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Language errors in public spaces are still frequently found in various media, such as signboards, banners, billboards, and posters. This phenomenon not only indicates a deviation from standard Indonesian language rules but also has the potential to influence how people understand and use language. This study aims to describe the forms of language errors in public spaces, analyze them from a critical linguistic perspective, and identify their implications for public literacy. The method used is descriptive qualitative research with a critical linguistic analysis approach. Data in the form of examples of language use in public spaces are analyzed based on aspects of spelling, diction, and sentence structure, then interpreted in relation to the social practices and ideologies that underlie them. The results of the study indicate that the dominant language errors include spelling errors, inappropriate word choice, and the use of ineffective sentence structures. From a critical linguistic perspective, these errors are not only caused by a lack of mastery of language rules but are also influenced by social habits, the reproduction of deviant language practices, and the tendency to use foreign languages ​​to construct a certain image. These findings indicate that repeated exposure to language that does not conform to rules can affect the quality of public literacy. Therefore, it is necessary to strengthen critical literacy and increase language awareness so that society is able to use and evaluate language more appropriately and responsibly.

The rapid advancement of information and communication technology has increased the need for data security and confidentiality in digital information exchange. Various threats, such as eavesdropping, data theft, and information manipulation, require effective security methods capable of protecting message content without attracting unauthorized attention. One of the techniques used to address this issue is steganography, which conceals secret information within digital media so that the existence of the message remains undetectable. This study aims to implement the Least Significant Bit (LSB) method on digital facial images as a medium for embedding secret messages and to evaluate the quality of the resulting stego images. The system was developed using the Python programming language with a Tkinter-based graphical user interface to facilitate the processes of message embedding and extraction. Prior to embedding, the secret message was secured using an XOR encryption operation with a specific key. The embedding process was performed by modifying the least significant bits of image pixels, resulting in minimal visual distortion. Experimental results indicate that the LSB method successfully conceals secret messages while maintaining the visual quality of the cover image. The evaluation produced low Mean Squared Error (MSE) values and Peak Signal-to-Noise Ratio (PSNR) values exceeding 85 dB, indicating a very high similarity between the original and stego images. Furthermore, the hidden message could be accurately extracted using the correct key, provided that the image had not undergone compression or manipulation. Therefore, the LSB-based steganography approach on digital facial images is proven to be an effective method for enhancing information security and confidentiality.

The aim of this study is to describe the ineffectiveness of sentences in reports on celebrity infidelity in the DetikHot section of the Detik.com online media. The study uses a qualitative approach with a descriptive method because it focuses on analysing linguistic phenomena in news texts. The data source for the study was the sentences in the news articles about celebrity infidelity, which were selected using the purposive sampling technique. Data were collected using the documentation method by reading, noting and classifying data based on the criteria for effective sentences. Data analysis was conducted through the stages of data reduction, data presentation, and conclusion drawing. The results of the study show that there is still a lot of ineffective language use in DetikHot reports, such as wordiness in the phrase 'Masalah yang menyeret nama selebgram Azizah Salsha masih terus bergulir', unclear sentence structure in the phrase 'demi pengakuan suami selingkuh', and the use of non-standard words in the phrase 'bikin heboh'. It was also found that there was the use of illogical sentences and the incorrect choice of words, which caused the information to become ambiguous and less effective. The most common errors were wordiness and unclear sentence structure. This study shows that the quality of journalistic language in online media still needs to be improved to ensure that the information conveyed is clearer, more concise, logical, and easier for readers to understand.  

The advancement of information technology has driven higher education institutions to manage their digital presence professionally, particularly through quality website management as a representation of institutional identity. Preliminary observations of the Universitas Graha Karya (UGK) website (ugk.ac.id) identified several issues, including inconsistent page layouts, inactive hyperlinks, and irregularly updated content. This study aims to analyze the quality of the UGK website based on three WebQual 4.0 dimensions—usability, information quality, and service interaction quality—and to determine improvement priorities using Importance Performance Analysis (IPA). A descriptive quantitative approach was employed, with data collected through questionnaires distributed to 308 active students selected via purposive sampling using the Slovin formula at a 5% margin of error. Data analysis included validity testing, reliability testing, WebQual 4.0 analysis, gap analysis, and IPA Cartesian diagram mapping. Results indicate negative grand mean gap values across all dimensions, with service interaction quality recording the largest gap (-0.16), followed by information quality and usability (both -0.01). IPA mapping identified five indicators in Quadrant I as the main improvement priorities: ease of menu navigation (U2), relevance of academic information (IQ2), clarity of information language (IQ4), website access security (SI1), and ease of contacting administrators (SI4). The study concludes that UGK's website quality has not fully met user expectations and requires structured, user-oriented improvements.

