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Digital transformation in public services has encouraged government institutions to develop technology-based services, including the Online Police Record Certificate (SKCK) service at Kupang City Regional Police Resort. This study aims to analyze the effectiveness of the Online SKCK service as an administrative requirement at the Kupang City Regional Police Resort. The research employed a qualitative approach with a descriptive method. Data were collected through observation, interviews, and document analysis involving service officers and users of the Online SKCK service. Data were analyzed using an interactive model consisting of data reduction, data display, and conclusion drawing. The findings indicate that the Online SKCK service has improved accessibility, service efficiency, and transparency through the implementation of the PRESISI POLRI application. Based on the effectiveness indicators, namely program understanding, target accuracy, timeliness, goal achievement, and real change, the service can be categorized as moderately effective. Target accuracy and real change emerged as the strongest indicators, while program understanding and timeliness still face several challenges, including limited digital literacy among users, application system disruptions, and data verification issues. Nevertheless, the Online SKCK service has provided significant benefits in supporting the modernization of public services. The study concludes that improving system quality, strengthening public outreach, and developing a more integrated service system are necessary to optimize the effectiveness of the Online SKCK service at the Kupang City Regional Police Resort.

The empowerment of Micro, Small, and Medium Enterprises (MSMEs) is a strategic effort to enhance the capacity and independence of business actors in supporting sustainable economic development. However, based on data from Rumah BUMN Aceh Utara, out of a total of 413 assisted MSMEs, only 9.16% have successfully upgraded their business status, while 90.84% have not yet done so. This study aims to describe MSME empowerment through the assistance program of Rumah BUMN Aceh Utara and to identify its supporting and inhibiting factors. This research employs a qualitative method with a descriptive approach. Data were collected through interviews, observations, and documentation involving Rumah BUMN managers and MSME actors, and were analyzed using the interactive model of Miles and Huberman. The results show that MSME empowerment in Rumah BUMN Aceh Utara is based on Suharto’s theory, which consists of three main approaches, namely empowering through training and mentoring that contributes to the improvement of business actors’ capacities, protecting through business legality facilitation, and supporting through the provision of production facilities, packaging machines, access to capital, promotion, and MSME gallery facilities, although these have not yet been fully optimized. The supporting factors of MSME empowerment include institutional support, technological development, and MSME participation, while the inhibiting factors include limited human resources, limited funding, and low participation of some MSME actors. This study emphasizes the importance of improving the quality of mentoring, optimizing the utilization of facilities, and increasing MSME participation to support the sustainability of empowerment programs.

Dysphagia in extremely elderly patients represents a significant clinical challenge because it is frequently associated with frailty, malnutrition, and an increased risk of aspiration. Multifactorial etiologies and atypical clinical manifestations may complicate diagnosis and delay appropriate management. This study aimed to describe the diagnostic evaluation and clinical findings of dysphagia in an extremely elderly patient through a case report supported by a scoping review. A 105-year-old woman with chronic progressive dysphagia underwent comprehensive assessment, including physical examination, upper gastrointestinal endoscopy, histopathological evaluation, and chest radiography. Relevant literature on dysphagia in geriatric populations was reviewed to provide contextual understanding of diagnostic challenges and underlying etiologies. The evaluation revealed chronic active gastritis and a hamartomatous polyp in the gastroesophageal region without evidence of malignancy. Comprehensive assessment successfully excluded malignant and acute obstructive causes, emphasizing the complexity of dysphagia diagnosis in extremely elderly individuals with frailty and aspiration risk. These findings underscore the importance of endoscopic and histopathological examinations in distinguishing benign from malignant etiologies and support early recognition of multifactorial non-malignant causes to optimize clinical management and reduce the risk of adverse outcomes in this vulnerable population

The area and distance between buildings at POLINELA Campus make the presence of adequate connector roads an important necessity to support the mobility of the academic community. This study aims to optimize the scheduling of flexible pavement construction for the POLINELA Connector Road using the Critical Path Method (CPM) based on Microsoft Project 2021. The research method used is descriptive quantitative by processing the Budget Plan (RAB) data into a project schedule consisting of 11 main activities. CPM analysis is used to determine the sequence of work, dependencies between activities, the critical path, and project completion time. The results show that the total project duration is 23 calendar days (May 11–June 6, 2026). CPM analysis identified 10 activities on the critical path with zero float, while embankment work is a non-critical activity with time flexibility. Applying a Start-to-Start (SS) relationship with a 3-day lag between excavation and embankment work allows parallel implementation, reducing the project duration by 4 days (14.8%) compared to the conventional Finish-to-Start (FS) scenario. These results indicate that implementing CPM through Microsoft Project 2021 can increase execution time efficiency, simplify schedule control, and support decision-making in road construction project management.

