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The present study aims to identify and analyse idiomatic expressions in the lyrics of "Shake It Off" by Taylor Swift. Idioms are a form of non literal expression which often pose a challenge for English language learners, due to the fact that their literal meanings are not easily discernible. Utilising a descriptive qualitative approach, this research analyses idioms based on Makkai's (1972) classification, which includes six types: phrasal verb idioms, tournure idioms, irreversible binomial idioms, phrasal compound idioms, incorporating verb idioms, and pseudo idioms. The findings indicate that the composition is replete with idiomatic usage, reflecting emotional meanings and social messages implicitly. A total of fourteen idioms were identified, which serve to reinforce Taylor Swift's stylistic language and make the song an effective and contextual medium for the purposes of English language learning. It is anticipated that these findings will contribute to the development of language teaching, particularly with regard to the comprehension of idiomatic meaning within the context of popular culture.

This study aims to analyze market sentiment towards Gold Financing Products (PKE) in Islamic banking before and after the Trump Effect phenomenon using the text mining method. This technique involves extracting information from unstructured text data to then be visualized and analyzed using the Natural Language Processing (NLP) approach and a RoBERTa-based classification model. Data was collected through web scraping from the X application with the help of API and processed using Google Colab. From a total of 4,074 tweets analyzed, it was found that the majority of public sentiment was neutral (59%), followed by negative (24%) and positive (17%). This reflects the public's tendency to discuss informatively rather than emotionally, although there was a spike in negative sentiment in certain periods indicating sensitivity to global dynamics, especially the impact of the Trump Effect on gold prices. The resulting wordcloud reveals key topics such as gold prices, buying and selling activities, and institutions such as Pegadaian Syariah and BSI. Terms such as "sharia", "riba", and "principles" emphasize the importance of Islamic financial values ​​in public perception. The results of this study indicate that text mining-based sentiment analysis is effective in capturing the dynamics of public opinion in real-time and can be a strategic tool for Islamic financial institutions in responding to market changes.

The pharmaceutical industry produces solid, liquid, and gaseous waste containing active pharmaceutical ingredients that pose serious environmental risks. These wastes can disrupt ecosystems and accelerate antimicrobial resistance. This systematic literature review examines pharmaceutical waste concepts, classifications, characteristics, and relevant regulatory frameworks. It also addresses ecotoxicological effects on aquatic and terrestrial ecosystems, antibiotic contamination and resistance, water and soil pollution, treatment technologies, industrial policies, and best practices. Findings show that conventional wastewater treatment is largely ineffective at removing pharmaceutical residues, resulting in their presence in surface water, soil, and even drinking water. Compounds such as β-blockers, cytostatics, antibiotics, and hormones harm aquatic life by impairing reproduction and causing mutations. Antibiotic-laden industrial waste contributes to the emergence of resistant bacteria. Recommended treatment methods include biothermal processes, advanced oxidation (e.g., UV/H₂O₂, ozonation), adsorption (activated carbon), coagulation-flocculation, and controlled incineration. Stronger enforcement of hazardous waste regulations (e.g., Government Regulation No. 101/2014, Ministry of Environment and Forestry Regulation No. 56/2015) and adherence to WHO (2025) guidelines are essential. In conclusion, multisectoral collaboration (One Health), improved waste treatment capacity, and adoption of best practices are crucial to preventing pharmaceutical pollution and promoting environmental sustainability.

Fiqh al-Lughah is a discipline that examines the philosophical and historical aspects of the Arabic language, including the factors influencing its development. One of the most rapidly growing branches of Arabic language studies is Nahwu (grammar), which plays a crucial role in understanding linguistic structures and rules. This study aims to analyze the relationship between Fiqh al-Lughah and the development of Nahwu and how a deeper understanding of Fiqh al-Lughah contributes to the analysis and application of Nahwu rules. This research employs a qualitative method with a descriptive-analytical approach based on classical and modern literature reviews. The findings indicate that Fiqh al-Lughah significantly influences the formation of Nahwu theories, particularly in the historical development of grammatical rules, word classification, and syntactic concepts in Arabic.