This study was motivated by the widespread use of Indonesian language that does not conform to standard linguistic rules in Instagram content created by adolescents aged 17–20 years. As a social media platform that emphasizes speed and self-expression, Instagram encourages users to employ slang, nonstandard abbreviations, code-mixing, and various other forms of language deviation. This study aims to analyze the forms of Indonesian language errors found in adolescents’ Instagram content and to identify the factors contributing to these errors. The research employed a descriptive qualitative approach using content analysis. Data were collected through questionnaires distributed to 37 respondents and through an analysis of their language use habits on Instagram. The findings reveal that the most dominant forms of language errors include letter repetition to emphasize emotion (78.3%), nonstandard abbreviations (56.7%), code-mixing between Indonesian and foreign languages (45.9%), and the use of slang (45.9%). The main factors influencing the use of nonstandard language are the desire to appear relaxed and informal (86.5%), the need for fast and practical communication (67.6%), and the influence of peer groups and social media trends. Nevertheless, most respondents are aware that these habits may negatively affect their formal language skills. This study highlights the importance of digital language literacy to help adolescents use Indonesian appropriately according to different communication contexts.

Marriage confirmation services are often hampered by manual procedures, leading to delays and administrative errors. This study aims to design and implement a web-based Marriage Confirmation Information System to facilitate registration, document uploads, and online monitoring of verification status and court schedules. The system was developed using the PHP programming language and MySQL database using the Waterfall method, encompassing analysis, design, implementation, and testing. The results show that the system is capable of optimally performing all managerial functions, from document validation to report automation. Black Box testing confirmed that all features functioned as expected and were easy to use. In addition to improving bureaucratic efficiency, the system ensures data security through login encryption and provides transparency through real-time status tracking. The presence of this platform significantly saves time and transportation costs for the public, as bureaucratic processes can be monitored from anywhere. In conclusion, this system successfully supports the digitalization of public services and improves the quality of administration within the Office of Religious Affairs (KUA) and Religious Courts, thereby realizing more effective, efficient, accountable, and modern governance for all levels of society

Nahwu (Arabic grammar) is a fundamental discipline in learning the Arabic language, helping to prevent errors in speech and serving as a primary key to clearly understanding Islamic legal texts. However, in practice, the teaching of Nahwu often faces complex challenges, particularly the lack of active participation among female students and their uneven mastery of the subject. Therefore, this study aims to explore the problems in teaching Nahwu at Al-Madani Islamic Boarding School in Cikalong and to identify the factors causing these issues. This study aims to: (1) reveal the problems faced by second-grade female students of KMI in learning Nahwu at Al-Madani Islamic Boarding School in Cikalong, and (2) identify the contributing factors influencing the emergence of these problems. This research employs a descriptive qualitative approach. The researcher used three data collection techniques: classroom observation, in-depth interviews with the Nahwu teacher, and questionnaires distributed to the students. For data analysis, the researcher applied the Miles and Huberman model, which consists of data reduction, data display, and conclusion drawing. To ensure data validity, data triangulation techniques were used. The results of the study indicate that the problems are divided into two main aspects: (1) learning-related problems, including the gap between memorization of grammatical rules and their application (i‘rab), high levels of academic anxiety, and decreased classroom concentration; and (2) contributing factors, including methodological factors, linguistic-psychological factors, and classroom management factors. The researcher suggests that teachers adopt more interactive teaching methods and media, as well as innovative visual tools to reduce the abstract nature of Nahwu materials and enhance students’ functional understanding. Additionally, activating “Halaqah Nahwiyyah” (grammar study circles) in dormitories is recommended to overcome psychological barriers and improve students’ linguistic confidence.

Advances in information technology have brought significant changes to how Micro, Small, and Medium Enterprises (MSMEs) conduct their business operations, particularly in the areas of marketing and sales. However, Stretto Pizza MSME still relies on manual processes for ordering and transaction recording, which results in limited marketing reach, suboptimal data management, and an increased risk of errors in recording. This study aims to develop a web-based e-commerce information system that can integrate sales processes and data management more effectively. System development was conducted using the Waterfall method, which includes the stages of requirements analysis, design, implementation, testing, and maintenance. The system was built using the PHP programming language with MySQL database support. System testing was performed using the Black-Box Testing method to ensure that every feature functions according to user needs. The research results show that the designed system is capable of supporting product ordering processes, customer data management, sales transactions, and report generation more efficiently. With this system, it is hoped that the Stretto Piza SME can improve its operations while expanding its marketing reach through the use of digital technology.

