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Magelang City faces the challenge of limited land availability, with a total area of only 18.58 km2 and a high population density. Consequently, telecommunications infrastructure development requires a precise strategy. This study aims to analyze the business model and investment feasibility of Pole and Greenfield type telecommunication towers in Magelang City. Using a descriptive quantitative approach, this research processes secondary data from PT Dayamitra Telekomunikasi Indonesia by applying feasibility analysis based on Life Cycle Costing (LCC), Net Present Value (NPV), Internal Rate of Return (IRR), Break-Even Point (BEP), Payback Period (PP), and Benefit-Cost Ratio (BCR). The results indicate significant differences in cost structures; Pole towers proved to be more efficient, requiring an initial capital outlay of only 28.8% of the total capital required for Greenfield towers. Greenfield towers generated an NPV of Rp13.07 billion with an IRR of 20%, while Pole towers generated an NPV of Rp2.46 billion with a higher IRR of 23%. Pole towers have proven to offer a faster return on investment and better operational cost efficiency, making them the most strategic option to support network densification and the implementation of 5G technology in urban areas with spatial constraints like Magelang City.

Early detection of a potential heart attack is a crucial step in preventing sudden death from heart disease. This research aims to develop an Internet of Things (IoT)-based health monitoring system capable of measuring vital body data in real time and predicting the likelihood of a heart attack from CSV data obtained from sensors, integrated through RapidMiner as learning data using a machine learning algorithm, the Support Vector Machine (SVM). The system was built using an ESP32 microcontroller connected to a MAX30102 sensor to measure heart rate and finger oxygen levels (SpO₂), as well as a DHT22 sensor to measure temperature and humidity. The resulting data is sent to the Blynk application to display real-time data according to its parameters. The initial prediction logic was developed using a rule-based method based on medical thresholds for four vital parameters. The data was then used to train an SVM model as a classification system to detect potential heart attacks. Test results showed that the system can identify abnormal conditions with a good level of accuracy and provide early warnings based on changes in vital parameters in real time. This system is expected to be an initial solution for personal health monitoring, especially for individuals at risk of heart disease. It can be further developed with cloud integration and automatic notifications to users' devices.

Bullying is a serious problem that can disrupt the learning process and mental development of students, including in Islamic boarding schools. Early detection of bullying is essential to creating a safe and conducive learning environment. This study aims to apply the You Only Look Once (YOLO) algorithm to automatically detect bullying through video recordings in the environment of the SMK Skill Village Islamic School Business Boarding School. The method used involves collecting a video dataset representing various types of bullying behavior, labeling the data, and training an object detection model using the YOLOv5 algorithm. The developed system is capable of detecting and classifying bullying behavior in real- time with detection accuracy reaching [accuracy value if known]. The implementation of this system is expected to assist school authorities and boarding school administrators in monitoring, preventing, and addressing bullying incidents more quickly and effectively, while also serving as an initial step in leveraging artificial intelligence technology to create a safer and more comfortable educational environment.

QRIS (Quick Response Code Indonesian Standard) has become a widely used national digital payment standard. User satisfaction with this service needs to be monitored continuously to ensure its sustainability. This study aims to predict the level of QRIS user satisfaction based on their experiences and perceptions expressed organically on the Twitter social media platform. The method used is sentiment analysis with the Naive Bayes classification algorithm implemented using RapidMiner software. The research data was obtained from Twitter user comments collected through web scraping techniques. The text data then went through a preprocessing stage that included cleansing, stopword filtering, stemming, and tokenizing to be prepared as features ready to be processed by the model. The data was divided into training (80%) and testing (20%) subsets for model training and validation. The results showed that the Naive Bayes model was able to predict user satisfaction sentiment with an accuracy of 80.99%. These findings indicate that the model is highly accurate in identifying satisfied comments and sufficiently sensitive in detecting dissatisfaction. This study concludes that sentiment analysis of Twitter UGC data using Naive Bayes is an effective and efficient approach for predicting QRIS user satisfaction in real time. The practical implication of this study is to provide an automatic feedback system for service providers to monitor public sentiment and take targeted corrective actions.

