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Menstrual cycle disturbances are common side effects of injectable hormonal contraception and may affect contraceptive satisfaction and continuation. This study aimed to analyze the relationship between the duration of injectable contraceptive use and menstrual cycle disturbances among injectable contraceptive acceptors. A quantitative analytic study with a cross-sectional design was conducted at TPMB Maya from September to October 2025. A total of 67 injectable contraceptive users were included using a total sampling technique. The independent variable was the duration of injectable contraceptive use, categorized as less than one year and more than one year, while the dependent variable was menstrual cycle disturbance. Data were collected using a structured questionnaire and analyzed through univariate analysis and Kendall’s tau-b correlation test. The results showed that most respondents were aged 20–35 years (86.6%), had a senior high school education (55.2%), and were multiparous (77.6%). Most respondents had used injectable contraception for more than one year (82.1%), and 74.6% experienced menstrual cycle disturbances. Bivariate analysis revealed a statistically significant relationship between the duration of injectable contraceptive use and menstrual cycle disturbances (τ = −0.264; p = 0.032). The study concludes that longer use of injectable contraception is associated with a higher occurrence of menstrual cycle disturbances, emphasizing the importance of duration-based counseling in family planning services.

Innovation in biology learning is increasingly necessary, as conventional instructional practices are often dominated by memorization-based methods that limit students’ active engagement and critical thinking development. Along with rapid advances in science and technology, digital applications offer new opportunities to enhance teaching and learning processes. One such application is Canva, a digital design platform that can be utilized as an effective learning media to support teachers and students in biology education. This study aims to describe the implementation of Canva-based learning media through a training program conducted at SMA Islam Terpadu Daarul Rahman and to examine its perceived usefulness for both teachers and students. The training involved teachers in developing biology learning materials using Canva by integrating visual elements, images, and videos to present complex biological concepts more clearly. The results of the training indicate that Canva is considered practical, user-friendly, and efficient by teachers in designing learning materials. Teachers reported that the application helped them present content in a more attractive and structured manner. Furthermore, students benefited from the use of Canva-based materials, as they demonstrated better understanding of the subject matter and increased interest in learning biology. The integration of visual and multimedia elements also supported the development of students’ critical thinking skills by encouraging analysis and interpretation of biological phenomena. Overall, the use of Canva as a learning medium shows potential to enhance the quality of biology learning and foster more meaningful learning experiences.

Financial statement integrity refers to financial statements that accurately reflect the true condition of a company, without anything being concealed or hidden. The importance of financial statement integrity has become an increasingly pressing requirement that companies must fulfill in order to avoid misleading financial statement users, which could result in erroneous decision-making. This study aims to analyze the influence of managerial ownership, institutional ownership, company size, financial distress, and leverage on financial statement integrity in banking sector companies listed on the Indonesia Stock Exchange (IDX) for the period 2021-2023. The research population consists of banking sector companies listed on the IDX during the 2021-2023 period. This study involves 20 companies selected as samples using purposive sampling. The analysis technique used to test the hypotheses is multiple linear regression analysis. The results of this study indicate that managerial ownership, institutional ownership, company size, and leverage do not affect financial statement integrity, while financial distress has a negative effect on financial statement integrity. This study is expected to provide general input to managers or strategists at companies listed on the Indonesia Stock Exchange to always align all interests involved in company management.

This research aims to examine how prices and reviews influence consumers 'purchasing decisions on the Shopee platform in Jambi City. The rapid development of e-commerce has encouraged consumers to be more careful and discerning when selecting products, making price and product reviews important considerations in buying decisions. This study employed a quantitative approach via a survey method for data collection. The questionnaires were distributed online and successfully gathered responses from active Shopee users in Jambi City. Purposive sampling was employed to make sure that respondents met research criteria. The information gathered underwent analysis using IBM SPSS Statistics 27, which involved conducting assessments of validity, reliability, and classical assumptions, and multiple regression tests to see the impact of each variable on buying decisions. The study revealed that product price and reviews hold an important and relevant impact on consumer buying decisions. This research indicates that the more competitive the price and the better the quality, the bigger the possibility of customers buying products on Shopee.

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.

