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The use of hermeneutics in Qur'anic studies has long generated debate among Muslim scholars. Some view hermeneutics as a methodological tool that can bridge the historical distance between the revealed text and contemporary life, whereas others regard it as an epistemological threat that may weaken the authority of the Qur'an. This article aims to analyze the arguments of both proponents and critics and to identify possible areas of convergence. Using a descriptive-analytical approach and library research, this study examines relevant works by scholars who support and oppose the application of hermeneutics in Qur'anic interpretation. The findings show that proponents, such as Fazlur Rahman, Nasr Hamid Abu Zayd, and Mohammed Arkoun, argue that hermeneutics can enrich interpretive methods and help contextualize meaning. Conversely, critics, such as Adian Husaini and scholars who emphasize the authority of established tafsir traditions, argue that hermeneutics emerged from the problems of Biblical interpretation and therefore cannot be applied directly to the Qur'an, which is believed to retain its authenticity. The study concludes that the debate stems from different theological assumptions about text, revelation, and interpretation. It recommends the selective adaptation of hermeneutics as a supporting analytical tool, not as a replacement for the science of tafsir.

Problems that often occur in brooch pins are bent wire or detached from the hook, also the possibility of the brooch coming off the pin when worn as a problem encountered. The purpose of fabrication is to obtain a 60 mm long brooch pin, 0.5 mm diameter, AISI 1045 material. Fabrication methods include: brooch pin design; selection of AISI 1045 material for 0.5 mm diameter wire and for 0.3 mm plate; cutting wire 94 mm long and sharpening one end; cutting the brooch pin end hook plate; forming the wire into a circle with a 4 mm hole for one winding; cutting a 0.3 mm thick plate in the shape according to the design; forming a pointed end hook with a punch and die; pressing the base of the wire to one side of the shape plate; electroplating with Chromium solution material; ordering and installing the customer's taste brooch; unification between the brooch and the pin stem; and quality-dimensional inspection. The fabrication results are in the form of a 60 mm long brooch pin, 0.5 mm diameter, AISI 1045 material coated with Chromium with a total cost of IDR 290,-/piece and a production duration of 90 seconds/piece which means that the brooch pin can be used for various desired accessories.

The urgency of this research stems from the knowledge gap regarding contextual factors contributing to the underuse of learning media in rural elementary schools, which has not been adequately addressed in previous research, which has tended to focus on urban contexts. This study aims to examine teachers' perceptions at Sugayang Public Elementary School regarding the underuse of learning media in the learning process, as well as the factors that contribute to it. The method used was a descriptive qualitative method, utilizing in-depth interviews as a data collection technique. The data were then analyzed using data reduction, data display, and conclusion drawing techniques according to Miles and Huberman. The results showed that teachers experienced difficulties in using technology, difficulties in creating learning media, and the perception that using media was time-consuming. This reveals an important pattern that the underuse of learning media is a systematic problem rooted in the TPACK gap that is not supported by practical time management solutions. These findings imply that changes in learning practices will not occur simply through the provision of generic technology tools or training; rather, bottom-up and contextual solutions are needed. The novelty of this research lies in the in-depth qualitative approach applied to the under-researched context of rural elementary schools, which has not been studied before. This research contributes through recommendations for the implementation of a peer-mentoring program and the development of a ready-to-use digital learning media bank, thus offering valuable insights for future research with relevant stakeholders.

Background: Community nursing is a specialty field that combines nursing science skills, public health sciences, and social assistance in addressing individual and family health problems, including non-communicable diseases such as gout arthritis. Gout arthritis is a metabolic disease characterized by pain and joint inflammation due to the accumulation of purine crystals (hyperuricemia). The WHO reports a prevalence of gout arthritis reaching 3.74% globally, while in Indonesia the prevalence reaches 11.9% based on health worker diagnosis. In Brebes Regency, the prevalence reaches 13.67%, with 3,078 sufferers out of 22,550 productive-age population. Objective: To provide comprehensive community nursing care to Ny. R with musculoskeletal system disorder: gout arthritis in Tonjong Village, Tonjong District, Brebes Regency. Method: This study uses a case study approach with data collection through interview, observation, physical examination, and documentation study conducted on December 26–28, 2025. Results: Assessment findings showed that Ny. R, a 60-year-old woman, had a history of gout arthritis for 3 months with uric acid levels of 9.6 mg/dL, complaining of pain and aching in the left foot with pain scale 3. Two nursing diagnoses were established: acute pain and knowledge deficit. Nursing interventions included pain management, uric acid level monitoring, lemongrass stem decoction foot soak complementary therapy, and health education using leaflets. After 2 days of implementation, uric acid levels decreased to 8.2 mg/dL and pain scale decreased to 2. Conclusion: Community nursing care through complementary therapy (lemongrass stem decoction foot soak) and health education effectively reduced pain and improved knowledge about gout arthritis in Ny. R.