Based on the 2023 Indonesian Health Survey, the prevalence of overweight among adults reached 23.4% nationally and 24.5% in East Java Province. This condition highlights the need for food innovation, particularly high-fiber snacks suitable for overweight adults. This study aimed to develop cereal based on okara (soy pulp) flour and mung bean flour as an alternative high-fiber food product. Organoleptic testing was conducted on 30 semi-trained panelists evaluating color, aroma, texture, and taste using hedonic and hedonic quality tests. Data were analyzed using the Kruskal–Wallis test followed by the Mann–Whitney test, while nutrient content analysis was analyzed using One Way ANOVA followed by Duncan’s post hoc test. The results showed that in the hedonic test, color, texture, and taste parameters were significantly different (p<0.05), while aroma was not significantly different (p>0.05). In the hedonic quality test, color and taste showed significant differences (p<0.05), whereas aroma and texture did not (p>0.05). Overall, formulation 922 was the most preferred by panelists. The nutritional content of the cereal ranged from 407–410 kcal for energy, 76.44–77.53% carbohydrates, 8.91–9.66% protein, 6.80–7.30% fat, 5.20–5.51% moisture, 1.26–1.41% ash, and 9.72–10.90% total dietary fiber. The developed cereal is classified as a high-fiber food and has potential as a healthy snack for overweight adults.

Guru di sekolah dasar Tahfidz sering kali menghadapi tantangan besar dalam mengintegrasikan pengajaran Al-Qur’an dengan kemampuan pedagogik modern yang mendukung pembelajaran aktif. Kegiatan Pengabdian kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan kompetensi pedagogik dan profesional para guru di SD Tahfidz Ibnu Umar Karawang melalui pelatihan metode pengajaran yang bermakna dan inovatif. Permasalahan utama yang ditemukan di mitra sasaran adalah keterbatasan guru dalam menerapkan pendekatan PAIKEM serta kesulitan dalam menyusun perangkat ajar yang adaptif terhadap prinsip Kurikulum Merdeka. Metode yang digunakan dalam kegiatan ini adalah kombinasi ceramah interaktif, workshop penyusunan modul/RPP, dan praktik langsung melalui sesi microteaching. Pelatihan dilaksanakan dalam tiga sesi utama: (1) pemahaman karakteristik peserta didik usia 7–12 tahun berdasarkan aspek kognitif, sosial-emosional, dan psikomotorik; (2) desain pembelajaran bermakna (meaningful learning); serta (3) strategi pembelajaran aktif seperti Problem-Based Learning (PBL), Discovery Learning, dan pembelajaran kooperatif. Hasil kegiatan menunjukkan adanya peningkatan pemahaman 15 guru peserta dalam menciptakan lingkungan belajar yang berpusat pada siswa (student-centered) serta kemampuan mengintegrasikan teknologi pembelajaran modern (IPTEKS) seperti Canva dan media interaktif dalam proses KBM. Luaran dari program ini mencakup modul pelatihan pedagogik, publikasi artikel ilmiah, dan video diseminasi hasil implementasi metode pembelajaran.

This study aims to analyze the implementation of the madrasah quality paradigm from the perspective of the Qur'an at MIS Al-Hunafa Palangka Raya. The study used a qualitative field research approach with observation, interview, and documentation techniques. Data analysis used the Miles and Huberman model. The results of the study indicate that: 1) the quality paradigm is understood not only to be oriented towards academics, but also to the formation of character and spiritual values ​​of students; 2) the implementation of the quality paradigm is carried out through the integration of Qur'anic values ​​such as amanah, itqan, ihsan, discipline, and responsibility in madrasah culture, learning, and religious activities; and 3) the implementation of quality still faces obstacles in the form of limited infrastructure, variations in teacher competencies, and technological demands, so that the madrasah carries out strengthening through teacher training, facility optimization, and the development of a quality culture based on Qur'anic values. Thus, the implementation of the quality paradigm at MIS Al-Hunafa has been running quite well and is carried out sustainably.

This study investigates the effect of total risk on firm performance and sustained growth among consumer non-cyclicals manufacturing companies listed on the Indonesia Stock Exchange (IDX) over the period 2019–2023. Total risk is operationalized through the systematic risk proxy (Beta/β), estimated via the Capital Asset Pricing Model (CAPM) framework as the covariance between individual stock returns and the market return divided by the variance of market returns, using the Jakarta Composite Index (JCI) as the market benchmark. Firm performance is measured through Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q, while sustained growth is operationalized following Gerson et al. (2025) as SG = b × ROE, where b denotes the earnings retention ratio. Panel data regression analysis is applied to 225 firm-year observations drawn from 45 companies, with model selection guided by the Chow and Hausman specification tests. The Fixed Effect Model (FEM) is adopted for ROA, ROE, and SG, while the Random Effect Model (REM) is applied for Tobin’s Q. Results indicate that systematic risk exerts a significant negative effect on ROA (β = −0.312; p < 0.01) and ROE (β = −0.278; p < 0.01), but is statistically non-significant for Tobin’s Q, suggesting that capital market pricing in Indonesia does not fully incorporate systematic risk information. Critically, systematic risk exerts the largest and most significant negative effect on sustained growth (β = −0.347; p < 0.01), revealing a dual transmission mechanism through which risk suppresses ROE while simultaneously inducing more conservative dividend policies, both of which constrain long-run growth sustainability. These findings carry important implications for corporate risk management strategy and empirically enrich the literature on risk, performance, and growth in emerging capital markets.

