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This study examines the role of mathematics learning in improving logical thinking skills in early childhood. The background of this study is based on the importance of logical thinking skills as a foundation for children's cognitive development, which can begin at an early age through appropriate mathematics learning. The purpose of this study is to analyze how mathematics learning can stimulate the development of logical thinking in early childhood and explore effective learning strategies. The methods used are library research and observation of several models of mathematics learning for early childhood in early childhood education institutions. The findings indicate that fun and concrete activity-based mathematics learning can improve children's abilities in critical thinking, constructing patterns, drawing conclusions, and solving simple problems. The implications of this study emphasize the need for the application of creative and interactive mathematics learning methods to support the development of logical thinking from an early age, while also encouraging educators to integrate mathematics into children's daily activities. This study also recommends the development of learning media appropriate to children's developmental stages for optimal results.

Measurement is a fundamental domain of mathematics that connects formal mathematical concepts with everyday experiences. Despite its practical relevance, students often experience persistent difficulties in understanding measurement conceptually, tending to approach it as a procedural activity rather than as a process of reasoning about quantities, units, and comparisons. These challenges indicate that learning measurement is influenced not only by individual cognitive factors but also by the social dynamics that shape classroom learning environments. This study aims to examine classroom social dynamics in learning measurement by providing empirical evidence from contextual learning situations. This study employed a qualitative research approach to explore how social interaction, scaffolding, and participation mediate students’ understanding of measurement in contextual learning environments. Data were collected through classroom observations, video recordings of learning activities, analysis of students’ written work, and interviews with selected students and the teacher. Contextual measurement tasks were designed to encourage collaboration, dialogue, and justification, enabling the examination of student–student and teacher–student interactions as they naturally occurred in the classroom. Data analysis was conducted iteratively to identify patterns of interaction, forms of scaffolding, and students’ learning progression within the Zone of Proximal Development. The findings reveal that students initially engaged with measurement tasks in a predominantly procedural manner, with limited conceptual understanding and minimal peer interaction. After the implementation of contextual learning situations, classroom social dynamics changed substantially. Students became more actively involved in discussion, collaborative problem-solving, and collective meaning-making. Peer interaction supported the articulation and refinement of students’ reasoning, while teacher scaffolding guided learning by extending students’ thinking without providing direct solutions. These social processes facilitated students’ movement from their actual level of understanding toward higher levels of conceptual competence within the Zone of Proximal Development. The study further shows that contextual learning tasks alone are insufficient to promote meaningful understanding unless they are supported by productive social interaction and adaptive scaffolding. Conceptual understanding of measurement emerged through socially mediated processes rather than through task completion alone. This study contributes to mathematics education research by emphasizing the central role of classroom social dynamics in contextual learning and by offering insights into how interaction and scaffolding can be orchestrated to support students’ conceptual understanding of measurement.

This study aims to describe the forms and social functions of code-switching and code-mixing in the film Hujan Bulan Juni and to explain how language choice represents identity and social differences among the characters. The film was chosen because it portrays interactions between characters from different cultural backgrounds Javanese and Manadonese which allows for complex patterns of language contact. The study employed a descriptive qualitative method using observation and note-taking techniques on dialogues containing Indonesian, Javanese, and Manadonese linguistic elements. The data were analyzed using the sociolinguistic frameworks of Gumperz (1982) and Wardhaugh (2015) to uncover the social functions and identity meanings reflected in the speakers’ language choices.The findings reveal that code-switching from Indonesian to Manadonese serves to reinforce ethnic solidarity, emotional closeness, and cultural pride, while switching from Indonesian to Javanese reflects politeness, intimacy, and social hierarchy. Meanwhile, code-mixing between Indonesian and Manadonese marks distinctive speech styles and expresses regional identity, whereas code-mixing between Indonesian and Javanese functions to soften utterances and portray the speakers’ courteous demeanor. Overall, language choice in Hujan Bulan Juni is not merely a communicative tool but also a representation of identity and social differentiation within Indonesia’s multilingual society.

