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This study discusses the progress of science in Andalusia during the rule of the Umayyad Daulah II, which served as an essential bridge between the Islamic world and the West. The purpose of this research is to examine the factors that stimulated scientific advancement, the fields of knowledge that developed, and the intellectual values inherited for modern life. This study employs a qualitative approach with a library research method by analyzing various historical sources, academic journals, and scholarly works related to Islamic civilization in Andalusia. The results show that scientific progress in Andalusia under the Umayyad Daulah II emerged from political stability, social tolerance, religious enthusiasm, and government support for education and research. Knowledge flourished in diverse disciplines such as medicine, astronomy, mathematics, philosophy, art, and architecture. Andalusia became a leading center for education and translation, transmitting Islamic knowledge to Europe and contributing greatly to the rise of the Renaissance. In conclusion, the intellectual achievements of Andalusia demonstrate that the harmony between faith, justice, and openness produces a just and progressive civilization. These scientific and moral values remain relevant for guiding the development of a modern civilization grounded in ethics and humanity.

This study uses a qualitative method of a descriptive approach with an interpretive paradigm to gain an in-depth understanding of the process of planning, implementing, and evaluating broadcast programs. This research was carried out at the Communication and Information Office of Bogor Regency, Jalan Tegar Beriman Number 1, Pakansari, Cibinong District, Bogor Regency, West Java 16914. The data collection techniques used are direct observation of the broadcast process, in-depth interviews with broadcasters and program managers, and documentation to support the validity of research data. The results of this study show that broadcasting strategies are implemented through content planning that suits the needs of listeners, the implementation of interactive broadcasts involving listeners and routine evaluation to maintain the quality of the information that has been delivered. In addition, the use of digital media as a streaming platform and interaction through social media also supports a wider reach to listeners. The conclusion of the broadcasting strategy implemented by Radio Teman 95.3 FM is considered effective in maintaining listener loyalty and attracting new audiences, so that it can be an example for other local radio stations in facing the current digital media competition.technological optimization, audience engagement, and adaptation to the development of new media.

Agrarian conflicts in Lampung illustrate that land disputes are not only about ownership but also about how language shapes public perceptions of power and justice. This study aims to explain the changing patterns of media reporting on agrarian conflicts and the social meanings emerging from these changes. The research uses a descriptive qualitative approach with Fairclough’s critical discourse analysis and Lederach’s conflict transformation theory. Data were obtained from online news reports on agrarian conflicts in Lampung published between 2010 and 2025. The results show that earlier reports emphasized control and security, while later coverage shifted toward issues of justice, land rights, and community recognition. This change indicates that language in media reporting plays a crucial role in transforming public perspectives from a logic of authority toward a consciousness of justice and humanity. The study highlights the importance of fair and empathetic public communication as a foundation for peaceful and sustainable conflict resolution.

Marketing Public Relations is a communication tool that is useful for promoting the advantages of each company's products to increase public trust. Another impact of marketing public relations is creating a positive impression on the public, including towards the Erigo Company. The purpose of this study is to measure the influence of Marketing Public Relations activities on the image of the Erigo company. This study uses a quantitative approach with a survey method. Data were collected through questionnaires distributed online to 75 respondents. The theories used in this study are the Public Relations theory by Edward R. Bernays and the corporate image theory by Kotler and Keller. The results of the analysis show that Marketing Public Relations has a significant influence on the image of the Erigo company, with a contribution of 65.1% and a correlation coefficient value of 0.812, which is included in the very strong category. It can be concluded that Marketing Public Relations carried out by Erigo effectively supports the formation of the company's image among young consumers.