This study aims to examine the implementation of policies regarding the use of the e-Kelurahan feature in the Sangu Palu application in Taipa Village. The study employs George C. Edward III’s policy implementation theory, which consists of four dimensions: communication, resources, disposition, and bureaucratic structure. A qualitative descriptive approach was used, with data collected through observation, in-depth interviews, documentation, and literature review involving nine informants. The findings indicate that the implementation of the e-Kelurahan policy has not yet run optimally. The main obstacle lies in the communication aspect, particularly the lack of direct public socialization regarding the use of the application, resulting in low public understanding and limited utilization of digital services. In addition, training for village officials has not been conducted continuously, as it was only provided during the initial implementation stage. Therefore, periodic retraining is needed to improve technical competence and evaluate service performance. Although the aspects of disposition and bureaucratic structure have generally functioned well, they have not been sufficient to optimize digital service utilization. These findings are consistent with the Electronic-Based Government System (SPBE) evaluation results, which place Palu City in the “sufficient” category, indicating the need for further improvement in digital service implementation.

A chronic metabolic disease characterized by elevated blood glucose levels due to insulin resistance or impaired insulin secretion is classified as type 2 diabetes mellitus. The prevalence of diabetes continues to rise each year and has become one of the major challenges in global health due to its potential to cause serious complications, such as cardiovascular disease, kidney failure, neuropathy, and vision impairment. In addition to pharmacological therapy, the use of herbal plants is increasingly being developed as a complementary therapy because they are considered safer, more readily available, and contain bioactive compounds with potential antidiabetic properties. This review article aims to assess the effectiveness of several herbal plants namely cinnamon (Cinnamomum cassia), fenugreek (Trigonella foenum-graecum), bitter melon (Momordica charantia), and moringa (Moringa oleifera) in aiding the management of type 2 diabetes mellitus based on various research findings. This study employs a literature review method by collecting and analyzing various national and international scientific publications related to the antidiabetic activity of these four plants. The review results indicate that all plants have potential as adjunct therapies for diabetes because they contain active compounds such as flavonoids, polyphenols, cinnamaldehyde, charantin, quercetin, trigonelline, and saponins, which can help reduce blood glucose levels, optimize cellular response to insulin, increase GLUT4 activity, and help minimize oxidative damage. Based on the study results, moringa and cinnamon plants demonstrated the most consistent effectiveness in contributing to blood sugar control in individuals with type 2 diabetes mellitus. Thus, these herbal plants have the potential to be used as complementary therapies in the management of type 2 diabetes mellitus; however, their use must still adhere to proper dosing and should not replace primary medical therapy.

A chronic metabolic disease characterized by elevated blood glucose levels due to insulin resistance or impaired insulin secretion is classified as type 2 diabetes mellitus. The prevalence of diabetes continues to rise each year and has become one of the major challenges in global health due to its potential to cause serious complications, such as cardiovascular disease, kidney failure, neuropathy, and vision impairment. In addition to pharmacological therapy, the use of herbal plants is increasingly being developed as a complementary therapy because they are considered safer, more readily available, and contain bioactive compounds with potential antidiabetic properties. This review article aims to assess the effectiveness of several herbal plants namely cinnamon (Cinnamomum cassia), fenugreek (Trigonella foenum-graecum), bitter melon (Momordica charantia), and moringa (Moringa oleifera) in aiding the management of type 2 diabetes mellitus based on various research findings. This study employs a literature review method by collecting and analyzing various national and international scientific publications related to the antidiabetic activity of these four plants. The review results indicate that all plants have potential as adjunct therapies for diabetes because they contain active compounds such as flavonoids, polyphenols, cinnamaldehyde, charantin, quercetin, trigonelline, and saponins, which can help reduce blood glucose levels, optimize cellular response to insulin, increase GLUT4 activity, and help minimize oxidative damage. Based on the study results, moringa and cinnamon plants demonstrated the most consistent effectiveness in contributing to blood sugar control in individuals with type 2 diabetes mellitus. Thus, these herbal plants have the potential to be used as complementary therapies in the management of type 2 diabetes mellitus; however, their use must still adhere to proper dosing and should not replace primary medical therapy.

