Abstract:This study examines the implementation of customer-driven excellence strategy in the Umrah travel industry in Depok City by investigating the relationships between service quality, brand credibility, perceived value, and…
customer-driven excellence outcomes. Using a quantitative research approach with Partial Least Squares Structural Equation Modeling (PLS-SEM), data were collected from 105 customers who have utilized Umrah travel services within the past two years. The measurement model demonstrated excellent reliability and validity, with all constructs meeting stringent psychometric criteria for convergent and discriminant validity. The structural model reveals that all three hypotheses are strongly supported, with brand credibility emerging as the most influential factor (β = 0.398, p < 0.001), followed by perceived value (β = 0.356, p < 0.001) and service quality (β = 0.285, p < 0.001). The integrated model explains 74.2% of variance in customer-driven excellence, demonstrating strong explanatory power and large predictive relevance (Q² = 0.486). These findings provide empirical evidence that successful customer-driven excellence strategy requires integrated approaches prioritizing brand credibility development while simultaneously enhancing perceived value and service quality. The study offers valuable insights for Umrah travel operators seeking to optimize competitive advantage through comprehensive customer excellence strategies that address both functional and emotional dimensions of religious tourism services.
Abstract:Dengue Hemorrhagic Fever (DHF) is an endemic disease in Indonesia caused by the dengue virus and transmitted through the bites of Aedes aegypti and Aedes albopictus mosquitoes. The risk of serious complications primarily…
arises during the critical phase, typically between the 4th and 6th days of fever, during which plasma leakage may occur, leading to shock and severe bleeding. Hematocrit levels and platelet counts are important parameters in the diagnosis and monitoring of DHF patients. This study aimed to determine the differences in hematocrit levels and platelet counts during days 4 to 6 of fever in DHF patients at Prima Medika Hospital Denpasar, in February 2025. This research employed a descriptive quantitative design with purposive sampling, involving 35 patients who met the inclusion criteria. The results showed a decrease in hematocrit levels with averages of 42.8%, 42%, and 41.2%, and platelet counts with averages of 87 x 10³/µL, 59 x 10³/µL, and 47 x 10³/µL from day 4 to day 6 of fever. Data were analyzed using the Shapiro-Wilk normality test, the Friedman non-parametric test for hematocrit levels, and the Repeated Measures ANOVA parametric test for platelet counts. Statistical analysis showed a p-value of 0.002 for hematocrit levels and 0.000 for platelet counts. The conclusion of this study is that there are significant differences in hematocrit levels and platelet counts between days 4 to 6 of fever in DHF patients.
Abstract:The rising prevalence of obesity in Indonesia contributes to increased risk of metabolic diseases such as diabetes mellitus. Body Mass Index (BMI) is commonly used to assess nutritional status and may be correlated with…
long-term blood glucose levels measured by Hemoglobin A1c (HbA1c). This study aimed to explore the relationship between BMI and HbA1c levels in patients at Prima Medika General Hospital, Denpasar. A cross-sectional analytic observational design was employed, involving 30 purposively selected respondents. BMI was calculated from weight and height measurements, while HbA1c levels were assessed using the immunoturbidimetric method. Results showed an even distribution of respondents in the normal and overweight BMI categories (each 46.5%), while 50% had HbA1c levels >8%. However, Pearson correlation analysis indicated no statistically significant relationship between BMI and HbA1c levels (p=0.982; r=-0.004). The study concludes that BMI does not have a linear correlation with HbA1c levels. Other factors such as type and duration of therapy, disease progression, and patient adherence may play a greater role in influencing glycemic control and should be further investigated.
Abstract:Family communication plays a fundamental role in shaping an individual's character, particularly in adulthood. This study examines the influence of family communication patterns on adult character formation through a bibliometric…
liometric analysis. Utilizing a Systematic Literature Review (SLR) and bibliometric approach, this research explores key trends, theoretical frameworks, and scholarly discussions related to family communication and character development. The study highlights the significance of open, trust-based, and emotionally supportive communication in fostering essential adult traits such as responsibility, integrity, empathy, and adaptability. Findings suggest that families with high conversation orientation cultivate individuals with stronger social skills and problem-solving abilities, whereas rigid conformity-oriented communication may hinder independent decision-making. Additionally, digital communication emerges as a growing factor influencing family dynamics. By mapping research trends and analyzing citation patterns, this study provides valuable insights into the long-term impact of family communication on adulthood and offers recommendations for future research.