Iwan Fals’ song "Bento" offers social criticism, which is analyzed using Teun A. Van Dijk's critical discourse analysis model. Released in 1989, the song critiques the social conditions and behaviors of the wealthy elite during the New Order era, highlighting issues of arrogance, corruption, and social inequality. This qualitative descriptive study applies the Analisis Wacana Kritis (AWK) method, analyzing the lyrics of "Bento" through three dimensions: text, social cognition, and social context. In the text dimension, the analysis reveals the main theme as a depiction of the fictional character "Bento," portrayed as an arrogant and corrupt figure. The text structure employs a narrative persona pattern, with semantic elements describing the luxury of New Order rulers and the exploitation of the common people. The stylistic devices, including anthropomorphism and rhetoric, emphasize the selfish enjoyment of the elite. In the social context, the song is a response to the corruption, collusion, and nepotism (KKN) that characterized the New Order regime. Through satire, "Bento" critiques the dominance of the elite and their disregard for the common people. Overall, the song exposes the power dynamics and corruption under the New Order regime.

The development of small and medium enterprises (SMEs) and household industries is often regarded as the economic foundation of a region. However, much of the existing research in Indonesia remains focused on quantitative descriptive analysis, while providing limited attention to spatial dynamics and interregional disparities. This study aims to critically evaluate the spatial distribution patterns of SMEs and household industries at the regency and city levels, with particular emphasis on clustering tendencies, unequal distribution, and their relationships with regional characteristics. A spatial analysis approach is employed to identify spatial autocorrelation and industrial clustering patterns, which is complemented by a structural analysis of infrastructure availability, market accessibility, and regional institutional capacity. The findings indicate that the distribution of SMEs and household industries is not geographically random, but rather forms clusters that are predominantly concentrated in areas with higher levels of accessibility and economic activity. This condition reflects spatial inequality that may exacerbate development disparities between regencies and cities. Furthermore, the results reveal that uniform industrial development policies are insufficient to accommodate the diverse spatial characteristics across regions. Therefore, this study underscores the importance of formulating spatially informed and context-sensitive policies for the development of SMEs and household industries in order to promote more balanced and sustainable regional industrial development.

This study discusses the introduction of digital signature patterns using the Backpropagation method on Artificial Neural Network (JST) to identify a person's characteristics and potential. The increasing use of digital identities demands a verification system that is more secure, accurate, and adaptive to the variations of each individual's signature. The main problem faced in the signature recognition system is the low level of accuracy when the visual features of the signature have similarities between users, both in terms of shape, size, and stroke pressure. In addition, variations of signatures made by the same individual are also a challenge in the identification process. As a solution, this study implements Principal Component Analysis (PCA) to extract important features from the signature image before the training process using JST. PCA is used to reduce the data dimension so that the learning process becomes more efficient and optimal. A total of 80 signature images were used in this study, consisting of 60 training data and 20 test data. The results showed that the system was able to achieve an accuracy level of 92.5%. These findings prove that the combination of PCA and JST methods is effective in recognizing digital signature patterns and has the potential to be applied to digital security-based biometric identification systems.

Diseases in primary health services exhibit complex spatial-temporal dynamics due to urbanization and population mobility. Conventional surveillance approaches are difficult to capture these patterns adaptively. Machine learning (ML) based on spatio-temporal modeling offers a solution with the ability to detect disease clusters automatically and with high precision. Research Objectives: This research aims to develop a machine learning model to detect disease hotspots from primary service data in Indonesia, with a focus on improving prediction accuracy, interpretability, and relevance of health policies. Methodology: The primary service dataset for 2024 (5,343 entries) was analyzed using three ML models Gradient Boosting Machine (GBM), Temporal Random Forest (TRF), and Multi-EigenSpot with spatial (village) and temporal (week, month) features. Performance evaluation includes predictive (AUC, F1-score) and spatial (Moran's I, Spatio-Temporal Correlation Index) metrics. Results: The results showed that Multi-EigenSpot achieved the best performance (AUC=0.91; F1=0.86), with the detection of dominant hotspots in Sungai Asam and Beringin Villages. Moran's I value of 0.63 indicates a strong spatial autocorrelation, while STCI=0.57 indicates moderate temporal stability. Conclusions: ML-based spatio-temporal models are effective in identifying hidden disease patterns and have the potential to be integrated into national digital surveillance systems. This approach supports precision public health by providing a scientific basis for real-time location- and time-based intervention policies.