The development of electronic commerce through marketplace platforms presents new challenges in civil law enforcement, particularly concerning the platform's liability for the circulation of counterfeit goods. This study aims to analyze Shopee's legal responsibility as a provider of electronic transaction services regarding the sale of counterfeit goods, based on Article 1365 of the Civil Code concerning Unlawful Acts and its relation to consumer protection principles as regulated in the Republic of Indonesia Law Number 8 of 1999 concerning Consumer Protection. The research uses a normative juridical method with a legislative approach and literature study, including provisions in the Law on Electronic Information and Transactions and Government Regulation Number 71 of 2019 on the Implementation of Electronic Systems and Transactions. The research findings indicate that although Shopee does not act as a direct seller, the platform still has a legal obligation to provide a reliable, secure, and responsible electronic system. Negligence in verifying sellers and monitoring products has the potential to fulfill the elements of unlawful acts, particularly the elements of fault and causal relationship with consumer losses. This study emphasizes that Shopee qualifies as a business actor in the context of consumer protection, thereby bearing both preventive and repressive responsibilities to ensure transaction security and prevent the circulation of counterfeit goods on its platform.

Parental involvement is widely acknowledged as a key factor in student academic success, particularly in second language acquisition. However, its impact at the university level, especially among pre-service English teachers, remains underexplored. This study investigates the relationship between parental involvement and English language achievement among first-year English Education students at Universitas Islam Kalimantan Muhammad Arsyad Al Banjari Banjarmasin (UNISKA). Employing a quantitative survey design, data were collected from 36 purposively selected participants using a structured Likert-scale questionnaire. The instrument measured both the forms and frequency of parental involvement and students’ self-reported performance in English-related subjects. Data were analyzed using descriptive statistics and Pearson Product-Moment Correlation via SPSS 26. Findings indicate that students generally perceive moderate to high levels of parental involvement, especially in providing academic resources, financial support, and attending university-related events. However, involvement in educational decision-making and career discussions was notably low. A significant positive correlation was found between parental involvement and students' academic performance, particularly in aspects such as discipline, assignment completion, and encouragement. Emotional impacts such as increased motivation or reduced anxiety showed more mixed responses. These findings highlight the enduring influence of parental support in higher education and suggest further exploration of its emotional dimensions.

This study analyzes the short story Cinta Semata Wayang by Nuryana Asmaudi SA using a literary psychology approach grounded in Sigmund Freud’s psychoanalytic theory. The research applies a literature study with a descriptive qualitative method. Data were collected through close reading to identify structural elements and the psychological dynamics of the characters. The findings reveal marital conflict symbolized through wayang figures, particularly Rama and Sinta. Structurally, the story presents a progressive plot, symbolic and metaphorical language, and central themes of love and responsibility. The psychological analysis highlights the interaction of the id, ego, and superego within the main characters: Rama experiences tension between personal desires and moral norms, while Sinta demonstrates superego dominance through loyalty and emotional endurance. The short story emphasizes that true love is not solely based on emotion but also requires responsibility, commitment, and moral awareness as the foundation of a harmonious and sustainable relationship. This research contributes to literary psychology studies and deepens understanding of moral values in literature.

This study analyzes the short story Cinta Semata Wayang by Nuryana Asmaudi SA using a literary psychology approach grounded in Sigmund Freud’s psychoanalytic theory. The research applies a literature study with a descriptive qualitative method. Data were collected through close reading to identify structural elements and the psychological dynamics of the characters. The findings reveal marital conflict symbolized through wayang figures, particularly Rama and Sinta. Structurally, the story presents a progressive plot, symbolic and metaphorical language, and central themes of love and responsibility. The psychological analysis highlights the interaction of the id, ego, and superego within the main characters: Rama experiences tension between personal desires and moral norms, while Sinta demonstrates superego dominance through loyalty and emotional endurance. The short story emphasizes that true love is not solely based on emotion but also requires responsibility, commitment, and moral awareness as the foundation of a harmonious and sustainable relationship. This research contributes to literary psychology studies and deepens understanding of moral values in literature.