This study implements the Damerau-Levenshtein algorithm for an Indonesian spelling checking and correction system based on the distance editing approach. The main objective of this study is to develop a system capable of automatically detecting and correcting spelling errors at the character level through a matching process against the KBBI dictionary and the Indonesian corpus. The methods used include data collection, text pre-processing, system design, and implementation of the Damerau-Levenshtein algorithm which includes insertion, deletion, substitution, and transposition operations. Testing was conducted using 25 test data consisting of standard words and modified words for typographical errors. The results show that the system is able to measure all test data with an accuracy level of 100% on a limited dataset. In addition, the average Damerau-Levenshtein Distance value of 0.84 indicates that most errors are in the light category. Evaluation using a confusion matrix produces precision, recall, and F1-score values ​​of 100% each. These results indicate that the Damerau-Levenshtein algorithm is effective in handling character-based spelling errors. However, the system still has limitations in handling complex semantic contexts and language variations. Therefore, further research is recommended to integrate language model-based approaches to improve the system's accuracy and generalization on real-world data.

This study aims to design and develop a web-based New Student Admission System (PPDB) Website at MIS Chairul Bariyyah Medan Krio to overcome the limitations of manual registration systems. The method used is Agile, as it supports iterative, flexible, and adaptive system development according to user needs. Data collection techniques include observation, interviews, literature study, and documentation. The system is developed using the Python programming language with the Django framework and MySQL database. The results show that the developed system improves the efficiency of the registration process, minimizes data recording errors, and facilitates real-time management of applicant data. In addition, the Website also serves as an information and promotional medium for the school that can be accessed anytime. Based on Blackbox testing and User Acceptance Test (UAT), the system is proven to run well and is easy to use. Therefore, this web-based PPDB system is effective in improving the quality of Administrative services at MIS Chairul Bariyyah.

With the advancement of technology, artificial intelligence tools have begun to emerge in the field of education, such as ChatGPT, which is now used by some teachers at Pondok Modern Darussalam Gontor to compare translations of Indonesian texts into Arabic. Although there are recognized reference books for correcting translations, there are discrepancies between machine translations, including errors in terminology selection and contradictions with the educational context. This raises questions about the accuracy of ChatGPT’s translations, making this study necessary to analyze and evaluate terminological errors. This study aims to analyze the translation errors made by ChatGPT when translating Indonesian articles into Arabic. This study also seeks to evaluate the quality of these translations based on the classification of terminological errors and Ali Al-Qasimi’s theory regarding the evaluation of terminology in terms of acceptance and rejection. This study employs a qualitative approach using content analysis, in which ChatGPT’s translations are compared with those in reference books, with reference to specialized Arabic dictionaries. Subsequently, the data was analyzed to identify error patterns and their acceptance levels within an educational context. The results indicate that translation errors can be classified into four main patterns: phonetic transfer, conceptual errors, semantic shifts, and inaccurate synonyms.

This study aims to identify and explain language errors in a scientific journal article entitled "Analysis of Language Errors in Expository Texts on the Digital Platform 'Ruangguru', August 2024 Edition as a Reading Resource for High School Students," published in the Semantik Journal, Issue 3, Number 4. The method applied in this study is descriptive qualitative using a literature study approach. For data collection, observation and recording techniques were used, while data analysis was carried out using the content analysis method. The findings of this study revealed 27 language errors divided into five categories, including 12 spelling errors (typos) (44.4%), 5 word choice errors (18.5%), 4 punctuation errors (14.8%), as well as ineffective sentence structure errors and errors in the bibliography (3 each) (11.1%). The causes of these errors include minimal editing process, inadequate understanding of PUEBI (Indonesian Standards for Ethics and Education), and inaccuracies from the author. This study shows that articles analyzing language errors still contain errors, so there is a need for improvements in the quality of editing by the author and the journal's editorial team.

This study investigates the use of oral corrective feedback (OCF) in English as a Foreign Language (EFL) classrooms among Indonesian university students, with a particular focus on lecturers’ preferences and students’ perceptions. The research addresses three main aspects: the types of errors that are corrected, the strategies of OCF employed, and the timing of feedback delivery. A qualitative case study design was adopted, involving classroom observations, semi-structured interviews with lecturers, and open-ended questionnaires distributed to students. Data from these instruments were analyzed separately and then triangulated to ensure credibility and validity. The findings reveal that lecturers mainly prioritize correcting phonological and grammatical errors, as these are perceived to directly influence students’ communicative competence and overall speaking performance. Among the six OCF types proposed by Lyster and Ranta (1997), recast and repetition emerged as the most frequently used strategies. These approaches were favored by lecturers as they corrected learners subtly while minimizing the risk of embarrassment and maintaining the flow of communication. Furthermore, lecturers applied both immediate and delayed feedback depending on the classroom context and learning objectives. From the students’ perspective, OCF was generally viewed positively, as it contributed to raising awareness of errors and fostering speaking improvement. Students particularly appreciated feedback strategies that respected their confidence and speaking flow. Overall, the study underscores the importance of aligning teacher practices with student preferences to maximize the effectiveness of oral corrective feedback in EFL learning contexts.

