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Male masculinity is a common theme in advertising. These potrayals often depict men as hardworking, resilient, and physically strong, thereby shaping an ideal male identity. This study uses Sara Mills’ critical discourse analysis perspective to examine the representation of the 2023 Extra Joss advertisement “Laki Buktikan!”. A qualitative descriptive approach is used, with data in the form of visuals, verbal narratives, and slogans that appear in advertising videos accessed via the TikTok application. The analysis will focus on the subjects and objects in the advertisement, the representation of masculinity, the position of the audience, the narrative structure, and the surrounding social context and gender ideology. The result of study show that the advertisement represents masculinity as an identity that must be continuously proven through strength, physical toughness, endurance, and a never-give-up attitude. Failure, defeat, and adversity are not condition that must be passively accepted, but rather condition demanding an active response from men to take concrete action. The advertisement not only promotes product, but also reproduces the ideology oh hegemonic masculinity by linking male self-proving to consuming Extra Joss energy drinks.

The prevalence of non-communicable degenerative diseases in Indonesia continues to rise, particularly affecting adolescents and productive age populations due to unhealthy lifestyle patterns and free radical exposure. Purple sweet potato leaves (Ipomoea batatas L.), a locally abundant resource often regarded merely as agricultural by-product, contain significant bioactive compounds including polyphenols, flavonoids, anthocyanins, and terpenoids demonstrating potent antioxidant properties with IC50 values of 47.99 ppm. This study employs a qualitative descriptive literature review approach, analyzing 28 scientific publications spanning 2018-2025 sourced from Google Scholar and PubMed databases to examine the potential of purple sweet potato leaves as effervescent tablet raw material for degenerative disease prevention. Findings reveal that bioactive constituents effectively neutralize free radicals, prevent lipid peroxidation, and protect cellular structures from oxidative damage linked to diabetes, cancer, and cardiovascular disorders. The effervescent tablet formulation provides strategic advantages including enhanced solubility, accelerated absorption rates due to elimination of disintegration processes, pleasant carbonation sensation masking unpleasant active ingredient taste, and superior gastrointestinal tolerance. This innovation offers promising prospects for degenerative disease prevention through local food resource utilization, though experimental validation regarding optimal formulation, effective dosage determination, and clinical efficacy assessment remains necessary for practical implementation.

This study aims to analyze the implementation of the Minimum Service Standards (SPM) for education administration in MTsN Batang, identify supporting and inhibiting factors, and formulate recommendations for service improvement. The study used a mixed-methods design with an evaluative approach to the CIPP model. Quantitative data were collected through questionnaires from 60 respondents, while qualitative data were collected through in-depth interviews and observations. Quantitative data were analyzed using descriptive statistics and Kruskal-Wallis tests, while qualitative data were analyzed using Miles and Huberman's thematic analysis. The study found that SPM implementation reached 72%, with the highest achievement in student administration (85%) and the lowest in financial administration (58%). The Kruskal-Wallis test showed a significant difference in perception between groups (p=0.032). The thematic analysis identified three themes: digitization of services, human resource capacity, and transparency of accountability. The implications of the research show the need to increase human resource capacity, optimize management information systems, and strengthen coordination with the Ministry of Religion.

This study aims to provide learning for hair dressing beginners in performing smoothing treatments on sensitive hair. The technique of using Hair Mask plays an important role in creating the illusion of firm eye folds, thus giving the impression of larger and more expressive eyes. This study uses an experimental method with a quantitative approach involving 4 models with sensitive and damaged hair to be assessed by 16 AKS Ibu Kartini Makeup students. The results of the study showed that the use of Hair Masks on sensitive hair is very necessary to coat the hair pigment before being exposed to smoothing cosmetics. These results can be proven that the success of student practice using Hair Masks is worth (X2) 31% compared to before using Hair Masks (X1) with an average value of 55%. It turns out that this technique is more effective and efficient in increasing success in smoothing because it reduces the risk of hair breakage. (p-value = 0.014). From this study it can be concluded that the use of Hair Masks on smoothing sensitive/damaged hair. This lesson makes a fairly good contribution to AKS Ibu Kartini students to be able to improve skills in smoothing sensitive hair.

