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This study aims to analyze the influence of digital experience and customer experience on passenger loyalty on the Progo Train route, Pasar Senen–Lempuyangan. The increasing digitalization of public transportation services through the Access by KAI application has highlighted the importance of examining the quality of digital experience and customer experience in maintaining passenger loyalty. The study employed a quantitative approach with a causal associative design. Data were collected from 150 respondents through a questionnaire with a five-point Likert scale using a purposive sampling technique. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4 software (Ringle et al., 2024). The results of the outer model evaluation showed that all indicators had outer loadings > 0.70, Average Variance Extracted (AVE) > 0.50, Composite Reliability (CR) and Cronbach's alpha > 0.70, thus all constructs were declared valid and reliable. The inner model test shows that digital experience has a positive and significant effect on passenger loyalty (β = 0.192; T = 2.237; p = 0.025). Customer experience also has a positive and significant effect on passenger loyalty (β = 0.243; T = 3.268; p = 0.001). The coefficient of determination (R²) of 0.133 indicates that both variables explain 13.3% of the variance in passenger loyalty. The customer experience variable has a more dominant influence than digital experience on Progo Train passenger loyalty.

The development of digital services by BPJS Ketenagakerjaan through the JMO (Jamsostek Mobile) application has triggered a surge in large-scale and unstructured user reviews on the Google Play Store, thereby complicating manual analysis and conventional sentiment analysis in accurately identifying specific issues. This research aims to implement the Aspect-Based Sentiment Analysis (ABSA) method to granularly evaluate JMO application reviews based on specific aspects, while simultaneously addressing class imbalance and computational efficiency issues. The proposed method combines the pretrained IndoBERT model as a contextual feature extractor, the SMOTE technique to balance the training data, and an artificial neural network (Neural Network) as the classification layer without performing full fine-tuning. The dataset used consists of 90,268 unique reviews categorized into five main aspects through keyword matching, namely General Satisfaction/Complaints, Performance & Stability, Service & Support, Feature Quality, and UI/UX, with initial lexicon-based labeling using the InSet Lexicon. The research results indicate that the proposed model successfully achieves highly optimal performance with an accuracy rate of 91.81% and a weighted F1-score of 92%. Furthermore, the implementation of SMOTE proved effective in enhancing model reliability on the minority class (negative sentiment), achieving an F1-score of 89%. The implications of this research contribute an accurate and efficient aspect-based sentiment analysis framework for developers, and serve as a strategic evaluation tool for BPJS Ketenagakerjaan in mapping specific user complaints to accelerate continuous improvements in the performance, stability, and service quality of the JMO application.

Dental caries is an oral health problem associated with the activity of Streptococcus mutans. Water hyacinth (Eichhornia crassipes) contains bioactive compounds such as flavonoids, tannins, and alkaloids with antibacterial potential. This study aimed to evaluate the effectiveness of water hyacinth extract against the growth of Streptococcus mutans. The research method used was an in vitro experimental study with a post test only group design. A total of 24 samples were divided into four treatment groups with extract concentrations of 6.25%, 12.5%, 25%, and 50%. Antibacterial activity was tested using the disc diffusion method on Mueller Hinton Agar media. Data were analyzed using the Kruskal-Wallis and Mann-Whitney tests. The results showed that water hyacinth extract inhibited the growth of Streptococcus mutans. The largest inhibition zone was observed at 50% concentration, while the smallest was found at 6.25% concentration. Kruskal-Wallis analysis showed significant differences among groups (p<0.05). In conclusion, water hyacinth (Eichhornia crassipes) extract has antibacterial activity against Streptococcus mutans.

Cutaneous fungal infections caused by Malassezia furfur remain a significant health concern in tropical regions, highlighting the need for safe and effective alternative therapies. Moringa oleifera L. leaves are reported to contain various secondary metabolites, including flavonoids, tannins, and saponins, which exhibit potential antifungal activity. This study aimed to develop a topical suspension formulation of Moringa oleifera leaf extract and to evaluate the effect of varying extract concentrations on the physical characteristics of the preparation. An experimental method was employed using four formulations: F0 as the control, and F1, F2, and F3 containing 9%, 10%, and 11% extract, respectively. Evaluation parameters included organoleptic properties, homogeneity, pH, viscosity, and adhesiveness, as well as stability testing using a cycling test method for 12 days. The results demonstrated that all formulations exhibited good organoleptic characteristics, homogeneity, and viscosity. The pH values remained within the acceptable range for skin preparations, although slight fluctuations were observed during storage. Adhesiveness also showed variations across several testing cycles. Overall, the formulations met acceptable physical quality criteria and demonstrated potential for further development as topical suspensions; however, formulation optimization is still required to enhance stability during storage.

