Effectiveness of Health Education in Improving Pregnant Women’s Knowledge of Triple Elimination Screening for HIV, Syphilis, and Hepatitis B

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Background: Triple elimination screening for HIV, syphilis, and hepatitis B among pregnant women is a strategic program in maternal and child health services to prevent intrauterine and mother-to-child transmission. The success of this program is determined not only by the availability of testing services but also by pregnant women’s level of knowledge regarding the benefits, procedures, and timing of triple elimination screening.

Objective: This study aimed to assess the effectiveness of health education in improving pregnant women’s knowledge of triple elimination screening for HIV, syphilis, and hepatitis B.

Methods: This study used a pre-experimental design with a one-group pretest-posttest approach. The study sample consisted of 196 pregnant women. Data were collected through interviews using a structured questionnaire to assess pregnant women’s knowledge. Respondent characteristics were analyzed descriptively. Knowledge was assessed before and after health education using a score ranging from 0 to 100. Differences in mean scores were analyzed using the paired sample t-test with a significance level of 0.05.

Results: Most respondents were aged 20-35 years (144 respondents; 73.5%), came from Gulak Galik Village (91 respondents; 46.4%), were unemployed (182 respondents; 92.9%), and underwent screening in the first trimester (150 respondents; 76.5%). Triple elimination screening results showed no reactive HIV or syphilis cases, whereas reactive HBsAg was found in 4 respondents (2.0%). The mean knowledge score increased from 57.59 ± 10.11 before education to 81.02 ± 11.11 after education.

Conclusion: There was a statistically significant difference in mean knowledge scores based on the paired sample t-test (t = 49.37; p < 0.001).

Digital Transformation and Bank Profitability in Indonesia: The Role of Firm Size as a Moderating Variable

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This study investigates the effect of digital transformation on bank profitability in Indonesia, with firm size examined as a moderating variable. Specifically, it assesses whether digital transformation enhances financial performance and whether larger banks are better positioned to benefit from digital initiatives. Using a quantitative research design, the study analyzes panel data from 41 banks operating in Indonesia. A fixed-effects regression model is employed to estimate the direct effect of digital transformation on profitability, measured by return on assets (ROA) and return on equity (ROE), as well as the moderating effect of firm size. The results show that digital transformation has a positive and statistically significant effect on both ROA and ROE, indicating that investments in digital technologies improve banking performance. In addition, firm size positively moderates the relationship between digital transformation and profitability. Larger banks appear to derive greater benefits from digitalization due to their stronger technological infrastructure, greater financial capacity, and higher ability to invest in innovation and human capital. The study concludes that digital transformation is a key driver of bank profitability and that organizational scale enhances its effectiveness. These findings contribute to the literature on digital transformation and banking performance and offer practical implications for bank managers and regulators in formulating digital strategies that align with institutional size and capabilities.

Effectiveness of Mozart Classical Music Therapy in Reducing Stress Levels Among Final-Year Medical Students at Nusa Cendana University

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Background: Stress is common among final-year medical students due to academic demands, thesis preparation, and clinical responsibilities. Mozart classical music therapy may serve as a simple non-pharmacological relaxation method to reduce stress.

Objective: To determine the effectiveness of Mozart classical music therapy in reducing stress levels among final-year medical students at Nusa Cendana University.

Methods: This quasi-experimental study used a one-group pretest-posttest design. Respondents were final-year students of the Medical Education Study Program, Faculty of Medicine and Veterinary Medicine, Nusa Cendana University. Stress levels were measured using the Perceived Stress Scale-10 before and after Mozart classical music therapy. The intervention was given for 15 minutes daily for seven consecutive days. Pretest and posttest stress scores were analyzed using a paired t-test.

Results: Before the intervention, most respondents had moderate stress (89.1%), followed by mild stress (7.3%) and severe stress (3.6%). After the intervention, mild stress increased to 30.9%, moderate stress decreased to 63.6%, and one respondent (1.8%) reported no stress. A significant reduction in stress level was found after therapy (p < 0.001).

