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Hypertension is a non-communicable disease often referred to as a silent killer because it generally does not present noticeable symptoms. Several risk factors contribute to the development of hypertension, including high body mass index (BMI) and low levels of physical activity. However, data regarding the association between BMI, physical activity, and hypertension at Pakuan Baru Public Health Center, Jambi City, remain limited. Therefore, this study aimed to determine the relationship between body mass index and physical activity with hypertension among adults at Pakuan Baru Public Health Center, Jambi City. This study employed a quantitative approach with a cross-sectional design. The research was conducted at Pakuan Baru Public Health Center, Jambi City, from November 19 to December 6, 2025. The study population consisted of all adult patients with hypertension at Pakuan Baru Public Health Center, totaling 2,797 individuals. A sample of 93 respondents was selected using an accidental sampling technique. Data were collected using observation sheets through measurements of height and weight to calculate BMI, as well as the Global Physical Activity Questionnaire (GPAQ). Data analysis was performed using univariate and bivariate analyses with the chi-square statistical test. The univariate analysis showed that 27 respondents (29.0%) were classified as severely obese, 42 respondents (45.2%) had a low level of physical activity, and 28 respondents (30.1%) were categorized as having stage 2 hypertension at Pakuan Baru Public Health Center, Jambi City. The bivariate analysis revealed a significant relationship between body mass index and physical activity with blood pressure among patients with hypertension (p = 0.000). It is expected that healthcare providers at Pakuan Baru Public Health Center will continue to provide education regarding the importance of controlling body mass index and engaging in regular physical activity, as these factors contribute to increased blood pressure among patients with hypertension.

The determination of scholarship recipients is a very important process in supporting students’ educational success, particularly in providing fair opportunities for high-achieving students who require financial assistance. However, in practice, this process often faces various challenges, such as assessor subjectivity and uncertainty in evaluating the applied criteria. Therefore, a decision support system is needed to assist decision-making in an objective and measurable manner. This study aims to implement the Fuzzy Tsukamoto method as a decision support system for determining scholarship eligibility. The criteria used in this study include Grade Point Average (GPA) as an indicator of academic achievement and parents’ income as an indicator of students’ economic conditions. The Fuzzy Tsukamoto method was selected because it is capable of producing crisp output values based on predefined fuzzy rules. Student data were processed through several stages, namely fuzzification to transform input data into fuzzy values, inference using the minimum operator, and defuzzification using the weighted average method. The results of the study indicate that the application of the Fuzzy Tsukamoto method is able to generate more objective, consistent, and measurable decisions. Based on the calculation results, a scholarship eligibility score of 63.9 was obtained, which falls into the eligible category. Thus, the Fuzzy Tsukamoto method can be considered an effective alternative to support fair, systematic, and transparent decision-making in determining scholarship recipients.

Generation Z students face increasingly complex academic challenges within the competitive higher education ecosystem. The pressure to maintain academic performance, social expectations, and intense digital exposure contribute to rising mental health issues such as stress, anxiety, and burnout. This study aims to analyze the relationship between academic pressure and the psychological condition of Gen Z students using a quantitative-descriptive approach through an online survey. The research instrument adapted the Academic Stress Scale (ASS) and the Depression Anxiety Stress Scale (DASS-21). The results show that the majority of respondents experience significant academic pressure, which correlates positively with symptoms of stress and anxiety. These findings highlight the importance of educational system reform that not only emphasizes academic performance but also supports students' mental well-being. Higher education institutions are expected to provide safe spaces, reliable counseling services, and more empathetic teaching approaches in response to the mental health issues facing this generation.

The development of Artificial Intelligence (AI) technology has provided new opportunities to enhance the quality of learning, particularly in elementary science education. One form of AI utilization is chatbots, which function as interactive learning media capable of encouraging students’ active participation. In science learning, questioning behavior is an important indicator of students’ cognitive engagement; however, many elementary school students tend to be passive in asking questions. This study aimed to examine the effect of using AI chatbots in science learning on students’ questioning behavior in Grade V of SDN Plalangan 03 Gunungpati, Semarang City. This study employed a quantitative approach with a quasi-experimental design. Data were collected through observation, questionnaires, and documentation. The data were analyzed to identify changes in students’ questioning behavior before and after the implementation of AI chatbots in science learning. The results indicated that the use of AI chatbots improved students’ questioning behavior in terms of frequency, confidence, and activeness in asking questions. AI chatbots provided a comfortable and flexible interaction space for students, which helped reduce psychological barriers in questioning. It can be concluded that the use of AI chatbots has a positive effect on students’ questioning behavior in elementary school science learning.

