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This study aims to develop a sentiment classification method for YouTube user comments related to the game Love and Deepspace using the Naïve Bayes algorithm, focusing on improving the text data processing and understanding user perceptions. Comment data were collected through scraping from YouTube videos, followed by preprocessing including text cleaning, normalization, stopword removal, stemming, and translation into English. Initial labeling was conducted using TextBlob, then the data were randomly sampled for training the Naïve Bayes model. Evaluation involved comparing sentiment distributions and visualization using Word Cloud and bar charts. The Naïve Bayes model achieved an accuracy of 77.36% in sentiment classification. The sentiment distribution shows differences between TextBlob (positive: 1,011, neutral: 1,312, negative: 575) and Naïve Bayes (positive: 901, neutral: 1,627, negative: 370), with Naïve Bayes being more conservative. The Word Cloud visualization identifies dominant words such as "bang," "game," and "main," while the bar chart shows the largest proportion of neutral sentiment. Naïve Bayes is effective for sentiment classification on informal comment data, with significant differences from rule-based methods like TextBlob. This research contributes to the development of text data processing techniques and user perception analysis, as well as opening up optimization opportunities with other algorithms like SVM for better accuracy.

This study investigates the role of Google Translate in supporting English vocabulary learning among junior high school students in the digital era. The research employs a qualitative approach involving seventh-grade students at SMP Negeri 19 Medan. Data were collected through pre-test and post-test, classroom observation, interviews, and documentation. The findings reveal that Google Translate significantly helps students understand vocabulary more quickly, improves their learning efficiency, and increases their confidence in completing English tasks. Students also demonstrate greater autonomy in exploring new vocabulary independently. However, the study also identifies challenges, particularly students’ tendency to rely excessively on direct translation without fully understanding context, which may lead to superficial learning. Therefore, teacher guidance is essential to ensure the effective and critical use of this tool. The study concludes that Google Translate can serve as a valuable learning resource when integrated appropriately into classroom instruction. The findings contribute to the development of technology-enhanced language learning and provide practical implications for teachers in utilizing digital tools effectively.

The increase in the number of elderly residents demands the provision of residential facilities that not only meet physical needs, but also support the psychological and social well-being of their users. This study aims to formulate the concept of behavioral architecture-based nursing home design by focusing on the relationship between elderly activity patterns, privacy levels, and spatial relationships of space in the local context of Indonesia. This study uses a qualitative-descriptive approach in the framework of architectural design, with data collection through observation of elderly activities, site analysis, and documentation studies. Activity data was analyzed to identify space needs and usage patterns, then synthesized with site characteristics to formulate the concepts of zoning, circulation, and behavior-based spatial relationships. The results of the study show that the activities of the elderly form a layered behavioral structure, including residential and health activities as primary needs as well as social, productive, and educational activities as support for psychosocial welfare. Hierarchically arranged space zoning based on privacy levels has been proven to improve the readability of the space, sense of security, and comfort of the elderly. The integration of green open spaces as part of the activity system also strengthens support for light physical activity and social interaction. This study confirms that the application of behavioral architecture allows the translation of data on elderly behavior and site conditions into a contextual, humanist, and quality-of-life-oriented design concept. These findings provide practical implications for designers and policymakers in the development of sustainable elderly housing.

Inconsistent terminology across cybersecurity frameworks undermines global governance and interoperability. The National Institute of Standards and Technology Cybersecurity Framework (NIST CSF 2.0) and ISO/IEC 27001:2022 share similar objectives but diverge semantically in defining risk, control, and resilience. This semantic gap causes difficulties in compliance mapping and automated policy translation. Research Objectives: This study aims to analyze the semantic similarity and divergence between NIST and ISO/IEC 27000 terminologies, identify conceptual structures influencing interoperability, and propose an AI-assisted foundation for harmonizing cybersecurity language globally. Methodology: A mixed-method semantic comparative design integrates Natural Language Processing (NLP) and ontology mapping. Using the nist_glossary.csv dataset and ISO vocabularies, terms were normalized and analyzed via cosine similarity using sentence-transformer embeddings. Ontological alignment was visualized through the Semantic Threat Graph (STG) and validated by certified experts using Cohen’s Kappa reliability tests. Results: From 672 term pairs, results show 40.9% high semantic equivalence, 38.8% partial overlap, and 20.3% semantic divergence. Strongest alignment appears in “Protect” and “Identify” domains, while divergences occur in governance and recovery-related terms. Ontology mapping revealed three conceptual clusters—Risk Governance, Technical Safeguards, and Organizational Readiness. Conclusions: Findings confirm a 79.7% total semantic alignment, indicating strong potential for harmonizing global cybersecurity standards. The study contributes an empirical model combining computational linguistics and AI-based ontology mapping to establish semantic interoperability, enabling unified cybersecurity governance and AI-driven compliance automation. Keywords: Semantic Interoperability; Ontology Mapping; Cybersecurity Frameworks; Terminology Alignment; AI Harmonization