The increasing volume of online hotel reviews provides valuable insights into customer perceptions but poses challenges for manual analysis due to its unstructured nature. This study aims to compare the performance of Recurrent Neural Network (RNN) and Bidirectional Encoder Representations from Transformers (BERT) in hotel review sentiment analysis. A total of 20,491 TripAdvisor hotel reviews were classified into three sentiment categories: negative, neutral, and positive. The research methodology includes text preprocessing, stratified data splitting, class imbalance handling using Random Over-Sampling, tokenization, and supervised model training. Model performance was evaluated using a confusion matrix and classification metrics. The results indicate that BERT outperforms RNN, achieving an accuracy of 80.54%, while RNN reached 62.21%. BERT demonstrated superior capability in capturing contextual and semantic information in hotel reviews. These findings suggest that transformer-based models are more effective for sentiment analysis of complex textual data in the hospitality domain and can support data-driven service improvement strategies.    

This study aims to analyze the factors affecting real wages of construction workers across provinces in Indonesia from 2010 to 2023 using panel data analysis. The independent variables include Provincial Minimum Wage (UMP), Consumer Price Index (CPI), Open Unemployment Rate (TPT), and Performance Pay (Balas Jasa). A panel dataset of 476 observations from 34 provinces over 14 years was analyzed using three model approaches: Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). The best model was determined through Chow Test, Hausman Test, and Lagrange Multiplier Test, which confirmed that the Fixed Effect Model (FEM) is the most appropriate for analyzing this research data. FEM estimation results show that simultneously, all independent variables (UMP, CPI, TPT, and Performance Pay) have a significant effect on real wages with an F-statistic value of 436,465.9 (p-value = 0.0000 < 0.05), indicating that the model as a whole is highly valid and capable of explaining the variation in real wages collectively. However, partial tests reveal that only the Real Wage variable has a positive and statistically significant effect on Performance Pay (coefficient = 106.3320; t-statistic = 1276.083; p-value = 0.0000), while UMP (p-value = 0.1472), CPI (p-value = 0.6460), and TPT (p-value = 0.6934) show no significant effects at the 5% significance level. The research model demonstrates very high predictive ability with an R-squared value of 0.999735 (99.97%), indicating that the variables studied can explain nearly all variation in real wages of construction workers at the provincial level. This research provides policy implications that improving real wages in the construction sector requires an integrated approach that focuses not only on minimum wage setting but also on regional inflation control, human capital quality improvement, and creating conducive labor market conditions through unemployment reduction

The use of protective equipment in the form of helmets is an important aspect of ensuring motorcycle rider safety. However, violations of helmet usage still frequently occur and are difficult to monitor continuously. This study proposes a real-time helmet detection system using the YOLOv8 object detection method. The YOLOv8n model was trained using a helmet and no-helmet image dataset that underwent data augmentation to improve the model’s robustness against variations in environmental conditions. The system was implemented using the Python programming language with the support of the Ultralytics and OpenCV libraries. The system input was obtained from a webcam with a resolution of 640×640 pixels, where each video frame was processed in real time to detect the Helmet and No Helmet classes. The system displays bounding boxes and class labels in real time and is equipped with a violation duration calculation mechanism. When a no-helmet condition is detected continuously, the system generates pop-up alerts and automatic notifications via the Telegram application. The experimental results show that the system is capable of detecting helmet usage and no-helmet violations in real time with stable performance. The integration of violation duration calculation helps reduce momentary detection errors and improves the reliability of identifying valid violations

This study develops an interpretable machine learning model to predict the settlement status of Hajj fees in Jambi Province, Indonesia. Utilizing the XGBoost algorithm on a dataset of 4,332 prospective pilgrims from 2025, the research addresses the critical challenge of class imbalance where only 28.5% of samples are labeled "Unsettled". The baseline XGBoost model achieved a ROC-AUC of 0.7778, with a recall of 0.3482 for the minority class. SHAP (SHapley Additive exPlanations) analysis was employed to interpret model predictions, revealing that financial features specifically NILAI_VA (Virtual Account Value), JML_SETORAN (Deposit Amount), and JML_PELUNASAN (Settlement Amount) are the most significant factors influencing repayment risk, with negative SHAP values indicating increased default probability. The findings demonstrate that an interpretable XGBoost framework can provide both predictive accuracy and actionable insights for policymakers, enabling targeted interventions such as flexible payment schemes and enhanced financial monitoring for high-risk pilgrims..