The coffee industry in Indonesia is growing rapidly and encouraging coffee shops, including MSMEs, to strengthen their branding strategies through digital media. This study aims to design and evaluate Instagram social media content to increase brand awareness of Kamala Kopi, a local coffee shop in Gunungpati, Semarang. The method used is the Multimedia Development Life Cycle (MDLC) with stages of concept, design, material collection, assembly, testing, and distribution. The content produced consists of music videos, promotional posters, and menu visuals, which were then tested through internal and external validation, as well as a questionnaire administered to 68 respondents. The research results showed a positive and significant influence of Instagram content on brand awareness of 1.007 with a coefficient of determination of 90.4%. These findings confirm that content on Instagram social media plays an important role in strengthening the visibility of SME brands and can be an effective strategy to increase brand awareness.

Penelitian ini menganalisis kekuatan pondasi tiang pancang pada proyek pembangunan Apartemen Arjuna Bima di Kabupaten Sleman. Penyidikan tanah menggunakan boring pada titik B2 menunjukkan bahwa lapisan tanah keras maksimum berada pada kedalaman 25 meter, sementara hasil bor tangan mengidentifikasi tanah berupa pasir sedang berwarna coklat keabu-abuan. Tiang pancang dipilih karena kemampuannya untuk memadatkan tanah pasir sedang selama proses pemancangan. Penelitian ini menggunakan metode kuantitatif dengan teknik pengumpulan data sekunder melalui studi literatur dan dokumentasi. Semua perhitungan dilakukan menggunakan metode Meyerhof, sedangkan analisis pembebanan struktur dilakukan dengan perangkat lunak ETABS v22. Analisis ini mencakup perhitungan kapasitas dukung aksial, kapasitas dukung lateral, dan penurunan pondasi akibat beban struktur atas. Hasil analisis menunjukkan bahwa beban aksial (P) sebesar 710,77 ton. Kapasitas dukung aksial kelompok tiang pancang (Qg) dengan diameter 80 cm, 60 cm, dan 42,9 cm pada kedalaman 20 m berturut-turut adalah 2.125,87 ton; 1.347,68 ton; dan 710,51 ton. Kapasitas dukung lateral (Hg) untuk ukuran tiang yang sama berturut-turut adalah 1.169,9 ton; 877,4 ton; dan 627,4 ton. Penurunan pondasi kelompok tiang (Sg) masing-masing adalah 2,46 cm; 2,1 cm; dan 2,03 cm. Berdasarkan hasil analisis, pondasi tiang pancang dengan diameter 80 cm dan 60 cm memenuhi syarat keamanan baik dari segi kapasitas dukung aksial maupun lateral, serta penurunan pondasi. Namun, untuk tiang pancang dengan diameter 42,9 cm, kapasitas dukung aksial tidak memenuhi syarat keamanan (Qg < P), sehingga tidak direkomendasikan untuk digunakan.

Clean water distribution in the Community-Based Drinking Water Supply and Sanitation Program (PAMSIMAS) in Kuwasen Lama Village, Gunungpati District, Semarang City, faces the challenge of unequal supply between highland and lowland areas. The main factors that affect these conditions include differences in topography, suboptimal piping network design, and unbalanced water pressure, especially during peak hours. This research proposes a solution based on Internet of Things (IoT) technology using the ESP32 module as a control center, which is integrated with the Blynk application for real-time monitoring and control of the system. The system is equipped with a water flow sensor, water level sensor, motorized valve, and booster pump to increase water pressure in high elevation areas. Two design schemes were tested, namely flow regulation using a motorized valve, and a combination of a motorized valve with a booster pump. The results of the simulation and implementation showed an increase in water pressure stability, equitable distribution, and a decrease in the frequency of supply disruptions. The system also allows for live monitoring of network conditions, facilitates technical decision-making, and improves operational efficiency. With an adaptive and community participation-based approach, this solution has the potential to become a model for PAMSIMAS clean water distribution management that is efficient, sustainable, and responsive to geographical challenges, while strengthening the resilience of clean water services in rural areas.