The development of value-added corn-based beverages representation an emerging opportunity within the agribusiness sector, particularly for student-led entrepreneurial initiatives seeking to utilize local agricultural resources. This study examines consumer perceptions of Zeagrain corn milk, a sweet-corn-derived drink positioned as a healthy, practical, and affordable alternative within the ready-to-drink market segment. The research aims to identify key attributes influencing consumer interest, evaluate perceived product performance, and assess the potential competitiveness of Zeagrain as a new agribusiness product. Data were collected using an online quantitative survey targeting respondents aged 17–35 years who represent potential urban consumers. The questionnaire measured demographic characteristics, consumption patterns of similar beverages, perceived importance and performance of product attributes, and purchase intention. The findings are expected to provide insights into consumer expectations regarding taste, packaging, nutritional value, and price. The results further serve as empirical input for improving product development strategies and enhancing the market readiness of Zeagrain. Ultimately, this study contributes to strengthening the commercialization prospects of corn-based beverages and supports innovation efforts among young agripreneurs seeking to optimize local commodities.  

William Shakespeare’s drama Antony and Cleopatra illustrates various aspects of hedonism, especially in the pursuit of love, power, and desire. These behaviors are reflected in the way the characters prioritize personal pleasure over political duty, showing how immediate gratification often clashes with responsibility. This study aims to explore the different types of hedonism represented in the play. A qualitative descriptive approach is used to analyze the dialogues and actions of the main characters, Mark Antony and Cleopatra, based on Weijers’ (2012) framework. The results reveal six categories of hedonism: folk hedonism (30%), value/prudential hedonism (20%), motivational hedonism (15%), normative hedonism (12.5%), utilitarian hedonism (12.5%), and egoist hedonism (10%). Among these, folk hedonism is the most dominant, particularly in Antony and Cleopatra’s pursuit of love and passion without considering the consequences for their political roles. The research shows that Antony and Cleopatra reflects how the pursuit of personal pleasure can shape character development, create conflict, and even lead to tragedy, illustrating timeless patterns where short-term desires overshadow long-term responsibilities.

Tourism is one of the sectors that plays an important role in boosting economic growth through travel activities and destination exploration. Tourists' preferences for nature-based tourism options, such as mountain hiking or beach tourism, are influenced by various factors, ranging from personal experiences and recreational interests to social characteristics. Therefore, a technology-based approach is needed to predict destination choice tendencies more accurately. As artificial intelligence technology develops, deep learning methods have been widely used in classification processes due to their ability to process large amounts of data and recognize complex patterns. In this study, a Multilayer Perceptron (MLP) model is used to classify tourists' preferences between mountain or beach destinations based on a survey dataset. The research stages include data processing, data splitting using a train-test split, model training, and performance evaluation using accuracy, precision, recall, and F1-score. The test results show that the MLP model is capable of achieving an accuracy rate of 99%, confirming that deep learning methods are effective in automatically mapping tourism preference trends. This research is expected to serve as a basis for the development of more personalized travel destination recommendation systems, as well as to support tourism management in formulating targeted promotional strategies.

Artificial intelligence (AI) is currently a rapidly developing technology in all fields, particularly in finance and the military. This study aims to examine the application of Artificial Intelligence (AI) technology to support financial report analysis and internal control within Indonesian Navy (TNI AL) work units. Along with the development of information technology, AI has the potential to provide innovative solutions to improve efficiency, accuracy, and transparency in state financial management, particularly in a military environment that demands high accountability. The research method used was descriptive qualitative with a case study approach in several work units within the Indonesian Navy. Data were obtained through interviews, observations, and a review of relevant documents and literature. The results indicate that the use of AI, such as machine learning and data analytics, can identify unusual financial transaction patterns, predict potential irregularities, and improve the effectiveness of internal oversight. However, the implementation of this technology still faces challenges, such as limited digital infrastructure, the need for human resource training, and the need for policies that support sustainable digital transformation. This study recommends the gradual and strategic integration of AI as part of the reform of the Indonesian Navy's financial management system.

In today's digital era, recommendation systems have become an integral part of supporting consumer purchasing decisions, including in the food and beverage industry. This study aims to develop a product recommendation system for snacks and beverages using the item-based collaborative filtering method. This method was chosen due to its ability to handle large-scale user and product data, as well as its efficiency in providing relevant recommendations based on user consumption patterns. In this study, the system calculates the average user rating and implements   Cosine Similarity to measure the similarity between products, resulting in more accurate recommendations. The system also evaluates the accuracy of recommendations using the Mean Absolute Error (MAE) metric. Based on the results obtained, which is 0.285403 for the average error on 17 items, the developed recommendation system can improve consumers' shopping experience, help them find products that suit their tastes, and support the sales of snacks and beverages products in the market