Dengue fever remains a major global health challenge, particularly in tropical regions, due to the high transmission of Dengue virus by Aedes aegypti and the limited sustainability of current control strategies. Artocarpus odoratissimus, an endemic Bornean plant, contains diverse secondary metabolites with potential pharmacological activities; however, a systematic synthesis of its biomedical relevance to Dengue is still lacking. This study aimed to systematically evaluate the biomedical potential of A. odoratissimus in Dengue prevention and control through a systematic literature review. This study employed a systematic literature review method following the PRISMA 2020 guidelines. Literature searches were conducted in Scopus, ScienceDirect, SpringerLink, PubMed, Google Scholar, Garuda, SINTA, and other relevant scientific databases for publications from January 2016 to February 2026. A total of 303 records were identified, and after duplicate removal, title and abstract screening, and full-text eligibility assessment, 23 studies were included for narrative synthesis. The findings revealed that A. odoratissimus contains major bioactive compounds, including flavonoids, phenolics, arylbenzofurans, stilbenoids, and prenylated chalcones, which demonstrate antioxidant, anti-inflammatory, immunomodulatory, and potential antiviral activities based on in vitro and molecular docking studies. Fruit peel, seeds, and stem bark exhibited the strongest biological evidence, particularly in reducing oxidative stress, inhibiting inflammatory mediators, and potentially interacting with Dengue viral target proteins. Furthermore, several species within the Artocarpus genus showed larvicidal and ovicidal activities against Aedes aegypti, highlighting the potential development of A. odoratissimus as a plant-based biolarvicide candidate.

Dengue fever remains a major global health challenge, particularly in tropical regions, due to the high transmission of Dengue virus by Aedes aegypti and the limited sustainability of current control strategies. Artocarpus odoratissimus, an endemic Bornean plant, contains diverse secondary metabolites with potential pharmacological activities; however, a systematic synthesis of its biomedical relevance to Dengue is still lacking. This study aimed to systematically evaluate the biomedical potential of A. odoratissimus in Dengue prevention and control through a systematic literature review. This study employed a systematic literature review method following the PRISMA 2020 guidelines. Literature searches were conducted in Scopus, ScienceDirect, SpringerLink, PubMed, Google Scholar, Garuda, SINTA, and other relevant scientific databases for publications from January 2016 to February 2026. A total of 303 records were identified, and after duplicate removal, title and abstract screening, and full-text eligibility assessment, 23 studies were included for narrative synthesis. The findings revealed that A. odoratissimus contains major bioactive compounds, including flavonoids, phenolics, arylbenzofurans, stilbenoids, and prenylated chalcones, which demonstrate antioxidant, anti-inflammatory, immunomodulatory, and potential antiviral activities based on in vitro and molecular docking studies. Fruit peel, seeds, and stem bark exhibited the strongest biological evidence, particularly in reducing oxidative stress, inhibiting inflammatory mediators, and potentially interacting with Dengue viral target proteins. Furthermore, several species within the Artocarpus genus showed larvicidal and ovicidal activities against Aedes aegypti, highlighting the potential development of A. odoratissimus as a plant-based biolarvicide candidate.

Nature tourism is one of the sectors that plays an important role in supporting the development of regional tourism, including in Lahat Regency, which has significant waterfall tourism potential. Currently, many visitors share their reviews and experiences through digital platforms such as Google Maps. This review can be used as a source of information to understand the public's evaluation of the quality of tourist attractions. This study aims to examine public perception of tourist attractions in Lahat Regency using the Support Vector Machine (SVM) method. Research data were collected through scraping from Google Maps, totaling 500 reviews from five tourist attractions, namely Curup Maung, Curup Buluh, Senyawe Waterfall, Panjang Waterfall, and Green Canyon. The research stages include data preprocessing, consisting of cleaning, case folding, normalization, tokenization, stopword removal, and stemming. After that, feature extraction was carried out using the TF-IDF method and the classification process using the SVM algorithm. Based on the research results, the Support Vector Machine (SVM) method is able to perform sentiment classification quite well, although the accuracy level varies for each tourist attraction. Curup Maung and Panjang Waterfall achieved the highest accuracy level of 90%. Nevertheless, most visitor reviews were dominated by negative sentiments. This indicates that there are still several aspects that need to be improved, particularly related to tourist facilities and services. This research is expected to serve as a consideration for tourism managers and local governments in efforts to improve management quality as well as the development of tourism in Lahat Regency.