Conclusion: Mozart classical music therapy significantly reduced stress levels among final-year medical students.

Explainable, Evidence-Based Verification of Arabic Claims via Multi-Source Retrieval and Cross-Lingual NLI

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We present a training-free, explainable system for verifying Arabic-language claims that combines Arabic Named-Entity Recognition (NER), parallel multi-source evidence retrieval, dense semantic reranking, and cross-lingual Natural Language Inference (NLI) under a single weighted verdict aggregator. Entities are extracted with CAMeLBERT-mix-NER and used to bias a parallel search over trusted Arabic RSS feeds, Google News, a verified-account X (Twitter) endpoint, and DuckDuckGo. Retrieved snippets are reranked by a multilingual-E5 encoder and scored by an XLM-RoBERTa-large checkpoint fine-tuned on XNLI/ANLI; per-source entailment and contradiction probabilities are combined through a weighted aggregator with multiplicatively capped priors over source authority, learned domain reputation, author credibility, and recency. We evaluate on the AraFacts benchmark and make the following contributions, each of which a reader can rely on: (i) a corrected, openly unit-tested aggregator that lets all retrieved evidence—not only official sources—drive the verdict; (ii) a rigorous, reproducible baseline study showing that AraFacts’s natural class imbalance (94% of claims are false-labelled) makes accuracy misleading and that even a well-tuned classical text-only classifier reaches only 0.40 macro-F1; and (iii) an explainable system packaged for deployment as a Streamlit application, a FastAPI service, and a Telegram bot, each exposing a per-source evidence trail. We also document and correct an evaluation error in an earlier version of this work. Code, scripts, and unit tests are released for full reproducibility.

FundusSSM: A Hybrid CNN–State Space Model with Geometry-Aware Ring-Scan Tokenization for Retinal Disease Classification

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Automated retinal disease classification from colour fundus photographs is a critical screening tool for early diagnosis of sight-threatening conditions, especially in regions with limited access to ophthalmologists. Convolutional neural networks (CNNs) and vision transformers have achieved strong performance in this task; however, both families treat the fundus image as a generic two-dimensional grid and ignore the well-known circular geometry of fundus photography and the concentric anatomical organisation of the retina. In this paper, we propose FundusSSM, a hybrid architecture that combines a pretrained ConvNeXt-Tiny feature extractor with a geometry-aware Ring-Scan State Space Model. The Ring-Scan tokenizer partitions the CNN feature map into  equal-area concentric rings that align with the optic disc, the macula, and the peripheral retina; each ring is then processed by a bidirectional Mamba block, and information is exchanged across rings every two layers through a lightweight cross-ring attention module. We evaluate FundusSSM on a 4,217-image, four-class fundus dataset (cataract, diabetic retinopathy, glaucoma and normal) under stratified five-fold cross-validation. FundusSSM achieves the highest mean F1-score among the evaluated models (95.78%), with a low cross-fold standard deviation of 0.59% that is smaller than those of the closest baselines (ConvNeXt-Tiny and Swin-Tiny), and it outperforms ConvNeXt-Tiny, Swin-Tiny, EfficientNet-B4 and ResNet-50 in mean F1. An ablation study confirms that the proposed Ring-Scan ordering reduces the cross-fold variance by approximately 46% relative to a raster-scan ablation that uses the same architecture but a standard row-major token order. We further introduce a ring-level explainability analysis that produces per-ring feature-contribution scores aligned with clinical anatomical zones, and we observe that the model concentrates most on central optic-disc tokens for glaucoma while activating all rings nearly uniformly for cataract — patterns that agree with how clinicians read the same images. We believe that the approach followed in this research and the achieved findings could be useful to other researchers who are interested in geometry-aware deep-learning models for fundus screening tasks.