Scientific writing is one of the essential skills that college students need to support research activities and the development of knowledge. However, students still encounter various challenges during the writing process. This study aimed to identify students’ responses toward scientific activities at FMIPA Universitas Negeri Surabaya and to examine the difficulties experienced by students in preparing scientific papers. The study employed a qualitative descriptive method using a purposive sampling technique. The research subjects consisted of 36 students from various study programs at FMIPA Universitas Negeri Surabaya who had been involved in research activities and scientific proposal writing. Data were collected through student response questionnaires consisting of closed-ended and open-ended questions. The data were analyzed descriptively and presented in tables and narrative descriptions. The results showed that most students had understood the existing student research programs and were familiar with the use of research guidelines. However, students still faced difficulties in systematically organizing research ideas, determining research variables and methods, finding relevant literature reviews, and connecting theories from various references. In addition, time management and the use of citation management applications were also obstacles for some students. Therefore, more structured assistance is needed through scientific writing training, reference searching training, and the use of citation management applications to improve the quality of students’ scientific writing.

This research used a qualitative approach with a descriptive analytical research type through a literature study method. The research data were obtained from various written sources such as scientific journals, books, research articles, and other documents relevant to the research topic. Data collection techniques were carried out through documentation by reading, recording, and classifying data according to the focus of the research. Data analysis was conducted descriptively and qualitatively through the stages of data reduction, data presentation, and drawing conclusions. The results of the study indicate that Civic Education has an important role in instilling tolerance values in students through materials related to diversity, democracy, human rights, and Pancasila values. Civic Education learning helps students understand the importance of respecting differences in ethnicity, religion, culture, and opinions in everyday life. In addition, teachers also play an important role in fostering tolerance through group discussions, teamwork, and presentation activities that train students to respect and cooperate with one another. However, there are still obstacles in implementing tolerant attitudes, such as environmental influences and the lack of awareness among some students. Therefore, cooperation between teachers, schools, and parents is needed to continuously foster students’ attitudes of tolerance.

This study aims to analyze the skills gap in the era of the Industrial Revolution 4.0 and the factors influencing it. The research employed a descriptive-analytical approach based on literature studies and the author’s analysis of the dynamics of formal education curricula and the development of industrial needs. The findings indicate that formal education curricula that are less adaptive to technological developments are the main factor causing the skills gap. In addition, the slow adaptation to technology in educational and industrial environments, as well as the unequal distribution of skills development across various regions in Indonesia, further widen the gap between graduates’ competencies and labor market demands. This condition affects the low readiness of the workforce in facing digital transformation and global competition. The study concludes that the skills gap is a strategic issue requiring serious attention from the government, educational institutions, and the industrial sector. Curriculum reform that is responsive to technological advancements, strengthening digital literacy, and ensuring equal access to training and skills development are essential steps to improve the competitiveness of Indonesian human resources. These efforts are expected to support poverty reduction, reduce social inequality, and achieve the long-term national development goals toward Indonesia Golden Vision 2045.

Effective communication is essential for teamwork effectiveness in healthcare, particularly in inpatient units where patient care requires coordination among multiple professionals. Internal data from Hospital X showed that more than 50% of medical incidents in the last two years were related to miscommunication among healthcare workers. In addition, the 2024 employee satisfaction survey reported that workplace communication satisfaction was only 62%, below the hospital target of 75%. This study aimed to examine the influence of effective communication on teamwork effectiveness with interprofessional collaboration as an intervening variable at Hospital X.This study used a quantitative cross-sectional design involving 226 healthcare workers, including doctors, nurses, and medical support staff. Data were analyzed using the Three-Box Method and PLS-SEM. The findings revealed that effective communication significantly influenced teamwork effectiveness both directly and indirectly through interprofessional collaboration. Interprofessional collaboration also acted as a significant mediating variable between communication and teamwork effectiveness. These results indicate that communication is a key foundation for strengthening collaboration and improving teamwork in hospitals. Therefore, hospitals should enhance communication training and interprofessional collaboration programs to improve healthcare quality and patient safety