The quality of rice that is suitable for consumption, one of which is determined by the absence of associated components when the rice is in storage. Rice storage is carried out by means of long shelf life and good rice quality. Damage to rice due to pest attacks causes a decrease in quality and quantity. Environmentally friendly efforts are needed to control the rice weevil Sitophilus oryzae using vegetable materials. This study sought to ascertain the death rate of rice weevils treated with lemongrass stem (Cymbopogon citratus), bay leaves (Syzygium polyanthum), and pandan leaves (Pandanus amaryllifolius). The study employed a fully randomized design with three treatments in the form of simplicia plant components. There were 21 study units because each treatment included seven repetitions. Each treatment used 20 rice weevil imago breeding results which were infested in a jar containing 200 g of rice for 4 weeks in the laboratory. The use of pandan leaf, bay leaf, and lemongrass simplicia at 7 days after treatment showed the proportion of rice weevil mortality was 59,29%, 39,29%, and 50,00%, respectively. As for the observations of 14 day after treatments, 21 day after treatments, and 28 day after treatments showed that the mortality rate of all rice beetles was above 50%. Regarding the percentage of rice powder, hollow rice, and rice weight loss, the findings of observations on rice weevil mortality did not reveal any significant variations across all treatments.

Poor soil quality and inefficient nutrient utilization remain major constraints in tomato (Solanum lycopersicum L.) cultivation, often resulting in reduced plant growth, lower productivity, and suboptimal fruit quality. This study aims to evaluate the growth performance of rose tomatoes through the integration of open-field cultivation and hydroponic planting systems. The research methods included land preparation using the Pythagorean technique to ensure proper spacing and planting layout, the application of organic fertilizers to improve soil fertility, and the transition to a hydroponic drip irrigation system using rockwool as the growing medium during weeks 1 to 7 of plant development. Plant growth parameters, including plant height, leaf development, stem vigor, and overall plant health, were observed throughout the cultivation period. The results indicated that the combination of appropriate soil management practices and precise nutrient delivery in the hydroponic system significantly enhanced nutrient uptake and supported healthy plant growth. Furthermore, the drip irrigation system helped optimize water use efficiency while reducing nutrient losses. This integrated cultivation approach demonstrated its potential as an effective solution for maintaining crop quality and productivity, particularly in areas with limited land resources. Overall, the findings suggest that integrated management practices can provide a practical, efficient, and sustainable strategy for farmers seeking to improve horticultural production in modern agricultural systems.

The character crisis among students has become a serious concern, marked by the rise of deviant behaviors such as bullying, drug abuse, and criminal acts committed by minors. This phenomenon underscores the urgent need to strengthen religious character through the active role of teachers in the school environment. This study aims to describe the role of teachers in shaping the religious character of Grade III students at Madrasah Ibtidaiyah Ma'had Al-Zaytun, as well as to identify the supporting and inhibiting factors in the character formation process. A qualitative approach was employed, with data collected through in-depth observation, interviews, and documentation. Research subjects were determined using snowball sampling, while data validity was verified through source triangulation, technique triangulation, and time triangulation. The findings reveal that teachers play multiple strategic roles in shaping students' religious character, including acting as educators, instructors, mentors, motivators, evaluators, facilitators, and advisors, as well as serving as role models and fostering habitual religious practices. Supporting factors in religious character formation include the availability of school facilities and infrastructure, along with various religious activities within the school environment. Inhibiting factors consist of internal factors related to students' individual characteristics and external factors stemming from the home environment. These findings affirm that the teacher's role is multidimensional and requires synergy between the school and family environment to effectively cultivate strong religious character in students.

The growth of information technology has driven changes in consumer behavior, one of which is through e-commerce platforms such as Shopee. This phenomenon has generated a large number of customer reviews, including those for local cosmetic products such as Wardah. These reviews serve as an important source of information for understanding customer perceptions and satisfaction levels. However, manual analysis of large and linguistically diverse datasets is inefficient and potentially subjective. This study aims to implement the multi-category Naive Bayes algorithm to classify the sentiment of Wardah product reviews on Shopee into three categories: positive, negative, and neutral. The data were collected using a web scraping technique and processed through a series of preprocessing stages including case folding, tokenization, stopword removal, stemming, and text cleaning. Subsequently, term weighting was performed using the TF-IDF method prior to classification. Model performance was evaluated using a confusion matrix as well as accuracy, precision, and recall metrics. The results indicate that the multi-category Naive Bayes algorithm achieved an accuracy of 86.00%, a precision of 86.63%, and a recall of 98.24%. This approach can assist business practitioners in objectively understanding customer opinions and support decision-making in business strategy and product development.