Recommender systems play a critical role in shaping user decisions across digital platforms; however, the increasing complexity of recommendation algorithms has raised serious concerns regarding transparency, trust, and accountability. This study focuses on enhancing the transparency of recommender systems by integrating Explainable Artificial Intelligence (XAI) techniques within a MovieLens-based recommendation framework. The primary problem addressed is the opacity of conventional recommendation models, which limits user understanding of why certain items are recommended and may reduce trust, perceived fairness, and system acceptance. Accordingly, the main objective of this research is to design and evaluate a hybrid explainable recommender system that balances predictive accuracy with human-understandable explanations. The proposed approach combines Matrix Factorization, feature-importance-aware neural networks, and knowledge graph embeddings to construct a robust recommendation model. To enhance explainability, multiple XAI strategies are integrated, including model-agnostic methods (LIME, SHAP, and CLIME), argumentation-based explanations, and context-aware personalized explanations. A comprehensive evaluation framework is employed, incorporating algorithmic metrics (accuracy, fidelity, robustness, counterfactual consistency, and fairness) alongside human-centered evaluations measuring trust, transparency, cognitive load, and perceived usefulness. Experimental results demonstrate that the knowledge graph–enhanced hybrid model achieves superior recommendation accuracy compared to baseline approaches. Moreover, context-aware explanations consistently outperform other methods in terms of fidelity, robustness, and user-perceived transparency, while argumentation-based explanations are found to be the most persuasive. CLIME offers a strong balance between technical stability and interpretability. The findings indicate that no single explainability technique is universally optimal; instead, hybrid and adaptive explanation strategies are most effective. In conclusion, this study confirms that human-centered, context-adaptive XAI significantly improves transparency and user trust in recommender systems, highlighting explainability as a fundamental component rather than an optional enhancement.

This study aims to analyze the impact of content marketing, influencer marketing, and online customer reviews on the purchasing interest in Skintific products on TikTok among Generation Z students of the Bachelor of Management program at Universitas Semarang. Primary data was collected through a Google Form questionnaire distributed to Generation Z students using purposive sampling technique, based on the criteria of Generation Z age, active TikTok users, and familiarity with Skintific products. A quantitative approach was applied using multiple linear regression analysis after validity, reliability, normality, multicollinearity, and heteroscedasticity tests met the requirements. The results show that content marketing, influencer marketing, and online customer reviews individually have a significant positive effect on purchasing interest in Skintific products. Simultaneously, these three variables significantly influence purchasing interest, with a strong contribution. These findings imply that an integrated digital marketing strategy involving content marketing, influencer marketing, and online customer reviews is effective in increasing purchasing interest among Generation Z students on TikTok. This provides valuable insights for companies in designing more effective digital marketing campaigns to attract young consumers through social media platforms.

Games that were initially enjoyed individually and offline have now evolved into online games that allow interaction, competition, and friendship with other players in real-time. Online games are now increasingly popular, one of which is Mobile Legends. This game can be downloaded through the Play Store and App Store. In April 2024, Mobile Legends ranked the most popular game by downloads on the statista.com website. The research objective was to determine the influence of event marketing, content marketing, influencers, and the social environment on the decision to purchase Mobile Legends game skins in Kebumen Regency. The method used was non-probability sampling with a purposive sampling technique aimed at 100 users. Data collection techniques used questionnaires and literature studies. The data analysis technique used multiple linear regression, which was then processed with the SPSS application version 25.0 for Windows. The results showed that event marketing had a significant effect on purchasing decisions, content marketing had a significant effect on purchasing decisions, influencers had no significant effect on purchasing decisions, the social environment had no significant effect on purchasing decisions, and event marketing, content marketing, influencers, and the social environment simultaneously had a significant effect on purchasing decisions.

The rapid advancement of digital technology has significantly influenced students’ learning behavior while gradually reducing their interest in local cultural education, including the study of the Javanese script. This phenomenon is evident at SDIP Haji Muhammad Subandi, where most students still struggle to recognize, read, and understand Javanese characters due to the limited use of engaging and interactive learning media. To address this issue, a 2D educational game was developed as an innovative, contextual, and enjoyable learning medium that integrates cultural elements into an interactive digital learning experience. The design and development process employed the Multimedia Development Life Cycle (MDLC) method, which consists of six stages: concept, design, material collecting, assembly, testing, and distribution. The game was built using Unity software to produce dynamic visuals, responsive controls, and supporting audio elements that enhance the immersive quality of gameplay. The educational game enables students to learn Javanese script through interactive play activities, including letter recognition, pronunciation practice, and quiz-based challenges. Each component was designed to strengthen cognitive understanding while increasing students’ intrinsic motivation to learn. Expert validation results indicated that the game met the “highly feasible” criteria as a learning medium, while user testing showed notable improvements in motivation, engagement, and learning enjoyment. Overall, this educational game not only enhances learning effectiveness but also contributes to the preservation and revitalization of the Javanese script as part of Indonesia’s cultural heritage in the digital era. Therefore, this game-based learning approach serves as an adaptive and culturally grounded educational innovation for primary-level students