Cutaneous fungal infections caused by Malassezia furfur remain a significant health concern in tropical regions, highlighting the need for safe and effective alternative therapies. Moringa oleifera L. leaves are reported to contain various secondary metabolites, including flavonoids, tannins, and saponins, which exhibit potential antifungal activity. This study aimed to develop a topical suspension formulation of Moringa oleifera leaf extract and to evaluate the effect of varying extract concentrations on the physical characteristics of the preparation. An experimental method was employed using four formulations: F0 as the control, and F1, F2, and F3 containing 9%, 10%, and 11% extract, respectively. Evaluation parameters included organoleptic properties, homogeneity, pH, viscosity, and adhesiveness, as well as stability testing using a cycling test method for 12 days. The results demonstrated that all formulations exhibited good organoleptic characteristics, homogeneity, and viscosity. The pH values remained within the acceptable range for skin preparations, although slight fluctuations were observed during storage. Adhesiveness also showed variations across several testing cycles. Overall, the formulations met acceptable physical quality criteria and demonstrated potential for further development as topical suspensions; however, formulation optimization is still required to enhance stability during storage.

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.

This study aims to determine the production process and the level of consumer acceptance of Bandung nagasari cake utilizing stevia as a natural sweetener and butterfly pea flower extract (Clitoria ternatea) as a natural coloring agent. The research employed a quantitative approach with an experimental method through organoleptic testing involving 20 panelists. Data collection techniques consisted of literature review, questionnaires, and organoleptic evaluation covering taste, texture, aroma, and appearance. The obtained data were analyzed using descriptive quantitative analysis with percentage calculations. The findings indicated that the Bandung nagasari formulation containing stevia and butterfly pea flower extract was more preferred than the formulation using granulated sugar. Approximately 90% of panelists preferred the taste attribute due to its healthier perception, while 80% of panelists favored the texture, aroma, and appearance attributes because of the softer texture and the attractive natural coloration produced by the butterfly pea flower extract. Furthermore, the product demonstrated a shelf life of 12 hours at room temperature and up to 3 days under refrigerated storage conditions. The study concludes that the incorporation of stevia and butterfly pea flower extract may serve as an innovative development of traditional Bandung nagasari cake without eliminating its traditional characteristics and shows favorable consumer acceptance.

Background: Acne vulgaris is one of the most common skin problems and is closely associated with the activity of Propionibacterium acnes. Long-term use of antibiotics may lead to bacterial resistance; therefore, alternative antibacterial agents derived from natural products are needed. White rice (Oryza sativa L.) is known to contain bioactive compounds such as flavonoids, alkaloids, terpenoids, tannins, and saponins, which potentially exhibit antibacterial activity. Objective: This study aimed to evaluate the antibacterial activity of ethanol extract of white rice against the growth of Propionibacterium acnes. Methods: This research was conducted as a laboratory experimental study using a post-test only control group design. The ethanol extract of white rice was prepared by maceration using 70% ethanol. Antibacterial activity was evaluated using the disc diffusion method with extract concentrations of 100%, 50%, 25%, 12.5%, and 6.25%. Clindamycin was used as a positive control, while sterile distilled water served as a negative control. The parameter observed was the diameter of the inhibition zone. Result: The results of phytochemical screening showed that the ethanol extract of white rice (Oryza sativa L.) contains flavonoids, alkaloids, and terpenoids. Antibacterial activity test showed that the ethanol extract of white rice at concentrations of 100%, 50%, and 25% was able to inhibit the growth of Propionibacterium acnes by forming an inhibition zone, while at concentrations of 12.5% and 6.25% no inhibition zone was formed. The highest inhibition zone diameter was found at a concentration of 100%. The ethanol extract of white rice at concentrations of 100% (7.65 mm), 50% (6.77 mm), and 25% (6.15 mm) was able to inhibit the growth of Propionibacterium acnes, and was classified as having moderate inhibition. In contrast, at concentrations of 12.5% and 6.25%, the ethanol extract of white rice did not show any inhibitory activity detected in vitro using the disc diffusion method. The results of statistical analysis showed a p value <0.001, which means there was a significant difference in the diameter of the inhibition zone between the treatment groups. Conclusion: In conclusion, the ethanol extract of white rice exhibits antibacterial activity against Propionibacterium acnes in a concentration-dependent manner; however, its inhibitory effect remains lower than that of clindamycin.