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.

The management of Uninhabitable Houses (Rumah Tidak Layak Huni/RTLH) in Sikka Regency faces a critical challenge due to the high number of inadequate housing units distributed across both urban and rural areas with complex geographical characteristics. The primary obstacle to effective policy implementation stems from the limited capacity of local government interventions in improving housing quality on a sustainable basis, which is largely caused by poor-quality housing data and the absence of an integrated single-data information system. This policy paper aims to formulate an acceleration strategy for addressing RTLH through the reform of data governance that is accurate, efficient, and accountable. Using Eugene Bardach’s (2012) policy analysis framework to evaluate alternative solutions based on technical feasibility, economic viability, political acceptability, and administrative operability, this study identifies the transformation of intervention mechanisms based on the National Integrated Socio-Economic Data (Data Tunggal Sosial Ekonomi Nasional/DTSEN) as the most appropriate policy option. To ensure long-term sustainability, the paper recommends a Phased Convergence Strategy, whereby data cleansing and matching processes based on DTSEN are implemented at the upstream level and subsequently integrated into the “One Data RTLH Sikka” digital platform in the medium term. This operational strategy is further strengthened through the enactment of a Regent Regulation (Peraturan Bupati) on Data Governance and the Mechanism for Determining Eligible Beneficiaries of Decent Housing Assistance, providing a legally binding framework for policy implementation. By positioning village and urban ward governments as the frontline actors in conducting by-name-by-address (BNBA) field verification, the policy minimizes the risks of inclusion and exclusion errors, eliminates budget overlaps, and optimizes local innovative programs such as the TERKASIH House Assistance Scheme (Terima Kunci Siap Huni – “Receiving the Key to a Ready-to-Occupy House”). The implementation of these recommendations is expected to promote data-driven governance that accelerates the reduction of extreme poverty and enhances the effectiveness of housing assistance programs in Sikka Regency.

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.

This study aims to analyze public relations strategies in the implementation of the Mental Revolution Program through Instagram at the Coordinating Ministry for Human Development and Cultural Affairs of the Republic of Indonesia. The Mental Revolution represents an effort to transform public mindsets, attitudes, and behaviors based on the values of integrity, work ethic, and mutual cooperation in order to build a progressive and competitive nation. This research employs a descriptive qualitative approach with a case study method. Data were collected through observation, in-depth interviews, documentation, and triangulation to ensure comprehensive findings. The results indicate that the implemented public relations strategies have optimally utilized social media as a means of public communication, particularly in reaching younger audiences. These strategies include the development of positive content, cross-sector collaboration, and the use of media relations to expand information dissemination. The SWOT analysis reveals that the main strengths lie in effective team coordination, structured communication strategies, and a strong organizational culture, while weaknesses include limited human resources and insufficient technological support. Opportunities arise from extensive networks with various institutions and media, whereas threats stem from public perceptions and limited communication competencies. In practice, the Mental Revolution Program is implemented participatively through various initiatives such as Indonesia Serving, Clean, Orderly, Independent, and United, which are disseminated via Instagram. However, its implementation has not been evenly distributed across regions and has only reached approximately 70%, due to budget constraints and varying levels of commitment among local governments. Therefore, the success of this program largely depends on synergy among stakeholders and consistency in internalizing transformative values within society.

Sweet corn (Zea mays saccharata Sturt.) is an increasingly popular horticultural commodity in Indonesia, attracting both farmers and consumer. This study aims to evaluate the effectiveness of single‑micronutrient fertilizer Mn‑EDTA (12%) in enhancing the growth and yield of sweet corn (Zea mays saccharata Sturt.). The treatments consisted of control, standard NPK, 0.25 NPK, 0.50 NPK, 0.75 NPK, and 1.00 NPK. The experimental findings demonstrated that the application of single‑micronutrient Mn‑EDTA (12%) fertilizer had a highly significant effect on vegetative growth and yield components of sweet corn, with statistically higher values compared with the control treatment. In general, fertilizer dosages equivalent to 0.25–1.00 NPK produced greater plant height, stem diameter, leaf number, ear length, ear diameter, biomass weight, ear weight with husk, ear weight without husk, plot yield, and productivity than the control. The RAE calculation indicated that the fertilizer was effective when applied at dosages equivalent to 0.75 and 1.00 NPK. The highest effectiveness was observed at the 1.00 NPK dosage, with an RAE value of 101%. Notably, the application of Mn‑EDTA (12%) fertilizer at the 1.00 NPK dosage provided significant field effectiveness, as reflected by the RAE value of 101%. This result implies that the use of single‑micronutrient Mn‑EDTA (12%) fertilizer at the 1.00 NPK dosage increased yield by 1.01 times compared with the yield improvement obtained from the reference fertilizer relative to the control treatment.