Abstract:Research on leadership styles and the strengthening of school culture in Islamic schools has become increasingly significant in response to the growing demand for educational quality grounded in religious values. School…
principals play a strategic role in developing an adaptive, collaborative, and character-oriented organizational culture that supports students’ holistic development. This study focuses on publication trends, thematic cluster structures, and the tendencies of leadership style implementation in strengthening Islamic school culture based on bibliometric analysis. The study employed a descriptive quantitative approach using bibliometric analysis of 397 Scopus-indexed documents published between 2019-2025. Data collection was conducted using Publish or Perish, while data visualization analysis was performed using VOSviewer through keyword co-occurrence techniques. The findings reveal that school culture and distributed leadership emerged as the most dominant themes and occupied central positions within the bibliometric network. The shift in research paradigms indicates a transition from structural approaches toward participatory, collaborative, and contextual approaches in modern educational leadership. Another finding demonstrates that the concepts of Islamic school and Islamic leadership have not yet appeared prominently in international research networks, thereby indicating a significant research gap regarding the integration of Islamic values into school culture and educational leadership practices. This study concludes that the strengthening of school culture is influenced not only by the administrative capabilities of school principals, but also by their ability to foster collaboration, social relations, innovation, and the continuous internalization of moral values. The novelty of this research lies in the use of bibliometric analysis to systematically map the relationship between leadership styles and Islamic school culture, while also offering a perspective on integrating the values of amanah, shura, and exemplary conduct into modern collaborative leadership models.
Abstract:The cognitive development of early childhood requires appropriate stimulation, one of which is through color recognition. Color block media serves as an educational tool that not only introduces various colors but also familiarizes…
amiliarizes children with geometric shapes, numerical concepts, and trains their thinking and memory skills. This study aims to implement color block media as an innovative learning method to effectively improve early childhood abilities in color recognition. Early childhood is a stage of exploration, where the learning process must be concrete, engaging, and enjoyable. Color block media combines visual and manipulative approaches that can foster curiosity and active involvement in the learning process. This learning-through-play activity encourages children to naturally identify, differentiate, and name colors. The study used a quantitative method with a pretest-posttest design to determine the effectiveness of the media. The research was conducted at KB Adduriyah 3 on October 29, 2024, and data analysis was performed using a t-test through SPSS 18 for Windows. The results showed a significance value (2-tailed) of 0.00. Since this value is smaller than the significance level (α = 0.05), the null hypothesis is rejected, and the alternative hypothesis is accepted. The results of the study demonstrate that color block media has a significant impact on improving children's color recognition skills. Additionally, the media also enhances children's active participation in learning activities. Therefore, color block media is highly recommended as a creative and effective learning strategy for educators and parents in supporting the cognitive development of early childhood.
Abstract:This study, conducted from 2017 to 2023, analyzes the relationship between international tourism and law using bibliometric methods on a dataset of 237 selected documents. The findings reveal a declining trend in annual…
dataset growth, with an average document age of approximately 2.93 years. The study delves into author collaboration, document types, and keyword usage. There was an average of 4,042 citations per document, reflecting the scholarly impact in the field. The dataset included 714 plus keywords and 738 author keywords, contributing to content analysis. Among the 570 unique authors, 87 were sole authors, while 99 documents were single-authored, and the average co-authorship was 2.47. Notably, there was no international co-authorship in the dataset. Document types encompassed articles, books, book chapters, conference papers, and more, with peak scientific production observed in 2020. Treemap and thematic map analysis visualize term distribution and research trends.
Abstract:Abstract: This study aims to classify the nutritional status of toddlers based on anthropometric data using the K-Nearest Neighbor (KNN) algorithm. Data were obtained from 20 Integrated Health Posts (Posyandu) in Rumbai…
Timur District, including Lembah Sari Village and Limbungan Village with a total of 1,000 toddler data. After cleaning and preprocessing, 782 data were obtained ready for use. The preprocessing stages include data cleaning and transformation, outlier removal, minority class handling, and data normalization. Next, data balancing was carried out using the Synthetic Minority Oversampling Technique (SMOTE) to address class imbalance. The data was divided into 80% training data and 20% test data, then the K parameter was tested from 1 to 15 using 5-fold cross-validation. The results showed that the value of K = 1 provided the best performance with a macro recall of 0.8827 and an accuracy of 86.26%. These results indicate that the combination of the KNN algorithm with the SMOTE method and Min-Max normalization is effective in improving classification performance on imbalanced data and producing accurate and balanced predictions of toddler nutritional status between classes.