This study examines how tax knowledge, the use of e-filing systems, and the enforcement of tax penalties influence individual taxpayers’ compliance in filing annual tax returns. Tax compliance is a critical factor for the sustainability of government revenue, yet public compliance rates remain suboptimal. The research employs a quantitative approach with an associative causal design, involving 131 respondents in West Jakarta selected through convenience sampling. The instrument, consisting of a questionnaire with 34 items, was tested for validity and reliability and then analyzed using multiple linear regression with the aid of SPSS. The results of the analysis indicate that tax knowledge, the use of e-filing, and tax penalties have a positive effect—both partially and simultaneously—on compliance with annual tax return filing. These findings underscore the need to improve tax literacy, strengthen the e-filing system, and ensure consistent enforcement of penalties to encourage compliance. This study provides an empirical basis for the development of more inclusive and efficient tax policies and supports the government’s strategy to optimize state revenue by raising taxpayer awareness and fostering a sense of responsibility.

Muscle-invasive bladder cancer (MIBC) is an aggressive malignancy associated with high morbidity, reduced survival, and impaired quality of life. Radiotherapy (RT) has been widely used as a bladder-preserving strategy, particularly for patients unsuitable for surgery or systemic chemotherapy. RT may also enhance tumor immunogenicity through programmed death-ligand 1 (PD-L1) upregulation, providing a rationale for combination therapy with immunotherapy. This study aimed to evaluate the effectiveness of combining immunotherapy and radiotherapy in MIBC treatment. A systematic review was conducted following PRISMA 2020 guidelines using the PICO framework. Literature searches were performed in PubMed, Embase, Cochrane, ClinicalTrials.gov, Web of Science, and Scopus databases for studies published between 2016 and 2025. Risk of bias was assessed using the Cochrane Risk of Bias Tool and ROBINS-I. Of 105 identified studies, five met the inclusion criteria and were included in the final analysis. Only one Phase II randomized controlled trial demonstrated low risk of bias in randomization and allocation concealment. ROBINS-I assessment indicated moderate to serious risk in confounding and participant selection domains. Clinical findings showed promising outcomes, with complete response rates ranging from 35%–50% and partial response rates from 25%–40%. Median overall survival ranged from 24–30 months, with favorable disease-free and progression-free survival outcomes. Combined immunotherapy and radiotherapy demonstrate potential to improve survival and disease control in MIBC; however, further rigorous clinical studies are needed to optimize patient-centered treatment strategies.  

This study aims to analyze the role of the sub-district head (Camat) in community empowerment and village development in Lamboya District, West Sumba Regency, based on Government Regulation Number 17 of 2018 concerning Sub-Districts. The research employed an empirical juridical method with a qualitative descriptive approach. Data were collected through interviews, observations, and literature studies involving the Camat, village heads, district staff, Village Consultative Body (BPD) members, and community representatives. The findings reveal that the Camat has carried out important functions in coordinating, supervising, and guiding village governance and development programs, as well as facilitating community empowerment activities. These roles contribute to improving development implementation and encouraging community participation at the village level. However, the effectiveness of these functions has not been fully optimized due to several obstacles, including limited infrastructure, inadequate human resources, weak coordination among institutions, and inconsistencies in regulatory implementation. These challenges affect the achievement of development objectives and the sustainability of empowerment programs. Therefore, strengthening technical regulations, enhancing institutional coordination, and improving the capacity of government officials are necessary to optimize the Camat’s role in supporting effective village development and sustainable community empowerment in Lamboya District.

The high volatility of cryptocurrency assets, particularly Ethereum, poses a significant challenge for investors during market downturns. Traditional passive strategies often lead to substantial capital erosion in bearish conditions. This study explores the application of Deep Reinforcement Learning (DRL) through the Deep Q-Network (DQN) algorithm to develop an adaptive trading agent. By integrating technical indicators—Relative Strength Index (RSI), Simple Moving Average (SMA), and Moving Average Convergence Divergence (MACD)—the proposed model aims to optimize decision-making processes. Experimental results using historical data from 2020 to 2026 demonstrate that while the market experienced a significant decline of 19.55%, the DQN agent successfully maintained capital stability with a marginal deviation of only -0.54%. This finding suggests that the DQN-based approach offers superior risk mitigation and capital preservation capabilities compared to conventional buy-and-hold strategies in volatile financial environments.