The state of law and democracy are two concepts that are interrelated in the mechanism of managing the government of a country. Democracy provides the foundation for creating equality and equality of rights for all citizens, while the state of law emphasizes that power in a country must be subject to the rule of law, not the will of a particular individual or group. This research is a normative legal research with a normative juridical approach that seeks to explore the harmony of legal rules with applicable norms. The results of the study show that from the colonial period to the reform era, a lot of progress has been made in strengthening the principles of the rule of law, both formally and substantially. The 1998 reform was a momentum that marked a strong commitment to make Indonesia a democratic country of law, where every citizen has rights and obligations protected by law. In Indonesia, democracy has gone through various phases from the parliamentary era, Guided Democracy, New Order, to the reform era that provides greater space for people's involvement.

Reading literacy among 6th grade elementary students is often superficial, limiting their ability to analyze implicit meanings and connect texts to real-world contexts. This review examines the potential of deep learning as a pedagogical approach to enhance in-depth text comprehension. Deep learning emphasizes active engagement, reflection, and the construction of meaningful knowledge, aiming to foster critical thinking and improve comprehension. Recent studies highlight implementation strategies such as reflective journaling and interactive discussions, which have demonstrated significant improvements in students' critical thinking and comprehension scores (p < 0.05). These findings suggest that deep learning methods surpass traditional approaches by promoting higher-order cognitive skills, enabling students to analyze and interpret texts more effectively. However, challenges such as inadequate teacher training persist, which may hinder the full integration of deep learning techniques. To address these challenges, further research is needed to explore scalable digital tools that can support deep learning in diverse classroom settings. By examining the potential for digital integration, future studies could provide insights into how technology can facilitate the widespread adoption of deep learning strategies, making them more accessible and effective for a broader range of students. Ultimately, this review underscores the promise of deep learning in enhancing reading literacy and suggests that addressing the barriers to its implementation could have significant educational benefits.

: The rapid expansion of cybersecurity standards and threat intelligence frameworks has led to significant semantic fragmentation among security terminologies, hindering effective information retrieval and interoperability across systems. Traditional keyword-based search approaches are inadequate for capturing the contextual meaning of security terms, particularly within formal frameworks such as NIST, MITRE ATT&CK, and CWE. This study addresses this challenge by proposing CyberBERT, a transformer-based semantic search framework designed to align cybersecurity terminologies through deep contextual representation and ontology-driven reasoning. Research Objectives: The primary objective of this research is to develop a semantic retrieval model capable of understanding conceptual relationships between security terms beyond lexical similarity. Methodology: The proposed methodology fine-tunes a BERT-based model on the NIST Glossary corpus using a combination of masked language modeling and triplet loss objectives to generate discriminative semantic embeddings. These embeddings are further aligned with cybersecurity ontologies, including MITRE ATT&CK and CWE, to enhance semantic consistency and explainability. Semantic retrieval is performed using cosine similarity within a 768-dimensional embedding space and evaluated using Mean Reciprocal Rank (MRR) and Precision@K metrics. Results: Experimental results demonstrate that CyberBERT achieves an MRR of 0.832, outperforming domain-adapted baselines such as SecureBERT and CyBERT. The integration of ontology alignment improves semantic accuracy by over 6%, while robustness evaluations confirm resilience against adversarial linguistic perturbations. Visualization using t-SNE reveals coherent semantic clustering aligned with the five core NIST Cybersecurity Framework functions. Conclusions: In conclusion, CyberBERT effectively bridges semantic gaps across cybersecurity terminologies by combining transformer-based contextual learning with ontological reasoning. The framework offers a robust, interpretable, and scalable solution for semantic search, supporting improved interoperability and knowledge discovery in cybersecurity operations and standards harmonization.