This study analyzes netizen sentiment concerning the 17+8 public aspirations circulating the digital platform X spanning the period from August 18 through October 31, 2025. 1,837 comments obtained through scraping method. Classification Research stages include data preprocessing, sentiment weighting based on lexicon, and feature extraction using TF-IDF. Data 80% used for learning purposes and the remaining 20% utilized for validation. The findings reveal that the majority of comments, amounting to 81.14%, contained negative sentiment, while the remaining 18.86% were positive. The outcomes demonstrate that community reactions toward the 17+8 People's Demands were dominated by unsupportive views. From a theoretical standpoint this scholarly work offers to enriching knowledge concerning public opinion classification on political issues through a computational approach, while also serving as a reference for future research focused on improving the accuracy of sentiment analysis related to political dynamics and the behavior of state institutions.

Antimicrobial resistance is a persistent threat to hospital care, particularly when empirical therapy relies on broad-spectrum antibiotics without continuous evaluation of local use and susceptibility patterns. This literature review aimed to synthesize evidence from four Indonesian hospital-based studies regarding antibiotic utilization, rationality assessment, and bacterial resistance profiles. A structured narrative review was conducted using four selected articles provided by the author. Data were extracted for study design, setting, population, antibiotic evaluation method, dominant antibiotic classes, rationality indicators, resistance profile, and stewardship implications. The four studies were descriptive and hospital-based, using retrospective records, concurrent observation, ATC/DDD with DU 90%, qualitative rationality criteria, and antibiogram data. The synthesis showed a consistent concentration of antibiotic use in broad-spectrum groups, especially third-generation cephalosporins, penicillins, quinolones, and macrolides. In a Bandung public hospital, total antibiotic consumption reached 95,719.01 DDD, with penicillins, cephalosporins, quinolones, macrolides, and sulfonamides included in the DU 90% segment. In intensive care, ceftriaxone was the most frequently used antibiotic and most rationality indicators were appropriate, although clinically significant drug interactions were still identified. In pediatric acute respiratory infection inpatients, cefotaxime and ceftriaxone dominated empirical therapy. Resistance mapping in Denpasar highlighted relevant Gram-positive and Gram-negative pathogens and recommended antibiotics according to susceptibility levels. Overall, the reviewed evidence supports an integrated antimicrobial stewardship model combining ATC/DDD-DU 90% surveillance, qualitative rationality evaluation, antibiogram-based empirical guidance, and periodic feedback to prescribers.

The dissemination of personal data through digital media has increased significantly alongside the growing use of Quick Response (QR) Codes for various purposes, such as electronic tickets, certificates, and digital identities. Conventional QR Codes are open and can be easily scanned, copied, or manipulated by unauthorized parties. The personal data referred to in this study includes sensitive information such as full name, identity number (NIK/National ID), date of birth, address, phone number, and email address. This research proposes a layered security system that combines the Advanced Encryption Standard (AES) cryptographic algorithm with steganography using the Discrete Cosine Transform (DCT) method. The process begins with encrypting personal data using AES, converting the encrypted result into a QR Code, and embedding the QR Code into a digital image using DCT, hiding it in the image’s frequency domain. The digital images used are of fixed size and formats that preserve visual quality. System evaluation is carried out by testing the visual quality of the stego image, the success rate of QR Code extraction, and the integrity of the encrypted data. The results are expected to conceal sensitive information visually while maintaining its confidentiality, with potential applications in electronic ID cards, digital certificates, e-tickets, and other confidential documents.

Introduction: Ramadan fasting is a religious practice observed by Muslims by abstaining from food and drink from dawn until sunset. These changes may increase the need for oral and dental healthcare. However, some Muslims still perceive that undergoing dental treatment while fasting may invalidate the fast, leading many patients to delay or avoid dental visits during Ramadan. Objective: This study aims to review and analyse various scientific literature regarding the safety and permissibility of dental procedures for patients who are observing fasting during Ramadan. Methods: This study used a narrative review method by searching scientific articles through PubMed, ScienceDirect, and Google Scholar databases using keywords relevant to the research topic. Articles were selected based on predetermined inclusion and exclusion criteria. Results: The review findings indicate that most dental procedures, such as local anaesthesia administration, scaling, restorative treatment, and tooth extraction, generally do not invalidate fasting as long as no material or fluid is intentionally swallowed. The use of suction devices, isolation of the treatment area, and proper scheduling of dental procedures are important factors in minimizing the risk of swallowing fluids during treatment. Conclusion: Most dental procedures can be safely performed on fasting patients while still considering both medical aspects and Islamic principles. Patient education regarding the safety of dental procedures during fasting should be improved to prevent delays in treatment and complications in oral health.