Digital learning applications like HeyJapan are increasingly popular. User reviews on platforms such as Google Play Store contain valuable information on user perceptions and experiences. To process this information systematically, this study employs a Natural Language Processing (NLP) approach to analyze sentiment toward the HeyJapan application. Data was collected using web scraping techniques with Python and the google play scraper library, resulting in 1,000 latest user reviews. The analysis included data collection, preprocessing, sentiment labeling using TextBlob, visualization, modeling with Logistic Regression, and evaluation. After preprocessing, 923 valid reviews were classified into three sentiment categories based on polarity which are positive, neutral, and negative. Results showed 71.4% of reviews positive, 26.1% neutral, and 2.5% negative. Visualizations in pie charts and word clouds provided an overview of user perceptions. Modeling with TF-IDF and Logistic Regression achieved 88% accuracy with the highest f1-score in the positive sentiment category. Evaluation indicates the model is fairly reliable in classifying sentiments, especially for positive and neutral categories, though negative sentiment classification needs improvement. This study shows the NLP approach can evaluate user perceptions of educational applications based on reviews and serve as a basis for improving foreign language learning app quality.

The problem in this study is the ability of the control object of students at Elementary School 14 Limo Kaum Batusangkar which is still relatively low, this is thought to be caused by many factors. The purpose of this study was to determine the profile of the control object ability of students at Elementary School 14 Limo Kaum Batusangkar. This type of research is descriptive which aims to reveal how the description of the basic movement skills of the control object in students at Elementary School 14 Limo Kaum Batusangkar during the research period from November to January 2025. The place of this research was at Elementary School 14 Limo Kaum Batusangkar. The population in this study were all students at Elementary School 14 Limo Kaum Batusangkar totaling 159 people. The sampling in this study used the Proportional Stratified Random Sampling technique, so that the sample in this study amounted to 32 people. The data collection technique was using the 2nd edition of the Test Of Gross Motor Development or TGMD-2. The data analysis technique used descriptive analysis techniques. Based on the research that the researcher has conducted, it can be concluded that the Control Object Ability Profile of Students Aged 7-9 Years at State Elementary School 14 Limo Kaum Batusangkar has an average of 16.19 or 31% who have object control abilities or are in the "less" classification.

According to a UNESCO report, more than 80% of industrial wastewater containing hazardous substances is discharged without treatment. This research aims to understand the implementation of Permen LHK Number 6 of 2021 in the management of hazardous waste at PT Bina Guna Kimia and the role of the Semarang Regency Environmental Agency (DLH). The research uses a descriptive qualitative approach with empirical juridical methods. Data were obtained through observation, interviews, documentation, and literature studies, and validated by source triangulation and analyzed qualitatively. The results showed that PT Bina Guna Kimia has implemented Permen LHK No. 6 of 2021 well, although there are still challenges such as the lack of understanding of employees about waste classification. The B3 waste management system in this company is quite effective with strict procedures in identification, storage, transportation, recording through logbooks, and real-time monitoring through the SIMPEL application. The company also regularly conducts training and works with certified vendors. DLH Semarang Regency plays an active role through supervision, socialization, compliance audits, coaching, and education to businesses to increase environmental awareness and compliance. This study suggests that DLH and PT Bina Guna Kimia improve education and training programs, and encourage industry players to seek alternative funding for the implementation of environmentally friendly technology. In addition, collaboration between stakeholders needs to be improved to create effective and sustainable hazardous waste management.

This paper provides a comprehensive examination of the concept and implementation of skill management as a cohesive set of competencies encompassing technical, interpersonal, conceptual, and strategic skills within organizational and entrepreneurial contexts. The background highlights the critical role of skill management in addressing the challenges posed by a highly competitive and rapidly evolving business environment, where mastery of these competencies determines both individual and organizational effectiveness in planning, organizing, leading, and controlling resources to achieve collective objectives. Grounded in a literature review of seminal works by Robbins & Coulter, Katz, Drucker, Mintzberg, Armstrong, and Barney & Hesterly, this study adopts a structured approach that covers definitions, classification of skill types, their roles in organizations, development strategies, implementation challenges, and applications in entrepreneurship. The findings indicate that: (1) technical, human, and conceptual skills are complementary across different managerial levels; (2) skill development requires a blend of formal education, field practice, mentorship, and technology utilization; (3) primary challenges include technological adaptation, complexity of decision-making, and limitations in training resources; and (4) in entrepreneurial ventures, effective skill management is fundamental to planning, finance, human resources, innovation, and communication. In conclusion, skill management should not be viewed as a static competency but as a strategic asset that must be continuously enhanced through lifelong learning, enabling both individuals and organizations to sustain growth and resilience in the era of globalization and digital transformation.