The development of e-commerce and social commerce has driven significant changes in student shopping behaviour, including at FEB UNDARIS. Ease of access, digital promotions, and the influence of social media have led students to shop online more frequently, even impulsively. This study aims to analyse how attitudes, subjective norms, and perceived behavioural control interact in shaping students' online shopping behaviour using the Theory of Planned Behaviour (TPB) framework. This study uses a descriptive qualitative method with in-depth interviews with ten students who actively shop online. The data were analysed to understand the experiences, perceptions, and social factors that influence their decisions in digital transactions. The results show that positive attitudes towards efficiency and promotions, social pressure from friends and influencers, and high perceived behavioural control due to technological convenience work simultaneously to reinforce online shopping intentions and actions. These three TPB components support each other and trigger increasingly impulsive consumption patterns in the digital environment.

Indonesian families are currently still faced with various challenges, including the low knowledge of mothers about childcare, which can have an impact on child development. This is crucial and a sign that there is a need to improve competence as parents, therefore the Great Parents School provides a way to overcome problems in childcare practices. This study aims to explain the transformation of young mothers who have participated in the Great Parents School program. This study uses a qualitative approach with a descriptive method, the informants in this study are young mothers who have undergone the Great Parents School program and accompanying facilitators, while the data collection process uses observation, interviews, and documentation with the research location in Sumbersari District, Jember Regency. The results of this study show that the empowerment process refers to the ACTORS theory, namely authority, self-confidence, trust, opportunity, responsibility, and support for mothers who have attended the Great Parents School. Mothers who have attended the Great Parents School have experienced improvements in their knowledge, attitudes, and skills related to childcare. This improvement can be seen through their understanding of the role of parents, the application of family functions such as instilling religious values, compassion, and protection, as well as the application of parenting and discipline patterns, and an understanding of communication skills. Therefore, it can be concluded that the Great Parents School serves as a bridge for mothers to become more empowered through improvements in childcare.

The Special Region of Yogyakarta (DIY) is characterized by high seismic activity due to its proximity to the subduction zone and the presence of active fault systems, particularly the Opak Fault. The 2006 Yogyakarta earthquake revealed significant vulnerability in local building structures and highlighted the complex geological conditions governing seismic wave propagation. This study aims to calculate and map the Peak Ground Acceleration (PGA) distribution in Prambanan District, Klaten Regency—one of the areas closest to the 2006 earthquake source. PGA values were estimated using the McGuire attenuation relationship, based on a moment magnitude of Mw 6.3 and the hypocentral distance to 88 observation points distributed at approximately 900-meter intervals. The resulting PGA map indicates values ranging from 26.7 to 31.7 gal, with a clear spatial trend showing increasing intensity from the northern to the southern parts of the study area. Higher PGA values occur in regions near the Opak Fault and in areas dominated by unconsolidated volcanic deposits of the young Merapi formation. These loose sediments amplify seismic waves, resulting in stronger ground motion compared to areas composed of more compact sedimentary rocks. The spatial pattern of PGA corresponds well with the distribution of structural damage recorded during the 2006 earthquake. The findings emphasize the significant role of local geology and fault proximity in shaping seismic hazard levels. Consequently, this study provides essential insights for disaster mitigation strategies, land-use planning, and structural vulnerability assessment within the Prambanan area.

The limited number of studies examining organizational communication patterns within technical government institutions a research gap, particularly in understanding how communication mechanisms are implemented by public relations units in technical based governmental organizations. This research aims to identify the communication patterns applied by the Public Relations Unit of the Geological Survey Center (PSG) in Bandung, as well as the supporting factors and challenges encountered in its implementations. The study employs a qualitative descriptive approach wih data collected through interviews, observations, and literature review. The findings reveal that the organizational communication pattern operates in multiple directions using both formal communication channels, such as official letters and scheduled meetings through the Nadine system, and informal channels, including face-to-face interactions and digital messaging through WhatsApp. Supporting factors in the communication process include leadership support, a well-defined organizational structure, a collaborative work culture, and the availability of adequate communication facilities and media. However, several constraints remain, including technical and non-tehcnical challenges such as varying work priorities, inconsistents responses times, and unstable network connectivity during field activities.