This study aims to analyze the role of teachers’ personality competence in shaping students’ learning environments through a literature review approach. Personality competence reflects teachers’ stable, mature, and authoritative character, enabling them to serve as role models for students and influencing the creation of a conducive learning environment both psychologically and socially. The method used is a literature review by analyzing various sources such as books, academic journals, and relevant official documents. The results show that teachers with positive personality traits are able to build harmonious relationships, create a comfortable classroom atmosphere, and enhance students’ learning motivation. Therefore, teachers’ personality competence is an important factor in supporting the quality of the learning environment and the success of the learning process. In addition, findings from various studies indicate that personality competence not only affects classroom interactions but also contributes to the development of students’ attitudes, discipline, and emotional stability. Teachers who demonstrate consistency, empathy, and integrity tend to foster a sense of trust and respect among students, which further strengthens classroom engagement. Moreover, a positive teacher personality helps reduce learning barriers such as anxiety, lack of confidence, and lack of participation in classroom activities. In the context of modern education, where student-centered learning is increasingly emphasized, teachers’ personality competence becomes even more essential in facilitating active learning and meaningful student involvement. Thus, strengthening teachers’ personality competence through training, reflective practice, and continuous professional development is crucial to improving overall educational quality and achieving optimal learning outcomes.

This study aims to analyze the implementation of the Bravo PUPR Online attendance system in improving the work discipline of Civil Servants (ASN) at the National Road Implementation Center of East Nusa Tenggara. The research focuses on punctuality of attendance, consistency in fulfilling working hours, task completion, compliance with attendance procedures, alignment between recorded data and actual conditions, and acceptance of consequences for violations. The study employs a qualitative approach with data collection techniques including observation, documentation, and interviews with leaders, system operators, and ASN as direct users. The results indicate that the implementation of the Bravo PUPR Online attendance system has improved administrative order in attendance and increased ASN awareness of time discipline. However, work discipline has not been fully optimal, as several issues remain, such as inconsistent attendance, suboptimal fulfillment of working hours, and discrepancies between attendance data and actual field conditions. In addition, technical constraints such as internet connectivity and GPS accuracy, as well as behavioral factors like negligence and lack of supervision, also affect system effectiveness. In terms of compliance, the Bravo system integrated with e-HRM is considered effective in detecting violations and enforcing strict consequences, ranging from warnings to administrative sanctions. This demonstrates that the attendance system functions not only as a recording tool but also as an instrument for monitoring discipline.

The rapid advancement of artificial intelligence (AI) has significantly altered the landscape of business decision-making, particularly for Micro, Small, and Medium Enterprises (MSMEs) in Indonesia. Despite their critical role in economic growth and employment generation, MSMEs frequently encounter substantial barriers related to technological adoption, digital literacy, and resource allocation. This research systematically investigates the utilization of artificial intelligence as a responsive innovation mechanism designed to optimize decision-making processes within the MSME sector. By employing a comprehensive systematic literature review methodology, analyzing peer-reviewed publications from globally recognized academic databases between 2018 and 2024, this study delineates the multifaceted benefits, complex challenges, and contextualized adoption strategies associated with AI integration. The findings reveal that artificial intelligence holds transformative potential for enhancing operational efficiency, refining predictive analytics, and sustaining long-term competitiveness. Conversely, critical challenges, including inadequate digital infrastructure, financial constraints, and organizational resistance, remain pervasive obstacles. Consequently, the study advocates for a gradual, responsive innovation approach that aligns technological adoption with specific business needs and environmental pressures. The insights derived from this research offer substantial theoretical and practical implications, providing a strategic framework for policymakers and MSME owners to accelerate digital transformation inclusively.

This study aims to develop a sentiment classification method for YouTube user comments related to the game Love and Deepspace using the Naïve Bayes algorithm, focusing on improving the text data processing and understanding user perceptions. Comment data were collected through scraping from YouTube videos, followed by preprocessing including text cleaning, normalization, stopword removal, stemming, and translation into English. Initial labeling was conducted using TextBlob, then the data were randomly sampled for training the Naïve Bayes model. Evaluation involved comparing sentiment distributions and visualization using Word Cloud and bar charts. The Naïve Bayes model achieved an accuracy of 77.36% in sentiment classification. The sentiment distribution shows differences between TextBlob (positive: 1,011, neutral: 1,312, negative: 575) and Naïve Bayes (positive: 901, neutral: 1,627, negative: 370), with Naïve Bayes being more conservative. The Word Cloud visualization identifies dominant words such as "bang," "game," and "main," while the bar chart shows the largest proportion of neutral sentiment. Naïve Bayes is effective for sentiment classification on informal comment data, with significant differences from rule-based methods like TextBlob. This research contributes to the development of text data processing techniques and user perception analysis, as well as opening up optimization opportunities with other algorithms like SVM for better accuracy.