Safety is mandatory aspect that must be considered in maritime transportation, the result of an incident or ship accident due to negligence in safety aspects will have a big impact on several aspects, namely the ship itself, the environment, industry, human life, and also other shipping activities. Sea conditions that are not easy to predict mean that all components in the voyage, such as the captain, crew, and the ship itself need to be ready for any conditions during the voyage. In order to support the safety and operation of ships, of course, ship safety equipment must be supported by good maintenance supported by a maintenance planning system or what is usually called a Planned Maintenance System (PMS) on each ship. Planned Maintenance System (PMS) is a paper and software-based system that allows ship owners or operators to carry out ship maintenance within a certain period of time based on the requirements of the manufacturer and ship classification bureau. Ship maintenance and maintenance are very important to maintain the condition of the ship so that it is seaworthy, increase ship productivity and extend the service life of the ship, which ultimately aims at nothing other than ship safety

The rapid evolution of industrial robotics has been significantly influenced by the integration of computational data and social media, enabling robots to become more adaptive and responsive in collaborative work environments. This study investigates the role of social media and computational data in enhancing the adaptability of industrial robotics through machine learning techniques. By integrating sentiment analysis from social media with sensor data from industrial robots, this study examines how real-time data functions can improve robot decision-making and human-robot collaboration. Experimental results show a 23% increase in operational efficiency, an 89% accuracy rate in social interaction classification, and a 15% reduction in prediction errors. Furthermore, 62% of public sentiment toward adaptive robots is positive, highlighting the growing acceptance despite concerns over the impact of automation on jobs. These findings suggest that leveraging social media and computational data can significantly enhance the adaptability of robots, leading to a more efficient and socially conscious industrial ecosystem.

The rapid development of financial technology (fintech), particularly digital wallet applications like OVO, has significantly transformed transaction patterns in society. However, issues such as server instability and unsatisfactory user experiences frequently emerge on social media platforms. This study aims to analyze user sentiments toward OVO on platform X (formerly Twitter) by comparing the performance of two machine learning algorithms: Naïve Bayes and Support Vector Machine (SVM). Data were collected through web scraping from 1,000 Indonesian-language tweets containing the keyword "OVO." The research methodology included text preprocessing (data cleaning, tokenization, stopword removal), feature extraction using TF-IDF, and sentiment classification (positive, negative, neutral). Evaluation results demonstrated that SVM achieved the highest accuracy of 85.2%, while Naïve Bayes reached 78.5%. SVM also outperformed in precision (87%) and recall (83%) due to its ability to handle non-linear data. These findings provide actionable recommendations for OVO developers to enhance server stability and features based on user feedback. Additionally, this study serves as a reference for future sentiment analysis research employing algorithmic comparisons.

This study aims to examine the kinship between the Sabu, Sumba, and Rote languages, which are regional languages spoken in East Nusa Tenggara, Indonesia. Geographically, these three languages are spoken in different areas, originating from three distinct islands, with each having its own unique linguistic characteristics. Based on linguistic classification, the Rote and Sabu languages belong to the Ambon–Timor subgroup, while the Sumba language is classified under the Bima–Sumbawa subgroup. Despite these differences, there are noticeable signs of linguistic kinship, including cultural elements such as similarities in the clan naming system, which suggests a potential historical connection among these languages. To investigate this further, the research gathered data from native speakers of the three languages, who provided verbal samples that were transcribed phonetically. Lexicostatistics was then applied to analyze the vocabulary and determine the percentage of kinship between the languages. This method involves comparing common words in each language and quantifying the level of similarity. The findings of this study are expected to contribute to a clearer understanding of the linguistic relationships between Sabu, Sumba, and Rote. The results will offer insights into whether these languages share a common ancestral root or if their similarities are due to cultural exchange and contact over time. This research also aims to highlight the importance of preserving these regional languages, as understanding their kinship could play a role in the revitalization of linguistic heritage in East Nusa Tenggara. The study's results are anticipated to enrich the field of comparative linguistics, particularly in relation to the Austronesian language family, and provide valuable information for future studies on language development in Indonesia.