The development of information technology has driven digital transformation in various sectors, including the food and beverage (F&B) industry. However, many small to medium-scale F&B businesses still rely on manual ordering systems, resulting in long queues, order recording errors, limited menu information, and suboptimal user experience. This study aims to design the user interface (UI) and user experience (UX) of a web-based Smart Ordering System that provides convenience, efficiency, and comfort in the food ordering process. The research method used is the Design Thinking approach, which includes empathize, define, ideate, prototype, and testing stages. The design process involves user needs analysis, user flow development, wireframe creation, and high-fidelity prototype development using Figma. Usability testing is conducted using the Single Ease Question (SEQ) method to evaluate ease of use and user satisfaction. The results indicate that the proposed UI/UX design provides a clear ordering flow, intuitive interface, and easy-to-understand user experience. Based on the SEQ results, most users experienced no difficulty in using the system, indicating that the design meets usability criteria with a very good category and is suitable for implementation in the F&B industry.

Budget efficiency is an important issue in state financial management because it is directly related to government spending priorities and their impact on public service programs. Discussions about budget efficiency policies are widespread on social media platform X, generating diverse public responses, thus necessitating an automated approach to understand public opinion trends more quickly and objectively. This research aims to analyze the sentiment of Indonesian people toward budget efficiency policies and compare the performance of the Naïve Bayes and Support Vector Machine (SVM) algorithms in classifying sentiment. The research data used 10,909 Indonesian-language tweets sourced from a public dataset, which were then processed thru the preprocessing stages including cleaning, case folding, normalization, tokenization, stopword removal, and stemming. Sentiment labeling is performed automatically using the Indonesian Sentiment Lexicon (InSet) approach to categorize data into positive, negative, and neutral sentiments. Feature extraction was performed using Term Frequency–Inverse Document Frequency (TF-IDF), and then the data was divided into training and testing sets with an 80:20 ratio. Model performance evaluation was conducted using a confusion matrix and the metrics of accuracy, precision, recall, and F1-score. The research results show that sentiment distribution is dominated by negative sentiment at 56.78%, followed by positive sentiment at 37.40%, and neutral sentiment at 5.83%. In the classification stage, SVM performed best with an accuracy of 86%, while Naïve Bayes achieved an accuracy of 74%. These findings indicate that SVM is more optimal for sentiment classification on social media text data and can be utilized to more effectively support the analysis of public response to budget efficiency policies.

The implementation of the One-Stop Integrated Service (PTSP) Website at the Ministry of Religious Affairs of Jambi City is part of the digital transformation of public services. This study aims to measure user satisfaction with the PTSP Website using the End User Computing Satisfaction (EUCS) method and the DeLone & McLean model. This research employed a quantitative approach using a survey method involving 100 respondents who are users of the PTSP Website. The EUCS variables consist of content, accuracy, format, ease of use, and timeliness, while the DeLone & McLean model includes system quality, information quality, and service quality. Data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0 software. The results indicate that system quality, information quality, and service quality have a positive effect on user satisfaction with the PTSP Website. This study is expected to serve as an evaluation reference for improving the quality of digital public services.