Social media has evolved into a significant platform where consumers freely express their opinions, experiences, and levels of satisfaction regarding various products, including those offered by Micro, Small, and Medium Enterprises (MSMEs). The comments and reviews shared by customers on these platforms contain diverse sentiments that can serve as valuable indicators of how consumers perceive product quality. Understanding these sentiments is crucial for MSME owners, as it allows them to evaluate their products and adapt to market expectations more effectively. This study aims to analyze customer sentiment toward MSME products on social media by utilizing the Naïve Bayes algorithm, a widely used classification method in text mining. The data used in this research consist of customer comments collected from various social media platforms. The research process involves several stages, including data collection, manual labeling of sentiments, text preprocessing (such as tokenization, case folding, and stopword removal), and splitting the dataset into training and testing subsets. Subsequently, the classification process is carried out using the Naïve Bayes algorithm to categorize sentiments into positive, negative, and neutral classes. The results of this study demonstrate that the Naïve Bayes method is effective in classifying customer sentiments with a satisfactory level of accuracy. These findings provide a comprehensive overview of consumer perceptions regarding the quality of MSME products. Furthermore, this research is expected to assist MSME business owners in understanding customer feedback more systematically and using it as a basis for improving product quality and enhancing customer satisfaction in a competitive digital marketplace.

this study aims to evaluate the impact of capacity building for village officials in Anjir Seberang Pasar I Village on the effectiveness of village administrative and financial management following the implementation of Law No. 6 of 2014. The primary focus of the study is to measure changes in the competencies of village officials before and after the implementation of technical guidance, as well as the use of the Village Financial System (Siskeudes) application and Internet Banking Business. The research method used is qualitative with a case study approach, in which data collection was conducted through observation, interviews, and the completion of pre-test and post-test questionnaires by respondents consisting of the Village Secretary, Kaur, and Kasi. The results of the study indicate a significant increase in three key variables: perceived usefulness, perceived ease of use, and attitude toward using. Quantitatively, the average validation score from respondents reached 4.53 (on a 5.0 scale), which falls into the “Agree” category regarding the system’s effectiveness. Based on data analysis, the success rate of capacity building for village officials was recorded at 29.23%, with a final understanding rate reaching 91.33%. These findings indicate that practice-oriented and participatory training is capable of improving the technical skills and accountability of village officials in managing digital-based government administration. The integration of Siskeudes and digital banking has proven to have a positive impact on a safer and more transparent payroll system at the village level.

The problem of stunting is still a serious issue in health development in Indonesia because it has an impact on the quality of human resources. This study aims to analyze the efforts of the Pagomogo Village Government in handling stunting. The research uses a descriptive qualitative approach with data collection techniques through observation, interviews, and documentation. Informants were determined using purposive sampling consisting of village governments, health workers, cadres, and the community. The results of the study show that the village government has implemented various programs, such as Supplementary Feeding (PMT), strengthening Human Development Cadres (KPM), improving services through community institutions, and sanitation development. However, the implementation of the program has not been optimal because it is still constrained by economic factors, low public awareness, limited counseling, and access to clean water. This study concludes that the main problem does not lie in the availability of programs, but in the implementation and sustainability aspects. Therefore, it is necessary to strengthen community empowerment, improve education, and evaluate results-based programs.

Old age is the final phase in the human life cycle, characterised by a decline in physiological function. Global data shows that the prevalence of old age will increase from 33.69 million to 48.19 million by 2035. One of the effects of this decline in physiological function is a disruption in the quality of sleep among the elderly. As many as 50-60% of elderly people in Indonesia experience sleep disorders. One way to overcome sleep disorders is through relaxation therapy. Progressive Muscle Relaxation is a technique performed by stretching and relaxing certain muscles to relax the body. The purpose of this study was to determine the effectiveness of progressive muscle relaxation on the quality of sleep in elderly people. This research method involved a nursing care process from assessment to evaluation using a case study design. The research sample consisted of one elderly person with moderate sleep quality. The intervention was given for 10-15 minutes using eight movements with a frequency of twice a week for one month. The data were analysed using pre-test and post-test PSQI questionnaires to determine sleep quality. The results of this study indicate that progressive muscle relaxation training has an effect on improving sleep quality in the elderly.