This study discusses the application of the HSV color segmentation method for color-based object detection in digital images. The data used consist of digital images in JPG, PNG, or WebP format containing various colored objects, including red tomatoes, yellow bananas, green apples, orange oranges, purple akebia, brown sapodilla, and blue blueberries. The research process involves converting images from BGR to HSV, determining HSV ranges for each color, creating masks, performing segmentation, analyzing pixels, detecting contours, and visualizing results using bounding boxes. The results show that the HSV method effectively detects objects, separates them from the background, and provides quantitative information, including pixel count, area percentage, and average HSV values for each color. Red, yellow, green, orange, purple, brown, and blue colors were successfully segmented, displaying clear and accurate objects, both for single and multiple objects, under various sizes and lighting conditions. These findings confirm that the HSV method is a simple, fast, and effective approach for color-based image analysis.

Tingginya konsumsi makanan instan di kalangan anak-anak sekolah dasar telah menjadi perhatian penting karena potensi risiko kesehatan jangka panjangnya. Penelitian ini bertujuan untuk merancang karakter buku cerita bergambar interaktif sebagai media edukasi bagi anak-anak usia 9–12 tahun untuk memahami bahaya makanan instan dan mengembangkan kebiasaan makan yang sehat. Penelitian ini menggunakan pendekatan metode campuran yang dikombinasikan dengan metodologi desain, termasuk tinjauan pustaka, wawancara dengan guru, ahli gizi, dan ilustrator, dan kuesioner yang disebarkan kepada 114 responden untuk mengidentifikasi kebutuhan pendidikan anak-anak dan preferensi visual. Proses desain melibatkan identifikasi masalah, pengembangan konsep, pembuatan prototipe, dan validasi melalui jajak pendapat audiens. Desain ini menampilkan karakter utama Lala, Lita, Ibu, dan Maskot Perut, dengan ilustrasi kartun digital berwarna cerah. Hasil validasi menunjukkan bahwa karakter dan desain visual selaras dengan minat dan kebutuhan audiens target, menjadikan media ini efektif dalam menyampaikan pesan edukasi dengan cara yang menarik sekaligus memotivasi anak-anak untuk memahami risiko makanan instan.

Digital transformation has become an urgent necessity for madrasas in improving the quality of Islamic education amid the rapid advancement of technology. However, various national reports indicate that the implementation of digitalization in many madrasas still faces significant challenges, including low teacher competence, limited infrastructure, and the absence of leadership capable of directing the change process regularly. This study aims to provide an in-depth analysis of the strategies employed by madrasah principals in managing digital transformation as an effort to enhance technology-based learning quality. The research uses a descriptive qualitative approach, relying on secondary data such as scholarly articles, policy reports, and official documents from relevant educational institutions. The findings reveal that the success of improving technology-based learning quality highly depends on visionary and adaptive leadership, particularly in digital planning, teacher capacity building, infrastructure provision, digital learning culture development, and the implementation of data-driven monitoring and evaluation. This study emphasizes that technology becomes effective only when managed through strategic leadership capable of integrating digital innovations into madrasa governance in a sustainable manner.

Background: Magnetic Resonance Imaging (MRI) is one of the most important imaging modalities in medicine, especially for diagnosing spinal disorders. The Short Tau Inversion Recovery (STIR) sequence has the advantage of suppressing fat signals, but often produces images with a low Signal-to-Noise Ratio (SNR), so that noise can interfere with diagnostic quality. Therefore, image optimization methods through noise reduction and image quality enhancement techniques are needed. Objective: This study aims to analyze the effectiveness of combining the Wiener Filter with Contrast Stretching and Unsharp Mask in reducing noise and improving the quality of Lumbar Sagittal STIR MRI images. Method: This study used an experimental quantitative approach with lumbar sagittal STIR MRI images as the research object. The research process included applying the Wiener Filter as a noise removal method, then improving the quality with Contrast Stretching and Unsharp Mask. Image quality was evaluated quantitatively using the SNR, CNR, PSNR, and MSE parameters. Results: The application of a combination of Wiener Filter with Contrast Stretching and Unsharp Mask showed an increase in SNR and CNR values compared to before processing, as well as higher PSNR values with lower MSE. This indicates that this combination method is effective in reducing noise while sharpening the anatomical structure details in Lumbar Sagittal STIR MRI images. Conclusion: The combination of Wiener Filter with Contrast Stretching and Unsharp Mask has been proven to improve the quality of Lumbar Sagittal STIR MRI images with significant noise reduction, contrast enhancement, and image sharpness. This method has the potential to be implemented in radiology practice to improve diagnostic accuracy.