In an organization, human resources are the main asset that plays an important role in achieving organizational goals. One of the factors that affect the effectiveness of employees' work is organizational culture. Organizational culture reflects the values, norms, and habits that are embraced by the same and serves as a code of behavior for all members of the organization. A strong and positive culture can create a conducive work environment, improve work morale, as well as encouraging employee loyalty and productivity. Conversely, a culture that is not aligned with organizational goals can lower motivation and negatively impact performance. Therefore, it is important to understand the extent to which organizational culture affects employee performance. In general, this study aims to analyze the extent to which organizational work culture affects employee performance in the Wiringpalennae Village Office, Tempe District, Wajo Regency The purpose of this study is to assess how good the Organizational Culture is to Employee Performance in the Wiringpalennae Village Office, Tempe District, Wajo Regency, as well as to measure the influence of Organizational Culture on Employee Performance in the Wiringpalennae Village Office, Tempe District, Wajo Regency. The research method applied is quantitative associative. The research sample involved 19 respondents. Data was collected through questionnaires or questionnaires and data analysis was carried out using quantitative descriptive analysis techniques, associative analysis, and simple linear regression analysis. The findings in the study stated that Organizational Culture has a positive and significant influence on Employee Performance at the Wiringpalennae Village Office, Tempe District, Wajo Regency. The analysis also shows that the Organizational Culture at the Wiringpalennae Village Office, Tempe District, Wajo Regency is in the good category, and the Performance of Employees at the Wiringpalennae Village Office, Tempe District, Wajo Regency is in the very good category.

The issue of determining the number of students' graduation times is one of the important indicators in transmitting the quality and effectiveness of the higher education process in universities. The rate of on-time graduation not only impacts accredited institutions, but also becomes a concern for campus management in designing learning strategies and academic guidance. This study aims to apply and compare two classification algorithms in data mining, namely C4.5 and K-Nearest Neighbor KNN, in predicting the accuracy of students' graduation times. Predictions are made based on academic attributes such as Grade Point Average GPA, number of credits that have been achieved, and Semester Grade Point Average IPS as input variables. The method used in this study is Knowledge Discovery in Database KDD which includes data selection, preprocessing, transformation, data mining, and evaluation of results. The study was conducted using the RapidMiner tool, with a dataset of 279 Informatics Study Program students from the 2015 to 2019 intake. The data was classified into two categories: "graduated on time" and "not graduated on time". The test results showed that the KNN algorithm provided better performance compared to C4.5. KNN produced an accuracy of 76.08%, with a precision of 73.11% and a recall of 41.92%. Meanwhile, the C4.5 algorithm produced an accuracy of 73.49%, with a precision of 64.62% and a recall of 41.89%. This difference in accuracy indicates that KNN is more effective in capturing patterns in the data and providing more accurate predictions in this context. Thus, the KNN algorithm can be considered a more optimal method to assist universities in predicting potential student admissions in a timely manner, thus enabling early intervention for students at risk of late graduation. This research also contributes to the development of data mining-based academic decision support systems in higher education.

The selection of recipients of the Single Tuition Fee (UKT) assistance at universities must be carried out with the principles of fairness, openness, and efficiency to ensure that the assistance is distributed appropriately. However, the manual selection process is often subjective and prone to error. Therefore, this study developed a decision support system based on the Simple Additive Weighting (SAW) method to assist the selection process of students eligible for UKT assistance more systematically and accurately. The SAW method was chosen because of its ability to process data involving various criteria to produce objective decisions. In this study, the criteria used for the selection of UKT assistance recipients include several aspects, such as the Cumulative Grade Point Average (GPA), parental income, number of dependents, non-academic achievements, distance of the student's residence from campus, active student status, and involvement in student organizations. Data from each criterion is then processed through a normalization stage to ensure uniformity of values and weighting based on their level of importance. After the normalization and weighting process, the next step is to calculate the preference value for each student. The results of the implementation of this system show that the SAW method can accurately rank student priorities, with a student named Selly receiving the highest preference score, 0.673. This indicates that the student in question meets the selection criteria with the best score. This developed system can support the UKT assistance selection process to be fairer and more efficient. By using the SAW method, subjective and manual errors in decision-making can be reduced, resulting in more objective and accurate decisions. In addition, this system also allows universities to evaluate UKT assistance recipients more transparently and precisely, which ultimately can increase public trust in the management of educational assistance at universities.

This study aims to develop an accurate predictive model for identifying students at risk of academic dropout using Decision Tree and Random Forest algorithms. The research utilizes a publicly available dataset sourced from Kaggle, which includes academic and demographic features such as GPA, attendance, credit load, financial aid status, and exam scores. The methodology involves several stages: data collection, preprocessing (handling missing values, encoding categorical variables, and feature scaling), model training, and evaluation using performance metrics such as Accuracy, Precision, Recall, F1-Score, and Confusion Matrix. Results show that the Random Forest algorithm outperforms Decision Tree in terms of accuracy and robustness, with notable feature importance on math, reading, and writing scores. The findings highlight the potential of machine learning in early detection of dropout risks and provide actionable insights for academic institutions to design timely interventions. This research contributes to the growing field of educational data mining and supports data-driven decision-making processes in higher education management.