 A brand is one of the most valuable intellectual assets in the business sector, serving not only as a product identity but also as a reflection of reputation and quality. However, the increasing phenomenon of brand infringement indicates the urgent need for stronger and more effective legal protection. Brand infringement brings various negative consequences, including loss of consumer trust, unfair competition, and significant financial losses for brand owners. This study aims to analyze brand infringement from a criminological perspective, identify causal factors, and evaluate the role of law in addressing such violations. The research employs normative legal methods through analysis of statutory regulations, legal and criminological theories, and a literature-based approach using secondary data obtained from books, journals, and legal documents. The findings reveal that criminology provides relevant insights through theories such as Rational Choice Theory, which explains that perpetrators calculate the risks and benefits before committing the violation, and Anomie Strain Theory, which highlights how the inability to achieve economic or social goals legally can drive individuals or groups to commit brand infringement. The classification of violations includes imitation, counterfeiting, misuse, and unlawful exploitation of brand rights. Several causal factors were identified, including weak legal supervision, limited enforcement, and the high consumer demand for cheaper counterfeit products. Furthermore, the study underlines the essential role of the criminal justice system in addressing brand infringement through the enforcement of criminal, civil, and administrative sanctions as regulated under Law Number 20 of 2016 on Trademarks and Geographical Indications. In conclusion, brand infringement is not merely a legal issue but also a criminological problem that requires comprehensive handling through effective law enforcement, stronger supervision, and increased public awareness to protect intellectual property and ensure fair business practices.

Handwritten digit recognition is one of the key challenges in the field of digital image processing and artificial intelligence, with significant potential in various applications such as automatic form input systems, handwritten data correction, and attendance systems based on handwriting. This study aims to develop a web-based information system capable of automatically recognizing handwritten digits using the K-Nearest Neighbors (KNN) classification method. The system is designed through several main stages, including image preprocessing (conversion to grayscale, thresholding, and image size normalization), feature extraction using the zoning technique, and classification using the KNN algorithm. This research utilizes the MNIST dataset, which contains thousands of handwritten digit images ranging from 0 to 9. The system is developed using the Google Colab platform, supported by Python libraries such as OpenCV, NumPy, and Scikit-learn. Test results show that the system can achieve an accuracy of over 90% at certain K values, indicating that the KNN method is quite effective and efficient in recognizing handwritten digit patterns. This system is expected to be applicable for various digitization needs of handwritten numbers in education, administration, and information technology sectors

Independent village status is the highest achievement in the classification of village development that shows strong social, economic and environmental resilience. Tanjung Harapan Village is the only village in Lingga Regency designated as an independent village in 2023. This study aims to analyze the capacity of the Tanjung Harapan Village Government in achieving this status using the organizational capacity theory of Horton et al. (2003), which emphasizes two main aspects, namely resources and management. This research uses a descriptive qualitative approach with data collection techniques through interviews, observation, and documentation. The results showed that in terms of resources, the village has adequate infrastructure and has begun to apply digital systems in administrative management, although there are still network constraints. In terms of management, the village head applies open leadership, involves the community in planning, and manages finances transparently. Capacity building of village officials is also carried out through training and periodic evaluations. In conclusion, the Tanjung Harapan Village Government has demonstrated adequate capacity to support the achievement of independent village status. However, there is a need to increase cross-sectoral cooperation and strengthen digital infrastructure to support the sustainability of village development.  