COVID-19 is a respiratory disease that poses a current threat. Public non-compliance with health protocols can negatively impact COVID-19 transmission. A person's behavior significantly impacts their health. The design of this research is quantitative descriptive with Cross Sectional design, the population in the study is all productive-age Banda Aceh residents totaling 252,899 people and the sample in this study totaling 399 people who have met the inclusion criteria with Accidental Sampling technique using statistical analysis of the t-test (paired-samples t test) and One Way Anova Repeated Measure Test using the Stata 14 program. The results of the study show that there are significant changes in community behavior after 2 years of the Covid-19 pandemic for 3 time periods (the beginning of the Covid-19 pandemic (2020), 1 year ago (2021) and currently (2022)) related to the 5M Health Protocol (p-value 0.0000), Barriers to Mask Use (p-value 0.0000), Information Related to Handling Covid-19 (p-value 0.0001), Perception (p-value 0.0000), Attitude (p-value 0.0000, and Behavior Towards Covid-19 (p-value 0.0000). However, the t-test results showed no significant change in community behavior in the Attitude variable between 1 year ago (2021) and now (2022) (p-value 0.8997) and in the Information Regarding Handling of Covid-19 variable between the beginning of the pandemic (2020) and now (2022) (p-value 0.3048). The most dominant change in community behavior after 2 years of the Covid-19 pandemic was in the 5M Health Protocol variable, in the period 1 year ago (2021) and now (2022), with a p-value of 0.0000 and a difference of 3.24. It is hoped that the community will continue to strive to improve their health behavior, so that the level of public health is maintained, and hopefully we are truly free from the Covid-19 pandemic

Magnetic Resonance Imaging (MRI) with Arterial Spin Labeling (ASL) is a non-invasive technique commonly used to assess cerebral perfusion, especially in stroke patients. However, ASL images often suffer from low contrast and high noise, which can hinder diagnostic accuracy in visualizing perfusion areas and detecting ischemic lesions. Image enhancement techniques, such as the unsharp mask, offer a potential solution to improve image quality. The effectiveness of this enhancement depends on the kernel size used in the unsharp mask filter. This study evaluates the impact of different kernel sizes (3×3, 5×5, and 7×7) on the quality of ASL brain images, focusing on both quantitative and qualitative improvements. A total of 63 ASL brain MRI images from stroke patients were processed using unsharp mask filters with the three kernel sizes. Quantitative analysis measured Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR), while qualitative assessment involved three radiologists independently evaluating five aspects of image quality: perfusion area clarity, grey-white matter contrast, ischemic lesion boundary visibility, noise level, and overall visual quality. Statistical tests, including Friedman and Wilcoxon, were applied to compare results across the kernel sizes. Results revealed that the 3×3 kernel achieved the best results in both quantitative and qualitative assessments, with the highest SNR, CNR, and visual quality scores. Significant differences (p < 0.05) were found between kernel sizes, confirming the superiority of the 3×3 kernel. The 7×7 kernel reduced noise but caused oversmoothing, negatively impacting image sharpness. In conclusion, the 3×3 kernel provides an optimal balance between noise reduction and edge preservation, enhancing ASL brain image quality for stroke diagnosis.