Financial management in the public sector, especially at the village level, often faces various challenges. These challenges include limited resources, complexity of administrative procedures, and the need for high transparency and accountability. In this context, the analysis of planning, control, and evaluation of financial management becomes very relevant. This study aims to find out (1) The Influence of Planning on the Routine Expenditure Budget (2) The Effect of Control on the Routine Budget. (3) The Effect of Financial Management Evaluation on Routine Expenditure Budget at Kalisegoro Village Office, Gunungpati District, Semarang City. This research was conducted using quantitative analysis methods. The data is in the form of a list of budget uses of the Kalisegoro Village Office. Data collection through documentation related to the problem being researched at the Kalisegoro Village Office, Gunungpati District, Semarang City. The analysis tool used was multiple linear regression. The results of the study show that Planning and Control has a significant influence on the Routine Expenditure Budget while the Financial Management Evaluation has no effect on the Routine Budget. For further research, it is recommended to use other variables that affect the Routine Expenditure Budget that is not yet present in this study, extend the observation time, and increase the number of samples.

This research is motivated by the problem in the Preservation of Gondang Buhun Traditional Arts in Kuta Traditional Village, Karangpaningal Village. This study uses a descriptive method with a qualitative approach with primary data sources in the form of interview results from 6 informants consisting of 1 village, 1 village official, 1 village elder, 1 person from the Gondang Buhun art administrator, 1 member of the Gondang Buhun art, 1 person, 1 community/community leader. Secondary data is in the form of relevant documentation. The data collection technique consists of observation, interviews with the stages of data reduction analysis, data presentation, and conclusion drawn. The results of the study show that the Karangpaningal Village Government has a role in the preservation of Gondang Buhun's traditional arts, including the role of stabilizer through support for the sustainability of traditional events through Gondang Buhun performances. The role of innovators encourages the birth of creativity through the development of training patterns, the role of modernizers facilitates it, the role of pioneers to be the main actors who initiate conservation initiatives through policy support, village budget allocation, and the role of self-implementers to provide instructions or directions. The obstacles found are the lack of regeneration of young artists, limited funds, and lack of promotion which have an impact on the decline of the existence of Gondang Buhun among the younger generation. Efforts that have been made are to support preservation through the provision of village budgets, training procurement, and support art performances at various traditional and state events.

KDRT atau domestic violence merupakan kekerasan berbasis gender yang terjadi di ranah personal. Kekerasan ini banyak terjadi dalam hubungan relasi personal, dimana pelaku adalah orang yang dikenal baik dan dekat oleh korban, misalnya tindak kekerasan yang dilakukan suami terhadap istri, ayah terhadap anak, paman terhadap keponakan, kakek terhadap cucu. Dampak bagi korban adalah mengalami sakit fisik, tekanan mental, menurunnya rasa percaya diri dan harga diri, merasa tidak berdaya, merasa ketergantungan pada suami meski telah disiksa, stres pascatrauma, depresi, bahkan keinginan untuk bunuh diri.  Pengabdian Masyarakat ini berupa edukasi kepada warga terutama kader Kesehatan tentang KDRT dan dampaknya serta upaya pencegahan dan deteksi dini KDRT di lingkungan keluarga. Kader juga harus mengsosialisasikan upaya pemerintah dalam mengatasi kasus KDRT. Kegiatan edukasi ini membantu meningkatkan pengetahuan dan kesadaran bagi warga, dan keluarga dalam penangganan terhadap kasus KDRT serta dampaknya.

This research aims to design an Islamic Boarding School (Ponpes) with a sustainable architecture approach that is able to answer environmental, social, and economic challenges holistically. The method used is a qualitative-descriptive approach through architectural design research, which combines empirical data from the field with theoretical studies from relevant literature. The design location is on Jl. Gunungpati Raya, Nongkosawit Village, Gunungpati District, Semarang City, with an area of ±19,909.77 m². Data collection techniques include literature study, site observation, and comparative design study. Data were analyzed descriptively and spatially to formulate user needs and site potential. The design results show that the sustainable architecture approach can be implemented through functional layout, passive energy utilization, vegetation preservation, rainwater management, and waste recycling system. The design also accommodates social and economic aspects through the provision of organic farming areas and small farms as part of practice-based education. Contemporary Islamic architectural aesthetics are applied contextually, creating a healthy, inclusive, and adaptive learning environment. This research produces a sustainable pesantren design concept that can be a reference model in the development of environmentally friendly and self-reliance-based Islamic educational institutions..