The rise of social media has created a digital public sphere that enables users to express their opinions on social and political issues openly and in real-time. One of the most discussed topics on social media platform X is the trending hashtag #IndonesiaGelap, which reflects public concern and criticism regarding various governmental and societal conditions. This study aims to conduct sentiment analysis on tweets containing the hashtag to determine the overall sentiment trend among users. The method employed in this research is the Naive Bayes classification algorithm, known for its simplicity and effectiveness in text classification. To enhance the model’s performance, Particle Swarm Optimization (PSO) is applied to optimize feature selection and parameter tuning. The dataset consists of public tweets collected via the Twitter API, followed by preprocessing, feature extraction using TF-IDF, and sentiment classification into three categories: positive, negative, and neutral. The results indicate that the integration of PSO significantly improves the classification accuracy of the Naive Bayes model compared to the baseline. The majority of tweets related to #IndonesiaGelap exhibit a negative sentiment, indicating widespread public dissatisfaction and criticism. This research is expected to contribute to a better understanding of public perception and serve as valuable input for stakeholders in addressing social issues in the digital age.

Sign language recognition is one of the areas of image recognition and image processing technology that is developing rapidly in human-computer interaction. This technology really helps the deaf and speech impaired in communicating with non-disabled people. This research aims to examine the optimization of an object tracking system in sign language using the Gaussian Mixture Model (GMM) and Kalman Filter by including the Region of Interest (ROI). The proposed system consists of three main components, namely hand detection, object extraction, and classification. Hand detection is done using the Kalman Filter to track hand movements accurately. Next, Region of Interest (ROI) features, such as shape, direction and movement features, are extracted from the detected part of the hand. These features are fed into a Gaussian Mixture Model (GMM) classifier, which can recognize sign language based on the extracted features. With the combination of GMM and Kalman Filter in this research, it can increase accuracy in object tracking, reduce interference from the background, and ensure the tracking focus remains on important objects. The dataset used is in the form os SIBI alphabet symbols, namely A-Z with the amount of data for each class, namely 620 images. Based on the research result, model testing using GMM, Kalman Filter and ROI produces higher accuracy of 99%, while model testing using GMM and ROI produces accuracy of 90%.

The optimal therapeutic impact of local vaginal drug delivery systems is strongly influenced by the physical characteristics balance of Solid Vaginal Suppositories. A comprehensive review regarding the comparison of mechanical profiles, specifically melting time and crushing strength parameters, from various base classifications constitutes the primary objective of this literature research. The implementation of a Literature Review study design was executed through the extraction of empirical data from twelve experimental journals published within the last ten years. Excessively rapid phase transformation characteristics at physiological basal temperatures and low compression resistance were consistently demonstrated by lipophilic bases such as Oleum Cacao. The risk of structural deformation during the distribution process is highly susceptible to unmodified lipid preparations. High surface elasticity accompanied by a delay in molecular hydration duration reaching 120 minutes was recorded in the utilization of Glycerinated Gelatin Base. Structural rigidity exceeding 4 kgF and disintegration time efficiency under 60 minutes were optimally demonstrated by Polyethylene Glycol (PEG) Base. An enhancement in mechanical resistance against external shocks during the storage period is offered by the thorough modification of the synthetic polymer ratios. Therefore, the determination of the PEG base as the most optimal material is recommended to maintain the quality stability of pharmaceutical products. Compendial regulation standards regarding the physical strength testing of pharmaceutical preparations must be obeyed by every institution to ensure long-term treatment effectiveness. Thus, the alignment between active substance release duration and physical preparation endurance can be realized for absolute patient comfort.

  Red dragon fruit contains bioactive compounds such as vitamin C, flavonoids, and polyphenols that have antioxidant potential and possess natural pigments that can be used as cosmetic colorants. This study aims to formulate and evaluate a blush-on powder preparation from dragon fruit pulp extract as an alternative natural colorant. The evaluation includes organoleptic testing, homogeneity, pH, irritation, spreadability, fineness, moisture content, and antioxidant activity. The results showed that the formulation met most of the requirements, exhibiting a pink color, a smooth texture, no odor, homogeneity, a pH of 6 suitable for the skin, no irritation, even spreadability within 4 applications, a fineness degree of 97.6%, and a moisture content of 6.91%. Antioxidant activity showed an IC₅₀ value of 0.3036 ppm (very strong), although the relative inhibition percentage was low (18.35%). Thus, dragon fruit extract has the potential as a natural ingredient in blush-on powder that provides both color and antioxidant benefits.