Mapping Cross Buying Research in Digital Services: A Bibliometric Analysis of Trends, Themes, and Future Research Directions

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This study aims to map the development of literature on cross-buying in digital services by identifying publication trends, thematic clusters, and the structure of relationships between research topics. The approach used was bibliometric analysis utilizing publication data obtained through Publish or Perish software from the Crossref database. The search process used three main keywords: Cross-buying behavior, Digital service adoption, and Customer purchase intention, with 1,000 publications each, resulting in a total of 3,000 documents analyzed. The obtained bibliographic data was then processed and visualized using VOSviewer software through keyword co-occurrence analysis to produce network visualizations, overlay visualizations, and density visualizations. The results show that the structure of the literature on cross-buying in digital services forms three main clusters: the digital service adoption cluster, the consumer behavior and purchase intention cluster, and the research methodology cluster. Keywords such as purchase intention, adoption, product, and service emerged as dominant topics in the research network. The trend analysis shows the development of research topics from an initial focus on consumer behavior to integration with digital technology and digital service transformation. Furthermore, the density visualization shows that topics related to purchase intentions and digital service adoption have the highest occurrence rates in the literature. Overall, this study provides a systematic mapping of the development of cross-buying research in digital services and demonstrates the link between consumer behavior, digital technology adoption, and digital service strategies in the academic literature.

Integrating Technology into The Grade Ten Mathematics Curriculum at New Amsterdam Secondary School: Enhancing Instruction and Student Outcomes

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Mathematics remains one of the essential subjects for the foundation of problem-solving, logical and analytical skill in the twenty-first century. There are, however, difficulties in mathematics achievement that are still evident in Guyana, and throughout the Caribbean. The study was carried out in the context of integrating technology in the Grade Ten Mathematics curriculum at New Amsterdam Secondary School, to determine if a technology-based teaching method would be effective for students in the school to achieve higher academic performance than the traditional method. The study had a quasi-experimental research design with a non-equivalent control group. There were three Grade Ten classes: two experimental and one control. Students took pre-tests and post-tests and the intervention was used in twelve lessons of the topic: mensuration. The technology-enhanced lessons for the experimental groups used multimedia presentations, videos, simulations, games and interactive activities, whereas the control group was taught the same using traditional methods.

Results showed significant gains in mathematics achievement for students in the technological approach. The mean gain score of the experimental group (Group I) was 11.286 (SD = 3.041) whereas that of the experimental group (Group II) was 10.231 (SD = 4.072) and the control group was 4.452 (SD = 2.803). The independent samples t-test gave a p value that was much lower than 0.05, which is the level of significance, and this meant that there was a significant difference between the technological method of instruction and the traditional method of instruction. The results of the study indicate that technology enhanced instruction has a positive impact on students’ academic achievement and comprehension in mathematics. The study recommends that technology can enhance mathematics education in secondary schools in Guyana and may be used to help remediate some of the issues that have long plagued mathematics education in Guyana and the wider Caribbean.

The Effect of Acupuncture Intervention on Sleep Quality among Students: A quasi-experimental study

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Poor sleep quality is common among adolescents and can impair cognitive function, physical health, mental health, and academic achievement. Acupuncture and acupressure are non-pharmacological therapies that can be used to improve sleep quality because they are safe, effective, and have minimal side effects. This study aims to analyse the effect of acupuncture intervention on sleep quality among students in Central Lampung, Lampung Province, Indonesia. This study used a quasi-experimental design with a pretest-posttest two-group design. A sample of 80 respondents was selected using simple random sampling and divided into acupuncture (n=40) and acupressure (n=40) therapy groups. The intervention was given in 10 sessions. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). Data were analysed using Paired Sample t-test and Independent Sample t-test with a 95% confidence level (α=0.05). Acupuncture therapy reduced PSQI scores from 13.13±2.604 to 9.48±2.276 with a mean difference of 3.650 (p<0.001). Acupressure therapy reduced PSQI scores from 11.93±2.464 to 9.80±1.924 with a mean difference of 2.125 (p<0.001). After the intervention, there was no significant difference between the groups (p=0.492). Acupuncture and acupressure were both effective in improving sleep quality, but acupuncture showed a greater change in scores.