This study investigates the implementation of the Gradient Boosting Machine (GBM) algorithm for network intrusion detection using the CICIDS2017 dataset within the CRISP-DM framework. The process encompasses Business Understanding, Data Understanding, and Data Preparation including data cleaning, categorical feature encoding, normalization, and data split (80 % training, 20 % testing). In the Modeling phase, GBM Hyperparameters (learning_rate = 0.1; max_depth = 5; n_estimators = 150) were optimized via Grid Search with 2-fold Cross Validation, and F1-Score  was selected as the primary metric due to class imbalance. Evaluation on the test set yielded accuracy of 99.99 %, precision of 100 %, Recall of 99.98 %, and F1-Score  of 99.99 %, demonstrating exceptional detection capability with minimal false negatives and false positives. Compared to previous studies, this GBM model outperforms in accuracy and stability without overfitting. These findings confirm GBM’s effectiveness for modern Intrusion Detection Systems and its suitability for Deployment in resource-constrained operational environments.

This study examines the role of the creative economy in enhancing sustainable tourism potential in Pampang Cultural Village, Samarinda, Indonesia, and identifies strategic priorities for its development. Pampang Cultural Village is recognized for its rich cultural heritage preserved by the Dayak Kenyah community, which serves as a valuable tourism asset. Despite this potential, the contribution of creative economy activities to tourism development has not been fully optimized. Therefore, a comprehensive analysis is needed to formulate effective development strategies. This research employs a mixed qualitative–quantitative approach using the SWOT-AHP method. SWOT analysis is utilized to identify internal strengths and weaknesses as well as external opportunities and threats affecting creative economy development. Subsequently, the Analytic Hierarchy Process (AHP) is applied to determine the priority level of each strategic factor and alternative strategy. The findings indicate that the village possesses significant creative economy potential in cultural performances, handicrafts, culinary products, traditional fashion, and cultural souvenirs. Cultural authenticity emerges as the primary strength, while limited innovation capacity and digital marketing skills remain the major weaknesses. The results further reveal that the highest-priority strategy is the development of innovative creative tourism products rooted in Dayak Kenyah cultural heritage while preserving cultural authenticity. This strategy should be supported by digital promotion, human resource capacity building, stakeholder collaboration, and improvements in tourism infrastructure to achieve sustainable tourism development.

Indonesia’s Free Nutritious Meal Program (MBG) requires an efficient and adaptive supply chain system to ensure timely distribution, cost efficiency, and adequate nutritional delivery for a large number of beneficiaries. However, conventional supply chain approaches are generally static and unable to respond effectively to dynamic demand, supply uncertainty, and logistical constraints. This study proposes a Multi-Objective Reinforcement Learning (MORL) model to optimize the MBG supply chain by simultaneously considering distribution cost, delivery timeliness, service level, nutritional adequacy, and food waste reduction. The model is developed using a simulation-based environment representing real-world supply chain conditions, including demand variability, transportation limitations, and kitchen capacity constraints. The results show that the proposed approach achieves cost reductions of 15–22%, improves delivery timeliness by 18–25%, maintains a service level above 90%, increases nutritional fulfillment by 12–18%, and reduces food waste by 10–15% compared to baseline methods. Sensitivity analysis further demonstrates the robustness of the model, with minimal performance degradation under disruption scenarios. These findings indicate that Reinforcement Learning provides a scalable and adaptive solution for optimizing large-scale public food distribution systems. The proposed model contributes both theoretically by integrating multi-objective optimization within an RL framework and practically by supporting data-driven decision-making for improving the effectiveness of the MBG program in Indonesia.

The increasing demand for scalable and high-quality digital marketing content has exposed limitations in traditional manual copywriting processes, which are time-intensive and difficult to scale. This research proposes an adaptive AI-driven copywriting framework that integrates a full-stack web architecture with optimized prompt engineering strategies for automated content generation. The system is implemented using React.js for the frontend, Node.js with Express for backend services, and a GPT-based API for language generation. Unlike prior implementations, this research introduces a structured prompt optimization mechanism to enhance content relevance and consistency. Experimental evaluation was conducted using multiple datasets of marketing prompts, with comparisons against baseline GPT usage and manual copywriting. Quantitative results show that the proposed system achieves improvements in BLEU (+18.7%) and ROUGE-L (+21.3%) scores over baseline methods. Human evaluation involving 30 participants indicates a significant increase in perceived content quality, coherence, and persuasiveness (p < 0.05). System performance analysis demonstrates an average response time of 1.8–3.0 seconds and a GTmetrix performance score of 82%. The findings confirm that the proposed framework significantly enhances efficiency, scalability, and content quality, contributing to both applied AI systems and intelligent web-based content production.