In Indonesia, housing design policies are increasingly adopting a human-centered approach, recognizing that a home is deeply connected to the preferences of its occupants. These preferences are highly personal and diverse. While housing design is becoming more tailored to the characteristics of residents, few designs take into account the profession of the homeowner as a basis for classification. This research was conducted through direct field observations and interviews with homeowners. It focused on houses owned by individuals from 10 different professional fields in Indonesia. The goal was to explore how different professions influence the design and organization of living spaces. The study revealed that a homeowner's profession significantly impacts home design. Key findings include the addition of specialized rooms based on hobbies or interests, spatial arrangements that reflect the owner’s priorities, and increasing adaptability in design to account for climate change. These observations highlight the importance of considering profession-specific needs in housing design. The results suggest that the existing Indonesian National Standards (SNI) for housing and settlements need to be updated. The current standards focus primarily on minimum space requirements, but they should be expanded to include factors related to the homeowner's profession, which significantly shape the character of the design. Integrating these factors would lead to more personalized, functional, and sustainable housing designs.

Case study research is one of the methodologies in qualitative research that seeks to investigate phenomena comprehensively in a real-world context. This paper provides a comprehensive discussion of case study research design, covering various aspects ranging from definitions and types to the steps involved in implementation. Various types of case studies are explained based on expert opinions, including intrinsic, instrumental, and collective case studies, along with classifications of explanatory, exploratory, descriptive, and others. Furthermore, the systematic phases involved in conducting case study research are detailed, including problem formulation, data collection and analysis, and reporting of results. Focus on the use of triangulation techniques and contextual approaches are essential to ensure the validity of findings. By gaining an in-depth understanding of this design, it is hoped that students and researchers will be able to design case studies appropriately and make significant scientific contributions.                                                                                                                                            

This study examines expressive speech acts in the comments section of One Direction’s YouTube video titled “10 Years of One Direction.” It aims to identify the types of expressive acts used, explore their communicative purposes, and determine which type is most frequently employed. The research uses Searle and Vanderveken’s (1985) classification—which includes acts such as thanking, apologizing, congratulating, praising, sorrowing, boasting, blaming, and greeting—and Leech’s (2014) categorization of speech act functions (competitive, convivial, collaborative, and conflictive). Using a descriptive qualitative approach supported by basic quantitative analysis, the study analyzes 70 selected comments from the video. Results show eight types of expressive speech acts: thanking, congratulating, praising, sorrowing, blaming, happiness, boasting, and regretting. These acts mostly serve convivial, collaborative, and conflictive functions. Notably, sorrowing was the most frequent, appearing in 28.57% of the comments, indicating a strong nostalgic and emotional response among fans. The findings highlight how digital fan communities use expressive language to share emotions and build collective memories.

As the primary raw material for sugar and ethanol production, sugarcane is a highly significant plantation commodity. However, its relatively long growing period of approximately one year makes it more susceptible to diseases. Machine learning technology has been applied in the identification of sugarcane leaves, including through pre-processing methods and the development of disease classification models using Convolutional Neural Network (CNN) and Support Vector Machine (SVM) approaches. However, these methods exhibit limitations in terms of accuracy. Therefore, improving identification accuracy using VGG-16 is essential. The objective of this study is to enhance the accuracy of sugarcane leaf disease identification by utilizing VGG-16. The dataset consists of  2,521 sugarcane leaf images categorized into five classes. The results of this study indicate an accuracy improvement from 97.78% to 99.14%, reflecting an increase of 1.36%

Letter management is one of the important aspects in supporting the efficiency of academic administration in schools. This study aims to explore and understand how letter management at SMA Al-Hidayah Medan can be optimized to improve the efficiency of academic administration. The study used a descriptive qualitative approach with data collection through direct observation and interviews with parties involved in the correspondence administration process. The research findings show that SMA Al-Hidayah Medan implements a combined letter management system, namely combining manual and digital management. Incoming and outgoing letters are recorded manually in the agenda book and expedition book, and archived digitally in the school computer system. However, the system used is still limited and has not been fully integrated. The obstacles found include limited human resources who have not fully mastered administration and information technology, weak document supervision, and archiving of physical letters that have not been systematically arranged. In addition, digital archiving which is still conventional without automatic categorization makes the archive search process less efficient. As an optimization effort, the school has implemented a semi-digital system, provided training for administrative staff, compiled letter classification codes, compiled SOPs for letter management, and utilized cloud storage and digitization of old archives. These steps demonstrate institutional awareness to build a more efficient and modern administration system. In conclusion, effective letter management plays a very important role in supporting academic administration, but requires continuous coaching, better digital integration, and strong managerial commitment.