price, promotion, people, and process variables had a significant effect on purchase intention, while physical evidence had no significant effect. In addition, TPB variables consisting of attitude, subjective norms, and perceived behavioral control also show a significant influence on patient intention. Based on these results, a marketing strategy was formulated using the TOWS Matrix approach classified in 7P elements and designed into three main solution pillars: (1) Public Awareness Strategy that includes public education through social media and community seminars, (2) Strategy to Strengthen Service Quality and Promotion Integration that focuses on strengthening service quality, developing clear service packages, and integrating cross-channel promotions, and (3) Personalized Service Development Strategy that tailors services to patients' needs and preferences. This strategy is expected to increase public awareness, form positive attitudes, and encourage patient decisions to use herbal inpatient services at Holistic Purwakarta Hospital.

 Penglipuran village is a traditional village and one of the villages in Bangli Regency, Bali. Penglipuran village is one of the villages that has its own uniqueness as a tourist village that is not owned by other villages. This research focuses on the traditional village of Penglipuran using qualitative descriptive analysis method, where the data is taken from research objects consisting of local residents. The result of the study show that the uniqueness of Penglipuran Village covers several aspects, namely Penglipuran Village as an economic driver and on the other hand, the achievement of equal distribution of basic education in Penglipuran Village.

Coronary heart disease is a disease in which the occurrence of blockages in the blood vessels in the heart. Coronary heart disease is a fatal disease, it is better to get as much information about this disease as possible. Data Mining can classify whether a person has heart disease or not based on symptoms. Data mining builds a model that can predict whether a person has heart disease or not. How well a model performs classification can be determined from its accuracy value, but this accuracy value can still be improved. Increasing the accuracy value can be done by performing Feature Selection. The research object used in this research is a dataset about coronary heart disease obtained from the Kaggle website. The classification method used in this modeling is the Random Forest algorithm to classify whether a person has coronary heart disease or not. The Random Forest Algorithm is a classification algorithm consisting of Decision Trees for classifying. The Random Forest algorithm is used because it has been proven to produce good accuracy in several previous studies. The Feature Selection method used in this modeling is the Chi-Square hypothesis test to determine whether there is an effect of each independent variable on the dependent variable. This research compared the value of modeling accuracy without using Feature Selection with modeling using Feature Selection. The result of this study is that the model without Chi-Square Feature Selection produced an accuracy value of 96,05% and the model with Chi-Square Feature Selection produced an accuracy value of 97,33%.

Sudoku is a digital game that is included in the type of logic-based puzzle game where the goal is to fill in the puzzle with random numbers. Therefore, in this research it is proposed to use Artificial Intelligence which contains the Depth First Search Algorithm to track the number of possible solutions that lead to only one so that it becomes efficient. This game has different levels of difficulty such as easy, medium and difficult. The time and complexity of execution will vary depending on the difficulty so it is proposed to use Android Studio software. The experimental results prove that there is an increase in playing the Sudoku game quickly and accurately by applying the Depth First Search Algorithm method. This is proven by the ability to complete this game using the Depth First Search Algorithm using the Android Studio programming language. The average time at the easy level is 11:04 minutes, at the normal level is 10:52 minutes, at the hard level is 25:46 minutes, and at the extreme level is 38 minutes.

Perkembangan bisnis busana muslimah yang semakin pesat membuat tingkat persaingan juga semakin ketat. Pemanfaatan teknologi internet berupa e-commerce, Shopee salah satunya, sangat membantu dalam memasarkan dan mempromosikan produk karena lebih efektif dan efisien menjangkau konsumen. Konsumen seolah diperebutkan dengan penawaran-penawaran seller melalui produk dengan kualitas yang sangat beragam pula. Tujuan penelitian ini adalah untuk mengetahui pengaruh harga, kualitas produk, dan promosi terhadap minat beli konsumen pada butikbintan di e-commerce Shopee (shopee.co.id/butikbintan). Dalam penelitian ini metode pengambilan sampel dengan menggunakan rumus Lemeshow dengan jumlah sampel (n) = 105 orang. Metode pengumpulan data dilakukan dengan tahapan observasi, dan kuesioner, yang diukur dengan Skala Likert. Metode penelitian menggunakan metode regresi linear berganda, dengan analisis instrumen penelitian uji validitas, uji reliabilitas, uji normalitas, uji multikolinearitas, uji heteroskedastisitas, uji t, uji F dan uji koefisien determinasi. Hasil penelitian menemukan bahwa harga berpengaruh positif signifikan terhadap minat beli konsumen, kualitas produk secara parsial tidak berpengaruh positif dan signifikan terhadap minat beli konsumen, promosi secara parsial tidak  berpengaruh positif dan signifikan terhadap minat beli konsumen, dan variabel harga, kualitas produk, dan promosi secara simultan berpengaruh terhadap minat beli  konsumen pada butikbintan di e-commerce shopee                                        ( shopee.co.id/butikbintan ).

Hypertension, a non-communicable disease often called the "silent killer," affects 30.8% of Indonesians aged 18 and older, with 34% of those over 60 undiagnosed (2023 Indonesian Health Survey). The high prevalence among the elderly is frequently associated with inadequate self-care activities. This study aims to find the relationship between hypertension knowledge and self-care activities among the elderly with hypertension at a Public Health Center Depok III in Sleman. A descriptive-quantitative approach with a cross-sectional design was used. 80 elderly with hypertension were selected using purposive sampling. Inclusion criteria were being over 60 years old, compos mentis, and able to communicate verbally; exclusion criteria included sudden illness or urgent commitments preventing questionnaire completion. Hypertension knowledge was measured with the Hypertension Knowledge Level Scale (HK-LS) instrument, and self-care activity was assessed using the Hypertension Self-Care Activity Level Effects (H-SCALE) instrument. The Gamma test showed a significant, positive, and very strong relationship between the knowledge level and self-care activity among the elderly with hypertension, with a p= 0.043 (r =0.875). The results indicated that there is a significant, positive, and very strong relationship between the knowledge level and self-care activity among the elderly with hypertension at a Public Health Center Depok III in Sleman. Based on the findings of this study, it is recommended that the health center improve its educational program, particularly concerning a low-salt diet, physical activity, and weight management.

Understanding customer purchasing behavior is essential for predicting customer loyalty, which directly impacts a company's long-term success. This research aims to determine the effect of chi-square and information gain feature selection in optimizing customer loyalty classification performance, compared to pure kNN. Using a public customer purchasing behavior dataset from Kaggle, containing 10,000 data, 12 attributes with loyalty_status as the label (Gold, Regular, Silver). Evaluating performance by accuracy, kappa, classification error, recall, precision, and RMSE. The highest accuracy 91.99% was obtained by kNN k=3 with information gain, kappa 0.844, precision 95.44%, recall 86.30%, with the lowest classification error 8.01% and the second lowest RMSE 0.245, after kNN k=3 with chi-square. Results show that feature selection has a positive impact on classification, increasing accuracy and reducing errors, with the combination of the kNN k=3 method and information gain proving successful in obtaining high accuracy in classifying customer loyalty.