Digital image processing is a rapidly developing branch of computer science and has many applications in everyday life. One of the fields that most often utilizes this technique is object detection and color identification in images and videos. This study specifically aims to implement the thresholding method in the HSV (Hue, Saturation, Value) color space to detect three basic colors, namely red, green, and blue, in digital images. The research process begins with uploading images using the Google Colab platform, a cloud-based computing environment that makes it easy for users to run Python programs without requiring additional software installation. After the image is uploaded, the next step is to convert it from the RGB (Red, Green, Blue) color space to the HSV color space. This conversion is important because the HSV color space is more suitable for use in the color segmentation process. The Hue value represents the type of color, Saturation shows the level of saturation, while Value describes the level of brightness. Once the image is in the HSV color space, the next step is to determine the HSV value range for each basic color. This range is determined based on experimental results and references from related literature. Using this range, masking is performed to extract the appropriate pixels so that only the red, green, or blue portions of the image are visible, while the other colors are reduced. The results show that the thresholding method in the HSV color space is capable of detecting primary colors with a good level of visual accuracy, especially in simple images with contrasting backgrounds. The implementation of this program is relatively lightweight, easy to run directly in Google Colab, and does not require high-spec hardware. Therefore, this method is very suitable for use as basic learning material for digital image processing, both for students and novice researchers.

In helping to support the appearance and confidence of the skin needs to be treated especially for dry skin. Having a dry facial skin causes discomfort because the cosmetics used will be difficult to stick to the skin. In addition, weather factors, the use of unsuitable cosmetics, exposed to excessive sun exposure, and unhealthy lifestyles can cause the skin to become dry. The purpose of this study was to determine the process of making gel masks from carrot extracts and seen from laboratory tests, organoleptic tests and hedonic tests. This study uses quantitative methods with an experimental approach. Data collection techniques through observation, documentation and observation sheets that can be seen from the results of laboratory tests, organoleptic tests (texture, color, aroma, adhesion) and hedonic tests (panelists). The results of the study obtained from the results of laboratory tests by looking at the pH level of each formulation are in a safe range of 4-5. In the organoleptic test, panelists declared F1 as a preparation of less thick, orange, and lack of scented in carrot. In the F2 formulation, panelists declare as a texture preparation that is thick, orange, and scented typical of carrots. In the F3 formulation, the panelists declare that the preparation is less thick, less orange, and a typical carrot scented. In the F4 formulation, panelists declare as a very thick, non -orange preparation. And very scented typical of carrots. In the adhesion of the panelist states from all formulations that F4 is very attached. In the hedonic test, the preparation that many panelists like, namely the F4 preparation, is very thick, not orange and very scented typical of carrots. Thus the gel mask of carrot extract can be used as material for making gel masks seen from laboratory tests, organoleptic tests, and hedonic tests.

Relations in mathematics are a fundamental concept that describe the connection between two sets. This concept is crucial because it forms the foundation for understanding functions and various other mathematical topics. In everyday life, relations can be found in numerous real-world situations, such as the relationship between teachers and their students, sellers and buyers, or students and their exam scores. By understanding relations, students can see how elements from one set are linked to elements in another set based on specific rules. Unfortunately, many students still find it difficult to grasp the concept of relations because it is often taught in an abstract way, filled with mathematical symbols that are not connected to their real-life experiences. As a result, students may feel that the topic is irrelevant to their lives, leading to a lack of interest and poor comprehension. In fact, if taught contextually and practically, the concept of relations can serve as a key bridge to help students understand functions and their relevance in the real world. This article aims to explain the concept of relations through a more practical and relatable approach. For example, it can be illustrated by connecting students' names with their attendance numbers, or linking foods with their nutritional contents. Through these examples, students can see that relations are not just rigid parts of a math lesson but also reflect meaningful connections in everyday life. In this way, it is expected that students will gain a more comprehensive understanding of relations—not only mathematically but also in terms of practical application and functionality. A solid understanding of relations will make it easier for students to learn advanced concepts such as functions, mappings, and mathematical logic. Therefore, a learning approach that emphasizes contextual understanding is essential, so that students are not merely memorizing formulas but are also capable of applying the concept of relations in real-world situations.