The management of scientific works at the Faculty of Law, Universitas Jambi, is still carried out manually through physical archives and simple digital storage without an integrated information system. This condition causes limited access, slow information retrieval, and a high risk of document loss and damage. This study aims to develop a web-based scientific repository system to improve the efficiency, accessibility, and security of managing academic works. The system was developed using the Waterfall method, which consists of requirement analysis, system design, implementation, testing, and evaluation. Data collection was conducted through interviews, observations, and questionnaires involving librarians, lecturers, and students. The system was implemented using the Laravel framework with a MySQL relational database to support document storage, metadata management, access control, and search functionality. The results show that the developed repository system is able to facilitate the submission, verification, publication, and retrieval of scientific works effectively. User acceptance testing indicates that the system meets user needs in terms of usability, functionality, and accessibility. The implementation of this system contributes to improving academic information management and supports digital transformation at the Faculty of Law, Universitas Jambi.

The skill mismatch between university graduates and technology industry requirements remains a significant challenge in Indonesia. PT Vinix Seven Aurum requires an assessment tool to objectively identify the initial competencies of MBKM and internship program participants. This research aims to design a web-based self-assessment platform that helps students measure their skill gaps against industry standards through radar chart visualization and personalized learning recommendations. The UI/UX design applies the Design Thinking method with empathize, define, ideate, prototype, and test phases, utilizing Figma for wireframe and high-fidelity prototype development. Data collection was conducted through observation, interviews, literature studies, and usability testing with 10 respondents. The results demonstrate good usability with a 100% completion rate across all features. The VINIX Skill Radar platform provides five assessment categories, a 1-10 rating scale system, radar chart visualization, gap analysis, and learning recommendations. This system enhances students' self-awareness of their competencies and supports effective mapping of training program participants' capabilities.

Digital portfolios are a crucial tool for professionally showcasing abilities and learning objectives. Nevertheless, the projects and certificates of participants in the Independent Study program at VINIX7 are still kept apart and are not controlled by an integrated system. This requirement is the basis for the research's design and development of a website-based digital portfolio system that will serve as participants' key platform. Requirements analysis, system design, implementation, and testing are all steps in the Waterfall approach of system development. The Laravel framework was used to create the VinixPort website, which is backed by a MySQL database. The system has tools for managing portfolio material, talent evaluation, user registration and login, and data presentation via analytics. The study's findings show that the VinixPort website was created successfully and that all of the system's primary features work as intended. This service helps users create organized digital portfolios that are readily available and prepared for both professional and academic use.

Many new business owners are seeking easy and simple business consulting services amid rapid technological advances. Unfortunately, most available platforms only offer consulting, not a place to consult and create websites. Biz Starter was created to meet this need, by becoming a platform that not only offers consulting services but also helps users build websites for their own businesses. The development process uses a user-oriented approach, starting from identifying needs, designing the appearance, and then conducting testing. The results show that it is quite helpful for users, especially beginners, because the appearance is simple, the flow is clear, and the business process is much more practical. Overall, this platform has succeeded in making the user experience easier, and it can serve as a digital companion for people who are preparing for business consulting.

This study conducts sentiment analysis of Indonesian user reviews of the CapCut application using IndoBERT and compares two evaluation schemes: a single 80/20 train–test split and stratified 5-fold cross-validation (k=5). A total of 1,048,575 reviews were collected from the Google Play Store through web scraping and labeled into three sentiment classes based on rating: negative (1–2), neutral (3), and positive (4–5). After preprocessing—cleaning, case folding, banned-word removal, normalization—and duplicate removal, 517,962 reviews were retained. IndoBERT Base P1 was fine-tuned using fixed hyperparameters (batch size 32, learning rate 2e-5, up to 4 epochs, early stopping patience 2), while undersampling was applied to the training set to address class imbalance. Performance was assessed using accuracy, precision, recall, F1-score, and ROC-AUC, supported by confusion matrix and ROC-curve visualizations. The single split achieved an accuracy of 0.756, whereas cross-validation produced a mean accuracy of 0.740. Across both schemes, the positive class achieved the best performance (F1-score 0.850; ROC-AUC 0.918–0.919), while the neutral class remained the most challenging (precision 0.198–0.206; F1-score 0.280–0.283). Overall, cross-validation is recommended for reporting because it reduces dependence on a single partition and provides a more representative estimate across multiple splits.