Indonesian Sign Language (BISINDO) serves as a primary communication medium for the deaf community; however, limited public understanding often creates barriers during daily interactions. This study aims to develop a real-time BISINDO word-level translation system using hand landmark extraction and temporal modeling with Long Short-Term Memory (LSTM). The system employs MediaPipe Hands to detect 21 hand landmarks per frame, which are then processed as sequential motion patterns to classify five BISINDO words: saya, terima kasih, maaf, nama, and kamu. A total of 250 gesture samples were recorded under controlled lighting conditions as the primary dataset. The processed sequences were used to train the LSTM model, which was subsequently integrated with an ESP32 microcontroller and a DFPlayer Mini module to produce direct audio output. Experimental results show that the model achieved an average accuracy of 86%, with precision and recall values ranging from 0.81 to 0.94. The confusion matrix analysis indicates that most gestures were correctly classified, although some errors occurred in gestures with similar initial motion trajectories. Integration testing demonstrated an average system latency of 3.8 seconds and an audio output success rate of 85%. These findings indicate that the proposed system is capable of translating BISINDO word-level gestures accurately, responsively, and consistently in real-time conditions. This study provides a strong foundation for the broader development of sign language translation systems, with potential enhancements in vocabulary expansion, multi-user datasets, and hardware optimization for deployment in real-world environments.

The development of social media as a space for disseminating information has presented opportunities as well as challenges in religious learning for students. TikTok, as a digital platform that is popular among the younger generation, provides a variety of Islamic content with the theme of fiqh and morals that have the potential to affect users' religious understanding. This study aims to analyze the influence of Islamic content on TikTok with the theme of fiqh and morals on the religious knowledge of students of the PAI Study Program UIN Palopo. The research method used a quantitative approach with multiple linear regression analysis of 268 respondents selected through random sampling techniques. The results of the study show that the content of fiqh has a positive and significant effect on students' religious knowledge, so that content that contains explanations of the laws of worship can improve religious understanding. Moral content has also proven to be significant, especially because of the presentation of moral values that are simple and relevant to student life. Simultaneously, the two variables contributed 61.3% to the increase in religious knowledge. These findings confirm that TikTok plays a role as an effective informal learning medium, although the limitations of the duration of the content make the understanding formed not always deep. This research implies the need to strengthen digital literacy and students' critical attitudes in filtering religious content so that the understanding obtained is more comprehensive and accurate.

This research aims to examine the contribution of the Price Variable, Promotion Variable, and Product Rating Variable to Consumer Purchase Intention for Wardah cosmetic products on the Shopee e-commerce platform. The type of research used is a quantitative approach with data collection techniques through questionnaires distributed to respondents, namely consumers who have purchased Wardah cosmetic products on the Shopee e-commerce platform. The data obtained were analyzed using multiple linear regression techniques.The findings show that the Price variable contributes significantly, indicating that the more appropriate and affordable the price offered is in accordance with consumers’ perceived value, the higher their intention to purchase Wardah products on the Shopee e-commerce platform. Promotion is also proven to make a significant contribution to Purchase Intention, meaning that the more effective, informative, persuasive, and attractive the promotional activities are (both online and offline), the stronger the consumers’ motivation to purchase Wardah products on Shopee. Product Rating also has a significant contribution to Purchase Intention, indicating that the higher the ratings or positive reviews given by other users, the greater the consumers’ interest in purchasing Wardah products on Shopee. Good ratings can lower perceived risk, increase trust, and encourage consumers to make purchases, especially on e-commerce platforms.This research emphasizes the importance of pricing strategies, improving promotional quality, and managing product reviews and ratings as efforts to increase consumer interest and purchase decisions.