This study explores the major challenges faced by moral education in the modern era, particularly within Madrasah Ibtidaiyah, where rapid technological advancement, globalization, and shifting patterns of student interaction have significantly influenced the traditional process of moral development. The purpose of this research is to analyze teachers’ strategies in revitalizing moral education, identify the supporting and inhibiting factors in its implementation, and evaluate its impact on students’ discipline. Employing a qualitative approach with a case study design, data were collected through in-depth interviews with the school principal, Islamic ethics teachers, and students, as well as observations of daily moral habituation practices within the school environment. The findings indicate that effective revitalization of moral education occurs through an integration of teacher role modeling, consistent habituation of moral practices, and value internalization supported by interactive learning methods. These strategies contribute to improved student discipline, greater independence, and more stable behavioral patterns. However, the effectiveness of these efforts is still influenced by external factors such as excessive gadget use and limited continuity of moral guidance at home. The study provides an integrative and adaptive model of moral education that aligns with the characteristics of the digital generation and emphasizes the essential collaboration between teachers, schools, and families. The results highlight the importance of a responsive, contextually relevant approach to moral development that meets the evolving needs and challenges of 21st-century learners.

The rapid development of digital media has created a communication pattern in which information spreads quickly and often without verification. In this situation, hoaxes and disinformation have emerged as a serious threat that affects social trust, religious harmony, and individual behavior in online spaces. This study aims to explore Qur’anic principles that are relevant for building critical awareness, especially through the momentum of Nuzul Qur’an as an illustration of revelation that guides people in understanding messages accurately. The research uses a qualitative descriptive-analytical design with a thematic tafsir approach to examine verses related to verification, prohibition of false speech, and speaking truth. Primary sources consist of the Qur’an and classical as well as modern commentaries, while secondary sources include books and scientific articles on digital literacy and misinformation. The findings show that Qur’anic principles such as tabayyun, avoidance of false accusation, and responsibility in communication are aligned with core elements of digital literacy that require users to identify reliable sources and evaluate messages before sharing. The conclusion suggests that integrating Qur’anic ethical values into digital literacy programs can reduce the circulation of hoaxes and strengthen a culture of truth in digital interaction.

This study aims to analyze and compare the price responsiveness of broiler chicken meat and native chicken meat in relation to household consumption patterns in Tarogong Kidul District, Garut Regency. A quantitative approach was employed using simple linear regression analysis based on primary data obtained through observations and interviews conducted in traditional markets. The analysis examines the extent to which price changes influence the demand for both commodities. The results indicate that broiler chicken shows a very strong relationship between price and demand, reflected in an R² value of 0.963. Statistical testing further demonstrates that price has a significant effect on broiler chicken demand (0.018 < 0.05), indicating that its demand is elastic and highly sensitive to price fluctuations. In contrast, native chicken shows an R² value of 0.698 and an insignificant price effect on demand (0.164 > 0.05), suggesting inelastic demand that remains relatively stable despite price changes. These findings reveal that consumers adjust their broiler purchase quantities more quickly in response to price changes, whereas native chicken consumption is more strongly influenced by taste preferences and habitual factors. The study concludes that there is a clear difference in price sensitivity between the two types of chicken. The implications of this research include the need for government price stabilization policies for broiler chicken to maintain household affordability, as well as quality improvement and marketing strategies for native chicken producers to strengthen competitiveness amid changing consumer demand.

This study aims to analyze public relations (PR) management practices and the leadership style of the Vice Principal for Public Relations (Waka Humas) in building a positive school image and establishing partnerships with industry sectors. The focus of the research lies in communication strategies, coordination patterns, and leadership approaches implemented to support school development programs based on industry collaboration. This research employs a qualitative approach using a case study method, with data collected through in-depth interviews, observations, and documentation analysis. The findings reveal that the Vice Principal for Public Relations applies strategic PR planning, including situation analysis, goal formulation, program implementation, and evaluation processes. Furthermore, a transformational leadership style is predominantly applied, characterized by the ability to motivate, inspire teachers and staff, and foster a collaborative culture in achieving school goals. This leadership approach has been proven effective in increasing stakeholder participation, expanding industrial networks, and strengthening the school’s image as an adaptive institution responsive to the needs of the workforce. Nevertheless, the study also identifies challenges related to limited resources, particularly concerning infrastructure support and time allocation for program implementation. These findings highlight the importance of enhancing the capacity of school public relations roles to ensure sustainable industrial partnerships and a strong institutional reputation.