The Effect of the Problem Based Learning (PBL) Model Assisted by Quizizz Media on IPAS Learning Outcomes of Grade IV Elementary School Students in Sanggau Regency

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Background: Social Science and Natural Science (IPAS) learning in elementary schools faces significant challenges, particularly in teaching the topic of social and cultural diversity in Indonesia. Conventional, teacher-centered approaches have failed to stimulate students’ critical thinking skills and active engagement, especially in the multi-ethnic context of Sanggau Regency, West Kalimantan.

Objectives: This study aims to: (1) test the significant effect of the Problem Based Learning (PBL) model assisted by Quizizz media on IPAS learning outcomes of Grade IV students; (2) describe the effectiveness of Quizizz in improving motivation and cognitive learning outcomes on the social and cultural diversity topic through PBL; and (3) analyze differences in learning outcomes between students taught using PBL assisted by Quizizz and those taught using conventional methods at SD Negeri in Sanggau Regency.

Methods: This study employs a quantitative approach with a Quasi-Experimental Research method using a Non-Equivalent Control Group Design. The study population comprises 45 Grade IV students across three SD Negeri in Sanggau Regency: SD Negeri 01 Sanggau (experimental), SD Negeri 02 Balai Karangan (experimental), and SD Negeri 14 Sekumpai (control). Samples were selected using purposive sampling. Data collection instruments include direct observation sheets, teacher performance observation sheets, a learning achievement test (20 multiple-choice items via Quizizz), and interview guidelines. Data were analyzed using descriptive statistics, normality test (Kolmogorov-Smirnov/Shapiro-Wilk), homogeneity test (Levene’s test), Independent Sample t-Test, and N-Gain score.

Expected Findings: Based on the theoretical framework and relevant prior research, it is hypothesized that the PBL model assisted by Quizizz media will have a significant positive effect on IPAS learning outcomes, demonstrate greater effectiveness in increasing motivation and cognitive learning outcomes compared to conventional methods, and produce a statistically significant difference in post-test scores between the experimental and control groups.

Conclusion: The PBL model assisted by Quizizz media is projected to be a contextually relevant, effective, and innovative approach to improving IPAS learning outcomes in the local cultural context of Sanggau Regency, providing empirical evidence to support its broader adoption in elementary social and science education in Indonesia.

System Dynamics-Based Policy Scenario Evaluation for Sustainable Municipal Solid Waste Management in Ambon City, Indonesia

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Unmanaged waste and heavy reliance on landfill disposal highlight the urgent need for sustainable municipal solid waste management planning in Ambon City. This study developed a system dynamics model to evaluate policy scenarios for increasing managed waste and reducing landfilled waste. Using Powersim Studio 10, the model projected waste generation and waste management performance from 2026 to 2035 to evaluate the achievement of the 100% managed waste target by 2029 and the post-target effects of policy interventions on system performance. The model was tested through structure verification and behavior reproduction testing. The simulation results indicate that the business-as-usual scenario fails to meet the 2029 target due to limited upstream reduce, reuse, and recycle capacity and continued reliance on the conventional collect–transport–dispose approach. In contrast, the integrated policy scenario provides the most effective policy direction. Achieving a 30% source- and community-based reduce, reuse, and recycle (3R) target requires management capacity to increase by 38.43% annually. This upstream intervention reduces downstream handling burdens by lowering the required annual increase in collection and transportation capacity from 8.94% to 5.50%. Furthermore, developing an integrated waste processing facility (abbreviated in Indonesian as TPST) before landfill disposal, with a capacity of 74 tons/day, substantially reduces landfilled waste. The integrated scenario achieves the 100% managed waste target earlier, in 2028, maintains this level through 2034, and produces the lowest landfilled waste among all scenarios through 2035. The proposed dynamic model provides a decision-support framework for local government in formulating more effective and sustainable municipal solid waste management strategies.