Security in e-commerce applications is a crucial factor that significantly affects user trust. Many users often feel anxious about the confidentiality of personal data, transaction security, and the potential for misuse of information. This study is a systematic literature review (SLR) using the PRISMA model, aiming to analyze in depth the influence of security on user trust in the context of e-commerce applications. Through this review, relevant previous studies on user security and trust were identified and evaluated to provide a more comprehensive understanding. The results of the analysis show that the improvement and implementation of superior security features, including strict data protection, multi-layered authentication, and transparent and robust privacy policies, have an essential role in growing and strengthening user trust. Guaranteed security not only creates a sense of convenience during the transaction process, but it is also very effective in increasing and maintaining user loyalty to the e-commerce platform in question. Improving security can be interpreted as a strategic investment for the sustainability of digital businesses.

Digital transformation in the health sector requires hospitals to improve service effectiveness through the use of Hospital Management Information Systems (HMIS). Berkah Pandeglang Regional General Hospital, as a regional hospital, still faces challenges in utilizing HMIS, such as limitations in infrastructure and user competence. This study aims to analyze the effect of SIMRS implementation and evaluation on the effectiveness of healthcare services. The research method uses a quantitative approach with a descriptive-verificative design. The research population consists of 278 healthcare workers, and 74 respondents were selected using proportionate stratified random sampling. Data were collected through closed questionnaires and analyzed using multiple linear regression to test the influence of variables. The results of the analysis show that the implementation and evaluation of SIMRS have a positive and significant effect on the effectiveness of health worker services. The most dominant components in implementation are the availability of hardware and human resource competence, while in evaluation, the most decisive aspects are the perception of usefulness and ease of use of the system. The conclusion of this study confirms that the success of SIMRS depends on the synergy between optimal implementation and systematic evaluation. Improvements in technological facilities, user training, and periodic monitoring are recommended to strengthen the effectiveness of health worker services at Berkah Pandeglang Regional General Hospital.

In today's digital era, the freight forwarding industry has become one of the fastest-growing sectors. The rapid growth of the digital economy has increased the need for fast, safe, and efficient delivery services. However, intense market competition in this industry has pushed companies to build a strong brand image. This is related to the increasingly fierce competition in the freight forwarding sector, such as JNE, SPX Standard, Tiki, and Pos Indonesia. This research is useful for companies and academics: it can serve as a shared reference for examining the influence of brand image on service usage decisions, in the development of theories and concepts in marketing and Islamic economics. The purpose of this study is to analyze the influence of brand image on the decision to use J&T Express's freight forwarding services. The research method used was quantitative, with a survey approach. A questionnaire was distributed to 117 respondents who were active users of J&T Express services. Data analysis was conducted using multiple linear regression with the help of SPSS version 26 software. The results showed that brand image had a positive and significant effect on the decision to use services, with a significance value of 0.015 (<0.05).

This research aims to throughly explore the differentiation strategy model implemented by the small-medium enterprise (SME) grocery store of  "Yussandi Komunika," in integrating digital transaction services such as prepaid credits, electricity tokens, and e-wallet top-ups, as an effort to create a competitive advantage. The background of the problem is driven by the highly competitive conditions in densely populated areas, where traditional grocery stores are compelled to transform in order to maintain their business relevance.Digital service innovation, presented through an adaptive and user-focused platform, has proven to be a core competency that is difficult to imitate and rare, simultaneously providing a sustainable competitive advantage. This innovation not only addresses the challenges of densely populated conditions but also establishes a new standard for efficiency and customer experience in a competitive market.The effective differentiation model for multi-service grocery stores in highly competitive areas is not solely based on price, but rather on a combination of services and the quality of interpersonal service. The store transforms into a "mini service point" offering one-stop shopping convenience for customers. The main differentiation strategies identified include: (1) Core Service Differentiation (offering comprehensive PPOB (Payment Point Online Banking) services and e-wallet balance availability), (2) Personnel Differentiation (quality of communication and speed of friendly service), and (3) Image Differentiation (creating a perception as a trustworthy and modern store).  

This study investigates how Bahasa Medan, a distinctive regional dialect from North Sumatra, is used, transformed, and sustained within the digital environment of TikTok. Drawing on Hymes’ (1972) theory of the speech community and supported by sociolinguistic frameworks from Gumperz (1982), Holmes (2013), Bell (1984), and Bucholtz and Hall (2005), the research explores how Medanese youth employ their dialect across multimodal forms of communication—spoken performances, textual captions, and interactive comment exchanges. Using qualitative descriptive methods, the study examines content from selected TikTok creators who integrate Bahasa Medan into their videos to express humor, identity, and solidarity. The findings reveal that TikTok functions as a digital speech community where dialectal expressions such as palak, sor, beserak, slek, berondok, and merajok serve as linguistic markers of belonging and cultural pride. Furthermore, users exhibit strategic code-switching among Bahasa Medan, standard Indonesian, and English to balance local authenticity with global participation. These interactions demonstrate how linguistic creativity, humor, and social engagement enable regional dialects to thrive in transnational digital spaces. The research ultimately shows that Bahasa Medan on TikTok is not merely a form of entertainment but a dynamic expression of identity, cultural continuity, and community in the era of globalized media.