This article aims to reconstruct legal awareness and social justice in the context of a contemporary rule of law through the integration of economic law, digital law, civil law, criminal law, and constitutional law within the framework of citizenship rights and Islamic Sociological Jurisprudence Theory. The main problem of this research stems from the fact that the development of the modern legal system tends to be sectoral, formalistic, and not fully responsive to social change, unequal access to justice, and digital transformation that affects the relationship between citizens and the law. This research uses a normative legal research method with a conceptual, legislative, and sociological approach. The results of the study indicate that legal awareness is not simply understood as formal compliance with norms, but must be developed as a substantive awareness oriented towards social justice, protection of citizenship rights, and public welfare. From the perspective of Islamic Sociological Jurisprudence, law is positioned not only as a regulatory instrument, but also as a means of social transformation based on the values ​​of justice, moral responsibility, and siding with the interests of society. Integration across legal branches is crucial for the legal system to more comprehensively address issues related to economics, digitalization, civil relations, criminal enforcement, and state governance. Therefore, the reconstruction of legal awareness must be directed toward establishing a legal paradigm that is integrative, humanistic, adaptive, and socially just.

This study presents a systematic qualitative literature review examining regulatory, ethical, and organizational challenges in the adoption of artificial intelligence (AI) for letter of credit (LC) automation in trade finance. Synthesizing prior interdisciplinary research, the review finds that AI technologies—such as machine learning and natural language processing—offer substantial efficiency, accuracy, and transparency gains in documentary credit examination. However, these benefits are constrained by regulatory uncertainty stemming from legacy legal frameworks, ethical concerns related to algorithmic opacity, bias, and accountability, and organizational challenges involving trust, governance, and workforce readiness. The findings highlight that AI-driven LC automation constitutes a socio-technical transformation rather than a purely technological upgrade, requiring alignment between evolving regulation, responsible AI governance, and organizational change management. This study contributes to the trade finance and digital transformation literature by providing an integrated perspective on how transparency can be institutionalized without undermining trust in automated financial decision-making

This research investigates how profitability, leverage, activity levels, and company scale impact financial distress in property and real estate firms traded on the Indonesia Stock Exchange. The selection of this sector stems from its high exposure to economic ups and downs, leaving its businesses particularly prone to financial troubles. Independent factors in the analysis include profitability, leverage, activity, and firm size, with financial distress serving as the outcome variable. Samples were drawn via purposive sampling from property and real estate entities listed on the Indonesia Stock Exchange over the 2022–2024 timeframe. Adopting a quantitative design, the study applies multiple linear regression as its core analytical tool. STATA version 17 handled the data analysis. Results show that, taken together, the independent variables exert a significant impact on financial distress. Ultimately, firms should optimize their financial metrics and pursue business growth to mitigate financial distress risks.

The establishment of national territorial boundaries is a strategic priority to safeguard sovereignty, maintain security stability, and strengthen bilateral relations between Indonesia and Malaysia as well as Timor-Leste. As of 2024, there remain nine Outstanding Boundary Problems (OBP) with Malaysia and two unresolved segments with Timor-Leste. These issues stem from the continued relevance of outdated colonial agreements, limited diplomatic capacity, weak inter-agency coordination, and minimal support from modern surveying technology. Based on an analysis of four policy alternatives using the criteria of effectiveness, efficiency, and long-term impact, the Strengthening of Intensive Bilateral Diplomacy has been identified as the priority policy. Implementation is directed to the Badan Nasional Pengelola Perbatasan (BNPP) as the main coordinator, supported by regulatory frameworks, diplomatic resources, and cross-ministerial/institutional coordination. Through this strategy, the resolution of pending boundary segments can be accelerated, legal certainty over national territory can be strengthened, security stability in border areas can be improved, and bilateral relations can become closer. Furthermore, Indonesia needs to strengthen diplomatic strategies, leverage technology, and enhance inter-agency coordination to accelerate the resolution of national border disputes. This policy directly contributes to achieving territorial sovereignty and sustainable development toward Indonesia Vision 2045.