This research is motivated by the importance of understanding the Heart Sutra within the framework of Humanistic Buddhism, especially for students of Buddhist religious education. The main problem lies in the limited understanding of the relevance of the Heart Sutra to humanistic values ​​in the context of modern life. This study aims to explain the relevance of the Heart Sutra teachings in building applicable spiritual, ethical, and social awareness. The method used is a literature study with a descriptive qualitative approach through text analysis and academic literature review. Data were obtained from primary sources in the form of translations of the Heart Sutra and secondary sources including journals, books, and scientific articles related to Humanistic Buddhism. The results of the study show that the teachings of sunyata (emptiness) in the Heart Sutra not only have profound philosophical meaning, but also provide practical implications in everyday life. The Heart Sutra is able to strengthen the philosophical foundation of Humanistic Buddhism, foster an attitude of compassion, wisdom, and tolerance, and serve as a relevant ethical guideline in facing the dynamics and challenges of modern society.

The thinking process carried out by teachers occurs in three phases, namely before learning, during learning, and after learning. The results of the analysis of these processes have the potential to produce innovative didactic designs, and these three processes can be formulated as a series of steps to produce new didactic designs. This series of activities is formulated as Didactic Design Research (DDR). Didactic Design Research basically consists of three stages, namely: (1) analysis of the didactic situation before learning which is in the form of a Hypothetical Didactic Design including ADP, 2) metapedidactic analysis, and 3) retrospective analysis, namely an analysis that links the results of the analysis of the hypothetical didactic situation with the results of the metapedidactic analysis. From these three stages, an Empirical Didactic Design will be obtained which is not closed to being continuously refined through the three stages of DDR.

This study explores the translation shifts found in the soundtrack of the film Rapunzel – Tangled, specifically in the German-to-Indonesian translation. The objective is to identify the types of translation shifts and analyze their distribution and tendencies during the translation process. The research data were taken from three songs: "Wann fängt mein Leben an?", "Mutter weiß mehr", and "Endlich sehe ich das Licht". A qualitative descriptive method was employed, focusing on lines containing translation shifts. Data were collected through documentation and analyzed based on Catford’s (1965) theory of translation shifts. A total of 74 translation shifts were identified, with the highest distribution in "Mutter weiß mehr" (32 shifts), followed by "Wann fängt mein Leben an?" and "Endlich sehe ich das Licht" (21 shifts each). In "Wann fängt mein Leben an?", structural shifts dominated, making up 38.9% of the shifts, followed by class and unit shifts (27.8% each), and intrasystem shifts at 5.5%. In "Mutter weiß mehr", structural shifts accounted for 35.4%, class shifts 34.1%, unit shifts 28%, and intrasystem shifts 2.4%. In "Endlich sehe ich das Licht", class shifts were the most prevalent (33.3%), followed by unit shifts (31.7%), structural shifts (30%), and intrasystem shifts (5%). The study concludes that structural and class shifts are the dominant strategies used in translating the soundtrack, helping to manage linguistic differences while maintaining meaning, musicality, and emotional impact in the target language.

This study is aimed at analyzing the degree of equivalence in the translation of Deutsche Welle (DW) news texts from German into Indonesian by applying Mona Baker’s theoretical framework. A qualitative descriptive method was employed, with four DW news texts and their Indonesian translations serving as the data source. The analysis focused on equivalence at the word level and above the word level, considering syntactic, lexical, cohesive, and communicative functional aspects of the text. The findings indicate that the degree of translational equivalence varies, ranging from high to low levels. The “equivalent” category was found to be dominant, accounting for 57.6%, suggesting that most translations were able to maintain the meaning and function of the source text. Meanwhile, the categories “less equivalent” (22.9%) and “non-equivalent” (19.5%) reflect shifts in meaning, loss of information, and inaccuracies in lexical correspondences and grammatical structures. These results highlight the challenges in maintaining full equivalence during translation.