The popularity of futsal continues to increase among teenagers, but many players have not mastered basic skills and also lack physical abilities, which has an impact on playing skills on the field. This study aims to analyze the effect of circuit training modifications to improve futsal playing skills in futsal extracurricular students at SMA Negeri 19 Garut. The research method used was an experiment with a One group pre-test post-test design. The sample consisted of 20 students who were members of the SMAN 19 Garut futsal extracurricular. The instrument used was a futsal playing skills test using the General Performance Assessment Instrument (GPAI). The results showed an increase in the average general performance score with the results of the Asymp. (2-tailed) = 0.403 <α = 5% = 0.05 (significant). Based on these results, it can be concluded that circuit training modifications can improve futsal playing skills.

Self-esteem exerts a significant influence on an individual's confidence and adaptability, indirectly influencing students' academic success. This research seeks to examine the association between self-esteem levels and the Cumulative Grade Point Average (GPA) of students at the Faculty of Economic,  Sultan Agung Islamic University, Semarang. This study employs a quantitative approach with a cross-sectional design. The research sample consists of 185 respondents selected randomly using the simple random sampling method. Data were collected through the Rosenberg Self-Esteem Scale (RSES) questionnaire to measure self-esteem levels and students' latest GPA records. Data analysis was conducted using the Spearman correlation test. The findings of this investigation reveal a robust positive correlation between self-esteem levels and students' GPA (p = 0.000; r = 0.774). This suggests that elevated self-esteem is intrinsically linked to improved scholastic performance. This study is anticipated to serve as a foundational reference for support programs aimed at enhancing students' self-confidence. In conclusion, a profound and statistically significant association is evident between self-esteem and students' academic performance.  

Quality public service is what is called the best service that meets service quality standards. Service standards are the benchmarks used as guidelines for the delivery of service and the reference for evaluating the quality of service as the obligation and promise of the service providers to the community in the context of quality, fast, affordable, and measurable service. The purpose of this study is to assess the quality of public service at the Maniangpajo Subdistrict office and to identify the factors affecting the quality of public service at the Maniangpajo Subdistrict office. This research uses a qualitative method with a population of 5 individuals, consisting of civil servants (2 people) and the public (3 people). Data collection was done using observation, interviews, and documentation techniques, while the data analysis technique used in this study is qualitative analysis, specifically the interactive analysis technique.The results of this study show that the service at the Maniangpajo Subdistrict office is considered good by service users because the staff are proactive in providing information and the waiting room is comfortable. Although there are no specific SOPs in place, they apply service standards in accordance with government regulations. However, issues such as limited human resources and the unavailability of ID card forms cause delays in service.For internal factors, it can be concluded that the main obstacle to service delivery at the Maniangpajo Subdistrict office is frequent internet network disruptions. These disruptions slow down the service process that requires internet connectivity. Additionally, internal factors such as the limited number of service personnel also affect the efficiency of service, especially when many service users are present, resulting in long waiting times.

This study explores the application of machine learning to predict students' GPA based on behavioral and time-related factors, including study hours, extracurricular activities, sleep, social interactions, and physical activity. Seven regression algorithms were employed to evaluate predictive accuracy using metrics such as MAE, RMSE, and R2 Among these, Regularized Linear Regression demonstrated the highest accuracy and interpretability, highlighting its suitability for this dataset. The findings emphasize the potential of machine learning in identifying key predictors of academic performance and offer practical applications for personalized academic advising and time management. This research provides a data-driven framework to support students and educators in optimizing learning outcomes.

According to the Central Statistics Agency (BPS), the level of education and welfare in the family greatly influences the quality of human resources in Indonesia. Therefore, efforts to strengthen family functions, such as increasing parental education and social welfare programs, are key in accelerating national development. This increase in human resources includes knowledge and skills in processing agricultural products, especially rambutan fruit, crystal guava and longan into processed food products with higher selling value such as chips. Apart from that, this program also trains them in creative product packaging, marketing, bookkeeping, simple financial management, and the use of digital technology, including online learning applications and social media. With these skills, they are expected to be able to contribute to improving the family's economy, as well as opening up new business opportunities that support financial independence.