This research investigates the integration of the creative economy as a catalyst for sustainable tourism development within Kutai National Park (KNP), East Kalimantan. Despite its ecological significance as a lowland rainforest and Orangutan habitat, KNP faces stagnation due to a reliance on extractive resources and a lack of diversified tourism products. Employing a qualitative descriptive methodology and SWOT analysis, this study maps the creative potential of the region and evaluates its impact across four sustainability pillars: economic, social, environmental, and institutional. Data were gathered through field observations and in-depth interviews with park authorities, local government officials, and creative entrepreneurs in the buffer zones of Sangatta and Bontang. The findings reveal significant potential in non-timber forest-based culinary arts, modernized ethnic crafts, and digital wildlife storytelling. A critical institutional barrier identified is the "sectoral ego" between conservation authorities and local governments. The study proposes a strategic shift toward a "Green Creative Hub" model, emphasizing that sound governance and institutional synchronization are essential for balancing conservation with economic empowerment. This research provides a roadmap for policy-makers to transition from extractive-based livelihoods to a knowledge-based service economy that preserves the integrity of protected landscapes.

This research critically investigates the circulation of disinformation concerning the instability of fuel prices on the digital platform X and its subsequent implications for the polarization of modern society. In an era where unverified economic news frequently dictates public reaction, fake news often acts as a potent catalyst for mass anxiety. By implementing a quantitative framework driven by lexicon-based computational sentiment analysis, this study effectively processed a dataset of 500 public opinion samples extracted via Google Colab spanning from April 2024 to April 2026. To ensure computational accuracy and eliminate textual noise, the data underwent a rigorous preprocessing phase encompassing case folding, alongside the systematic removal of URLs, account mentions, numbers, hashtags, and punctuation marks. The statistical outcomes revealed a highly disproportionate emotional landscape, overwhelmingly dominated by 451 negative reviews. In stark contrast, neutral observations and positive affirmations were nearly absent, recording only 40 and 9 instances, respectively. The data compellingly illustrates that the relentless influx of pessimistic narratives regarding economic instability directly induces financial panic, undermines rational discourse, and severely fragments cyberspace into deeply polarized factions.

The oil and gas industry requires efficient initial processing to separate reservoir fluids into oil, gas, and water phases. The Separator Unit is the main facility that plays a vital role in the surface facility production stage. This study aims to evaluate the type of separator used, identify control components, and understand the working principles and operational procedures of separators in the Main Production Facility (MPF) area. The methodology used is direct observation and literature studies during the implementation of practical work in July 2024 at PT. Citic Seram Energy Limited, Seram Non Bula Block, Maluku. The observation results show that the type of separator used is a Horizontal Three Phase Separator with tag codes 03-V-001A and 03-V-001B operating alternately. The separation process is carried out based on differences in fluid density utilizing gravity, supported by internal components such as deflector plates, mist extractors, weirs, and straightening vanes. Separator operation is maintained at an operating pressure of around 55 psig to ensure optimal separation efficiency and work safety. The conclusion of this study indicates that effective separator operation requires stable pressure and temperature control as well as routine maintenance to prevent sediment buildup and maintain product quality.

Background: Nallaswamy Class III alveolar ridge refers to an edentulous alveolar bone that has undergone resorption, resulting in a moderate ridge height with a knife-edge ridge form. This condition is relatively common and has been reported to reach a prevalence of approximately 89% in edentulous mandibles. Objective: To describe the prosthodontic treatment implications in patients with Nallaswamy Class III alveolar ridge using an acrylic resin removable partial denture (RPD). Case Report: A 22-year-old female patient presented to RSGM Soelastri with complaints of discomfort while chewing due to the loss of several posterior teeth in the mandible. The teeth had been extracted three years earlier due to caries and retained roots. Intraoral examination revealed healthy dentition in the maxillary arch and edentulous areas at teeth 35, 36, 45, and 46 in the mandibular arch. The alveolar ridge in the edentulous area showed a knife-edge form with moderate height, consistent with Nallaswamy Class III. Discussion: The condition was classified as Applegate-Kennedy Class III modification 1P with bilateral bounded saddle areas, which may affect mastication, aesthetics, and speech. Conclusion: Partial edentulism with a knife-edge alveolar ridge can be effectively managed using an acrylic resin removable partial denture.