Motor Vehicle Tax (PKB) is a key pillar of Regional Original Revenue (PAD) that supports development funding. However, seasonal fluctuations in payment realization create uncertainties in local budget planning. This study aims to address the limitations of the standard Random Forestalgorithm, which suffers from extreme prediction failures on time-series data due to its inability to capture temporal transitions between months. The proposed solution implements feature engineering using a Cyclical Encoding approach (Sine and Cosine transformations) and Lagged Variables. The dataset comprises historical records of motor vehicle tax potential and realization from January 2021 to November 2025. The baseline model evaluation without feature engineering yields highly inaccurate predictions with a Mean Absolute Percentage Error (MAPE) of 203.47% (accuracy of -103.47%). Conversely, after integrating Cyclical Encoding and Lagged Variables, the proposed model's performance improves drastically, achieving a MAPE of 14.40% (an accuracy rate of 85.60%), an MAE of 9,317 units, and an RMSE of 12,638 units. Feature Importance analysis confirms that the cyclically encoded month feature contributes the highest weight to the model's decisions with a score of 0.5031, followed by the potential feature at 0.1798. This study demonstrates that time-based feature engineering effectively optimizes Random Forestfor precise tax revenue forecasting.

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.

Geometry learning at the Junior High School (SMP) level frequently faces challenges due to the abstract nature of the objects, which impacts students' low spatial literacy. This issue is exacerbated by the dominance of conventional teaching methods that lack interactive digital media. This community service activity aims to enhance students' spatial literacy at SMP IT Qoshrul Muhajirin through learning assistance using ethnomathematics-based digibooks. The method employed consists of four stages: Planning, Acting, Observing, and Reflecting. Data were collected through observation, student response questionnaires, as well as pre-test and post-test instruments. The results indicate a significant improvement in students' spatial literacy by 22.70%, with the average score increasing from 43% in the initial stage to 65.70% following the assistance. Furthermore, 91.3% of students provided positive responses regarding the ease of use of the media, and 90.4% felt more motivated in learning. It can be concluded that the use of ethnomathematics-based digibooks is effective as an innovative learning solution capable of integrating digital technology with local cultural values to optimize students' spatial abilities.

The rapid development of artificial intelligence (AI) technology and personalization algorithms has fundamentally transformed the landscape of e-commerce and digital retail, particularly influencing the shopping behavior of female consumers. This study examines the utilization of AI-driven personalization algorithms and their impact on the research shopping phenomenon among female consumers in the digital era. Research shopping, defined as the behavior of searching for product information online while making the final purchase decision offline or across multiple platforms, has become increasingly prevalent as digital touchpoints multiply. This research employs a quantitative approach with a survey method involving 250 female respondents aged 18–45 who actively use e-commerce platforms in Indonesia. Data were collected using structured questionnaires and analyzed using Structural Equation Modeling (SEM). The findings reveal that AI personalization algorithms significantly influence female consumer decision-making processes, fostering research shopping tendencies through targeted recommendations, dynamic pricing, and adaptive content delivery. Furthermore, the study identifies trust, perceived usefulness, and digital literacy as key mediating variables between AI technology utilization and research shopping behavior. These results contribute to the growing body of literature on AI-driven consumer behavior and offer practical implications for digital marketers and e-commerce platform developers seeking to optimize user experience for female consumers.

Digital transformation in the judicial system represents a strategic step to improve the quality of legal services in Indonesia. One of the innovations implemented by the Supreme Court of the Republic of Indonesia is the E-Court system, which enables case administration and court proceedings to be conducted electronically. This study aims to analyze the effectiveness of the implementation of E-Court in realizing the principles of simple, fast, and low-cost justice, as well as to identify the obstacles faced by parties who do not utilize the system. The research method employed is a normative legal approach, involving the analysis of statutory regulations and scholarly literature. The results indicate that, normatively, E-Court has been effective in supporting judicial efficiency; however, in practice, it still encounters various challenges, including technical, social, and institutional aspects. These obstacles vary among different legal subjects, namely advocates, individuals, private legal entities, and government legal entities. Therefore, comprehensive efforts are required to optimize the implementation of E-Court to ensure that the objectives of judicial reform can be fully achieved. Furthermore, the findings reveal that, from a normative perspective, E-Court provides a more efficient mechanism compared to conventional systems, particularly in terms of case administration and communication between parties. However, this effectiveness has not been evenly realized due to constraints such as the digital divide, limited technological infrastructure, and low user readiness. Consequently, the implementation of E-Court still requires reinforcement in both technical and cultural aspects to ensure optimal accessibility for all segments of society.