Keywords: k-nearest neighbor; toddler nutritional status; SMOTE; min-max scaling; classification; anthropometric data
Abstrak: Penelitian ini bertujuan untuk mengklasifikasikan status gizi balita berdasarkan data antropometri menggunakan algoritma K-Nearest Neighbor (KNN). Data diperoleh dari 20 Posyandu di Kecamatan Rumbai Timur, meliputi Kelurahan Lembah Sari dan Kelurahan Limbungan dengan total 1.000 data balita. Setelah melalui proses cleaning dan preprocessing, diperoleh 782 data yang siap digunakan. Tahapan pra-pemrosesan meliputi pembersihan dan transformasi data, penghapusan outlier, penanganan kelas minoritas, serta normalisasi data. Selanjutnya dilakukan penyeimbangan data menggunakan Synthetic Minority Oversampling Technique (SMOTE) untuk mengatasi ketidakseimbangan kelas. Data dibagi menjadi 80% data latih dan 20% data uji, kemudian dilakukan pengujian parameter K dari 1 hingga 15 menggunakan 5-fold cross-validation. Hasil penelitian menunjukkan bahwa nilai K = 1 memberikan performa terbaik dengan recall macro sebesar 0,8827 dan akurasi 86,26%. Hasil ini menunjukkan bahwa kombinasi algoritma KNN dengan metode SMOTE dan normalisasi Min-Max efektif dalam meningkatkan kinerja klasifikasi pada data tidak seimbang serta menghasilkan prediksi status gizi balita yang akurat dan seimbang antar kelas.
Kata kunci: k-nearest neighbor; status gizi balita; SMOTE; min-max scaling; klasifikasi; data antropometri
Abstract:This study focuses on the development of an Augmented Reality (AR)–based learning application designed to assist students in understanding the mathematical concepts of volume and surface area of three-dimensional geometric…
tric shapes. The development process adopted the Multimedia Development Life Cycle (MDLC) model, which consists of six systematic stages: concept, design, material collecting, assembly, testing, and distribution. The research concentrated on the development and expert validation stages. Validation results from content and media experts indicate that the application meets pedagogical and technical feasibility standards. The content expert confirmed that the materials align with the national mathematics curriculum and are presented in a clear, contextual, and accurate manner, while the media expert highlighted the user-friendly interface, interactive features, and visual appeal of
the application. Theoretically, this AR-based medium bridges the gap between abstract mathematical concepts and concrete visualization by enabling students to interact directly with
virtual 3D objects. Practically, the application enhances learning motivation and engagement by providing dynamic, interactive experiences. Overall, this research contributes to the
advancement of educational technology by offering a systematic model for developing AR-based learning media that support active and meaningful learning in the digital
era.
Abstract:Abstract: Rehabilitation programs are essential in correctional systems to equip inmates with the skills and behavioral readiness required for social reintegration. However, rehabilitation program assignment in many correctional…
ectional institutions remains dependent on manual and subjective assessments, which may result in inconsistent decisions. This study develops a Random Forest–based prediction system to support objective and data-driven rehabilitation program determination. A quantitative approach was applied using historical inmate data from January 2023 to January 2025, comprising 2,023 records. The research process included data preprocessing, an 80:20 training–testing split, model training, and performance evaluation using accuracy, precision, recall, and F1-score metrics. The results show that the model achieved an accuracy of 86.17% during training in Google Colab and 68.83% when deployed within the application system. This performance gap reflects real-world deployment and computational constraints rather than model failure. The proposed system provides consistent and objective rehabilitation program recommendations, thereby supporting more effective rehabilitation planning and decision-making in correctional institutions.
Keywords: correctional institutions; inmate rehabilitation programs; machine learning; random Forest; prediction system
Abstrak: Program pembinaan narapidana memiliki peran penting dalam sistem pemasyarakatan untuk membekali warga binaan dengan keterampilan serta kesiapan perilaku dalam proses reintegrasi ke masyarakat. Namun, pada banyak lembaga pemasyarakatan, penentuan program pembinaan masih bergantung pada penilaian manual yang bersifat subjektif, sehingga berpotensi menimbulkan ketidakkonsistenan dalam pengambilan keputusan. Penelitian ini mengembangkan sistem prediksi program pembinaan narapidana berbasis algoritma Random Forest guna mendukung pengambilan keputusan yang objektif dan berbasis data. Pendekatan kuantitatif diterapkan menggunakan data historis narapidana periode Januari 2023 hingga Januari 2025 sebanyak 2.023 data. Tahapan penelitian meliputi prapemrosesan data, pembagian data latih dan uji dengan rasio 80:20, pelatihan model, serta evaluasi performa menggunakan metrik akurasi, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa model mencapai akurasi sebesar 86,17% pada tahap pelatihan di Google Colab dan 68,83% saat diimplementasikan pada sistem aplikasi. Perbedaan performa tersebut mencerminkan keterbatasan lingkungan operasional, bukan kegagalan model. Secara keseluruhan, sistem yang dikembangkan mampu memberikan rekomendasi program pembinaan yang lebih objektif dan konsisten, sehingga mendukung perencanaan pembinaan yang lebih efektif.
Kata kunci: mesin pembelajaran; program pembinaan narapidana; random Forest; sistem pemasyarakatan; sistem prediksi