Globalization has brought significant impacts across various sectors of life, including language and literature. Rapid flows of information, intercultural interactions, and the dominance of international languages such as English have triggered changes, adaptations, and even identity confusion in the use of local languages and the development of literary works. This paper explores the influence of globalization on the evolution of language and literature, both in the context of preservation and creativity. Language undergoes modifications in structure and vocabulary as a result of cultural interaction and technological advancement, while literature evolves in terms of genres and media, as reflected in the emergence of digital literature and literacy phenomena on social media platforms. On the other hand, globalization also provides opportunities for local literary works to reach international audiences through translation and digital media. Using a descriptive and analytical approach, this paper highlights the challenges and opportunities arising from the intersection of globalization, language, and literature, as well as their significance in formulating strategies to maintain cultural identity through language and literary expression.

Globalization has brought significant impacts across various sectors of life, including language and literature. Rapid flows of information, intercultural interactions, and the dominance of international languages such as English have triggered changes, adaptations, and even identity confusion in the use of local languages and the development of literary works. This paper explores the influence of globalization on the evolution of language and literature, both in the context of preservation and creativity. Language undergoes modifications in structure and vocabulary as a result of cultural interaction and technological advancement, while literature evolves in terms of genres and media, as reflected in the emergence of digital literature and literacy phenomena on social media platforms. On the other hand, globalization also provides opportunities for local literary works to reach international audiences through translation and digital media. Using a descriptive and analytical approach, this paper highlights the challenges and opportunities arising from the intersection of globalization, language, and literature, as well as their significance in formulating strategies to maintain cultural identity through language and literary expression.

This research focusses on translators working with languages that have diverse promotional language systems and cultures. The study is based on the modulation theory given by Vinay and Darbelnet (1995). This research intends to highlight the changes in point of view produced by translators in translating texts from English into Indonesian. The data source of this study is Garuda Indonesia magazine, which is presented in English as well as its Indonesian translation. The research indicates that translators change their perspective based on various factors to produce a target language that is equivalent to the source language while retaining the original meaning. The changes include a) abstract for concrete, b) explicative modulation, c) the part for the whole, d) one part for another, e) reversal of terms, f) negation of opposite, g) active to passive, h) exchange of intervals for limits. The change in perspective creates a cultural bridge in translation involving different languages and cultures.

Objective: Autoimmune diseases are complex disorders that arise when the immune system loses tolerance to self-antigens, leading to chronic inflammation and tissue damage. To understand disease pathogenesis and to evaluate therapeutic efficacy, animal models are widely used in autoimmune research. This review aims to analyze various types of animal models employed in studies of autoimmune diseases such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), type 1 diabetes mellitus (T1DM), and multiple sclerosis (MS), with a particular focus on reproducibility and clinical applicability. Methods: This study was conducted through the selection and analysis of scientific literature published over the last ten years (2015–2025), using specific keywords including “clinical application,” “autoimmunity,” “animal models,” “humanized mice,” “lupus,” “rheumatoid arthritis,” “reproducibility,” and “translational research.” Literature searches were performed in major databases such as Google Scholar, PubMed, ScienceDirect, and Scopus. Results: Spontaneous models, such as NOD and MRL/lpr mice, exhibit close resemblance to human disease pathogenesis but are influenced by strain variability and environmental factors. Induced models, including collagen-induced arthritis (CIA) and experimental autoimmune encephalomyelitis (EAE), allow greater control over disease onset but do not fully capture the clinical complexity observed in humans. Humanized models demonstrate high translational relevance; however, their use is constrained by high costs and technical limitations. Conclusion: No single animal model is universally ideal for studying autoimmune diseases. Model selection should be based on biological relevance, reproducibility of outcomes, and the potential for clinical translation in autoimmune disease research.

In the Independent Curriculum implemented in schools starting the 2024/2025 academic year, there are Learning Outcomes (CP) that read "Students are able to modify/deconstruct literary works for creative economic purposes" and "Students are able to translate one text into another for creative economic purposes". In reality, in schools, there are still few teachers who connect literary works with economic issues, many teachers are still unfamiliar with the concept of translation, not many teachers have participated in translation training, and there is no guidebook for translating literary texts into non-literary texts or vice versa. This also applies to high school Indonesian Language teachers in Rembang Regency. Combining these two Learning Outcomes and connecting them to conditions in society, this community service conducted training on translating literary works into advertising texts for high school Indonesian Language teachers in Rembang Regency. The training was carried out with the first stage providing material on translation and advertising and the second stage providing mentoring to teachers to practice translating literary works into advertising.

Quiet quitting refers to a phenomenon in which employees do not formally resign from their jobs but intentionally limit their work efforts to the minimum required. This study aims to adapt the Quiet Quitting Scale developed by Galanis et al. (2023) into the Indonesian context. A quantitative approach was employed involving 100 respondents drawn from both private and government sectors. The adaptation process included forward translation by three linguists, synthesis of the translated versions, and cultural adjustment to ensure contextual relevance. Data were analyzed using Confirmatory Factor Analysis (CFA) based on a three-factor model consisting of detachment, lack of initiative, and lack of motivation. The results indicate that the Indonesian version of the Quiet Quitting Scale demonstrates acceptable construct validity across the proposed factors. However, several items still require refinement, suggesting that further development and validation with larger and more diverse samples are necessary to strengthen the scale’s psychometric properties.