Power transformer theft, a pervasive issue disrupting critical infrastructure, necessitates the development of cost-effective and energy-autonomous security solutions. This paper presents the design and implementation of a detection-focused anti-theft framework that integrates a Raspberry Pi Zero W, camera module, and passive infrared (PIR) motion sensors powered by a solar system for continuous monitoring. The system is designed for remote, off-grid deployment, utilizing a headless Raspberry Pi powered by a 5V solar panel and power bank to ensure energy autonomy. Upon motion detection, captured images are processed on the edge device using OpenCV’s Haar Cascade classifier, optimized for upper-body detection to minimize false positives and verify human presence. Captured images are processed locally on the edge device using OpenCV’s Haar Cascade classifier to confirm human presence before an alert is sent to the mobile application, emphasizing real-time operation and low latency. Once an intrusion is confirmed, the images are saved locally and uploaded via the Secure File Transfer Protocol to a custom-developed Android application. The app provides a dedicated remote monitoring interface, enabling secure file transfer and system access, while providing users with immediate notifications and image management capabilities. The system emphasizes low power consumption, real-time operation, and low deployment cost. Tests over 200 triggered events under varied environmental conditions achieved 90% detection accuracy with an average latency of 4.5 s. Solar autonomy was maintained for approximately 24 h under normal operation. It is concluded that the integration of solar power, edge computing of images, and mobile monitoring provides a feasible, scalable, and financially viable framework for securing transformers, especially in resource-constrained environments.

This study explores the implementation of an electronic Human Resource Management System (e-SDM) in the Gubeng sub-district of Surabaya to optimize civil servant (PNS) leave management. The primary focus is on assessing how digitalization improves efficiency, transparency, accountability, and service quality in human resource administration, particularly in leave processing. Traditionally, manual procedures required 7-14 days to approve leave requests, involved multiple steps, manual calculations, and were prone to errors, delays, and lack of transparency. The introduction of the e-SDM system significantly reduces processing time to approximately one day, enabling online submission, real-time monitoring, and electronic approval accessible anytime and anywhere via smartphones. The system automatically calculates leaves balances and prevents over-application, ensuring data accuracy and reducing misuse. Besides operational efficiency, the system enhances transparency by providing accessible real-time status updates, creating an audit trail for each decision, and making the process auditable and accountable. Despite these advantages, challenges such as user resistance, digital literacy, infrastructure issues, and system integration remain. This research employs descriptive-analytical methods, combining interviews, observations, and documentation, to analyze the effectiveness of e-SDM implementation. The findings indicate that digitalization has streamlined leave management, minimized administrative burdens, and improved data accuracy. Moreover, it fosters a fairer and more transparent work environment, reinforcing good governance principles and supporting Surabaya's vision to become a smart city. The research underscores the importance of technological adaptation within bureaucratic reforms and offers strategic recommendations for further system improvements. Overall, the successful adoption of e-SDM in Gubeng serves as a model for digital transformation in public service delivery, contributing to more efficient, transparent, and accountable governance in local government institutions.

The rapid advancement of smartphone technology has shaped consumer buying behavior, especially among students who depend on these devices for learning and social interaction. This research examines how product features and price perceptions influence students’ decisions to purchase Oppo smartphones in Malang City. Using a quantitative research design, data were obtained through questionnaires distributed to 428 respondents and processed using multiple linear regression analysis. The findings indicate that both product features and perceived price positively and significantly affect purchasing decisions, with product features demonstrating a more dominant role. The proposed model accounts for 66.2% of the variance in purchase decisions, suggesting that these two factors play a substantial part in shaping consumer choices. The results highlight the need for manufacturers like Oppo to focus on continuous feature improvements and maintain competitive pricing to strengthen market appeal. It is also suggested that future studies integrate additional variables such as brand image, marketing promotions, or user experience to offer a broader and more in-depth explanation of the determinants influencing smartphone purchase behavior.