This article explores the concept of sets in mathematics, a fundamental foundation for various disciplines. The discussion includes the definition of a set as a well-defined collection of objects, as well as various methods of presenting them such as enumeration, description of properties, set-forming notation, and Venn diagrams. In addition, the article outlines the various types of sets (empty, universe, equal, part, disjoint, crossed, equivalent, power) and explains the fundamental properties of set operations (identity, dominance, complement, idempotent, absorption, commutative, associative, distributive, De Morgan). The primary objective is to provide a concise yet comprehensive understanding of sets as a foundational pillar of logical and mathematical thinking.

Panji Kahirupan Dance is a Cirebonese mask dance created by H. Taufik Hidayat, the founder of Sanggar Ki Bagus Rangin. This dance portrays the journey of human life, from pre-birth to adulthood, inspired by the changing characters (wanda) of the Cirebon mask tradition. This study aims to describe and analyze the symbolic meanings embedded in the Panji Kahirupan Dance. The research uses a qualitative method with a semiotic approach, allowing the researcher to explore both the denotative and connotative meanings of the symbolic elements in the dance. Data were collected through observation, interviews, and documentation, and validated using triangulation of techniques and sources. The data analysis involves data reduction to select relevant information, data presentation to synthesize findings, and conclusion drawing to interpret the symbolic meanings of each performance element. The costumes carry symbolic meanings through their colors: white represents the sanctity of life’s beginning, yellow symbolizes spirit, and red denotes ambition. The soft gamelan music contributes to a spiritual and contemplative atmosphere. The floor patterns, such as circles and straight lines, symbolize the life cycle and life’s purpose.

This normative legal study examines the potential and challenges of implementing restorative justice approaches in cases involving corporate perpetrators within Indonesia's criminal justice system. The research employs statute, conceptual, and case approaches to analyze legal principles, norms, and court decisions related to corporate criminal liability and restorative justice mechanisms. Through comprehensive literature review of international academic databases and examination of Indonesia's legal framework, including the New Criminal Code of 2023 and Prosecutor's Regulation No. 15 of 2020, the study reveals that restorative justice offers a transformative alternative to traditional retributive models by prioritizing restoration, rehabilitation, and reconciliation between corporate offenders, victims, and affected communities. The dual track system selective model emerges as the most appropriate framework for corporate restorative justice implementation, enabling selective application while maintaining prosecutorial discretion for serious offenses. However, significant challenges persist, including the absence of specific regulatory frameworks for corporate actors, structural complexities arising from the non-personified nature of corporate entities, and profound power imbalances between corporations and victims that threaten process integrity. The study demonstrates that successful implementation requires comprehensive legal reforms, enhanced institutional capacity, robust victim support mechanisms, and safeguards against corporate manipulation. The research concludes that while restorative justice holds considerable promise for enhancing corporate accountability and victim restoration, effective implementation is contingent upon establishing clear legal frameworks, technical guidelines, and protective measures that address inherent power asymmetries between corporate offenders and their victims.

Keselamatan dan Kesehatan Kerja (K3) merupakan kegiatan yang wajib ada dalam pekerjaan konstruksi termasuk pada proyek jalan lingkungan yang dikerjakan oleh pemerintah ataupun pihak swasta dengan sumber anggaran kecil ataupun besar. Hal ini karena setiap pekerjaan konstruksi memiliki potensi risiko kecelakaan yang harus mendapat perhatian serius. Sasaran pada penelitian ini bertujuan untuk mengetahui kesesuaian penerapan perlengkapan K3 yang telah direncanakan dalam dokumen kontrak, khususnya Rencana Anggaran Biaya (RAB) terhadap regulasi K3 yang berlaku, dengan menggunakan metode deskriptif kualitatif melalui analisis dokumen. Hasil dari penelitian ini menunjukan bahwa perlengkapan K3 pada Proyek Peningkatan Jalan Menteng XA di kota Palangka Raya tahun 2024 telah memenuhi ketentuan dasar, namun masih ada perlengkapan yang perlu ditambahkan sesuai ketentuan regulasi k3 seperti masker dan kacamata pelindung yang memiliki fungsi mengantipasi paparan bahan kimia, debu dan asap.