Abbreviation is a common linguistic strategy used to achieve efficiency and clarity in modern communication. This study examines the abbreviation systems of English and Indonesian through a contrastive linguistic approach, focusing on morphological patterns, phonological constraints, and usage conventions. Employing a qualitative descriptive design, the data were collected from established linguistic references and analyzed using classical contrastive analysis principles. The findings reveal that English abbreviation formation is structurally flexible, allowing both pronounceable acronyms and non-pronounceable initialisms, often maintaining complex consonant clusters and orthographic capitalization. In contrast, Indonesian abbreviation formation is strongly influenced by phonological preferences, particularly ease of pronunciation and conformity to open syllable structures, resulting in forms that closely resemble ordinary lexical items. These structural differences suggest potential sources of negative transfer for language learners and challenges in translation practices. The study concludes that abbreviation systems are shaped not only by linguistic rules but also by sociocultural and communicative needs. Understanding these contrasts is essential for language teaching, translation, and further comparative linguistic research.

This study traces the historical and intellectual processes that enabled Plato's ideas to enter the tradition of Islamic philosophy and subsequently influence Islamic boarding school education in Indonesia. Starting from the increasing openness of Islamic boarding schools to classical humanities, this study aims to understand how Plato's ideas were transferred from the context of Ancient Greece, reinterpreted by Muslim philosophers, and integrated into traditional learning practices. Using a library-based qualitative approach with hermeneutic, historical-intellectual, and thematic methods, this study analyzes the transmission pathways that include the Abbasid translation movement, the interpretive contributions of figures such as Al-Kindi, Al-Farabi, and Ibn Sina, and the absorption of concepts through literature on ethics, logic, and adab. The findings show that Islamic boarding schools did not inherit Plato's ideas directly, but rather through the Islamic philosophical tradition that reshaped Platonic elements to fit the Islamic intellectual framework. Concepts related to spiritual education, character building, and ethical rationality are in line with the orientation of tazkiyah al-nafs, which is the foundation of Islamic boarding school pedagogy. This study confirms that the relationship between Plato's ideas and Islamic education emerged through a long creative process, not merely a transfer of texts. Practically, these findings highlight opportunities to develop a more reflective, critical, and virtue-centered pesantren curriculum, while encouraging further ethnographic research to explore how the classical philosophical heritage is reinterpreted in contemporary santri learning practices.

Language barriers represent one of the most significant obstacles to educational equity and access worldwide. This study investigates the application of Natural Language Processing (NLP) technologies in multilingual educational contexts to facilitate cross-linguistic learning and improve educational outcomes for linguistically diverse student populations. We implemented and evaluated a comprehensive NLP-powered multilingual learning platform across 47 educational institutions in 12 countries, serving 8,450 students speaking 23 different languages. Our experimental framework integrated machine translation, speech recognition, multilingual content generation, and adaptive language learning algorithms. Results demonstrate that NLP-enhanced multilingual education improved student comprehension by 43.6% (p<0.001), increased participation rates by 67.8%, and reduced achievement gaps between native and non-native speakers by 52.4%. Students using NLP-assisted learning tools achieved test scores averaging 78.3% compared to 54.7% for control groups. However, challenges persist regarding cultural context preservation, idiomatic expression handling, and equitable performance across language families. This research provides evidence that NLP technologies can effectively democratize education across linguistic boundaries while identifying critical areas requiring continued development.

Communication is a fundamental human need for conveying information and ideas. However, individuals who are deaf and mute face difficulties in communicating with the broader community that does not understand sign language. This study aims to design and implement a real-time static sign language translator into speech using five flex sensors, an MPU6050 sensor, a Raspberry Pi Pico, an ADS1115 ADC module, and a DFPlayer Mini module as the audio output medium. Testing results show that the device successfully recognizes finger movements and hand orientation. The system is capable of playing audio output corresponding to recognized gestures, with the shortest latency recorded at 1.1 seconds and the longest at 2.8 seconds, achieving a detection accuracy rate of 75% based on 60 tests across 12 sign words. This device supports the translation of 12 simple sign words. The implementation demonstrates potential as an assistive communication tool, although further development is needed to improve accuracy, expand vocabulary, and conduct trials directly with deaf or mute users.

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.

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.