This study implements the Damerau-Levenshtein algorithm for an Indonesian spelling checking and correction system based on the distance editing approach. The main objective of this study is to develop a system capable of automatically detecting and correcting spelling errors at the character level through a matching process against the KBBI dictionary and the Indonesian corpus. The methods used include data collection, text pre-processing, system design, and implementation of the Damerau-Levenshtein algorithm which includes insertion, deletion, substitution, and transposition operations. Testing was conducted using 25 test data consisting of standard words and modified words for typographical errors. The results show that the system is able to measure all test data with an accuracy level of 100% on a limited dataset. In addition, the average Damerau-Levenshtein Distance value of 0.84 indicates that most errors are in the light category. Evaluation using a confusion matrix produces precision, recall, and F1-score values ​​of 100% each. These results indicate that the Damerau-Levenshtein algorithm is effective in handling character-based spelling errors. However, the system still has limitations in handling complex semantic contexts and language variations. Therefore, further research is recommended to integrate language model-based approaches to improve the system's accuracy and generalization on real-world data.

Fixed asset management is a crucial component in supporting the performance of local governments. However, the Polewali Mandar Regency Government still faces obstacles in managing assets conventionally, such as the risk of recording errors, duplicate data, and difficulties in field data verification which is time-consuming. This study aims to design and build a Web-Based Fixed Asset Management Information System integrated with Quick Response Code (QR Code) technology as a digital solution for real-time asset data collection, tracking, and monitoring. The approach taken for system development is known as the Waterfall approach, encompassing the phases of analyzing requirements, system design, execution, evaluation, and ongoing support. The creation of the system was carried out utilizing the PHP coding language, the MySQL database system, and Tailwind CSS to achieve a mobile-friendly interface. Data collection techniques were conducted through observation, interviews, and literature studies at the General Affairs Division of the Regional Secretariat of Polewali Mandar Regency. The result of this research is a fixed asset management information system featuring the generation of unique QR Code labels for each asset, category and location management, and reporting features divided into three access levels: Admin, Operator, and Verificator. Based on the system testing results, an average score of above 4.00 was obtained for indicators of ease of use (user-friendly), access speed, and information accuracy. In conclusion, the implementation of this QR Code-based system is proven to increase the efficiency of the asset identification process in the field, minimize manual input errors, and improve accountability in regional asset management in Polewali Mandar Regency.

This study aims to analyze news texts on the online news portal IDN Times. In addition, the study aims to identify various syntactic errors in the news texts on the portal, including non-standard sentence structures, the use of loanwords, ambiguous sentences, inappropriate diction, and low word efficiency, thereby providing an overview of the language quality and presentation of information in the online media. This research employs a qualitative descriptive approach, with a syntactic framework as the theoretical foundation. The researcher obtained data by reading several relevant references and recording information that could be used as data. Therefore, the reading and note-taking technique was used in this study. The data in this study consisted of news texts from the online news portal IDN Times, edition 2025. The data analysis method employed is the distributional method. The researcher analyzed the texts by identifying sentences that did not conform to syntactic rules and assessed the suitability of the texts as proper and accurate news texts. The results revealed various syntactic errors, including errors in sentence structure, diction, punctuation, sentence effectiveness, loanword usage, and conjunction usage. How ever, the findings indicate that although some syntactic errors were found, the news texts on the portal generally have a relatively good and coherent structure. Therefore, the texts can provide valuable insights into language use in the context of online media and serve as sources of information for studying language quality and effective communication in digital news writing.

Sanskrit verbs constitute a compelling object within linguistic research because of their semantic and structural complexity, which has not yet been widely explored. A proper understanding of Sanskrit verb usage can help prevent errors, especially among Hindus who use the language in cultural or religious contexts. Therefore, this research aims at analyzing the structure and semantic role of Sanskrit event verbs through the Natural Semantic Metalanguage approach. The data sources were from three chapters of the Bhagavad Gita (Chapters IX, X, and XI). The data were gathered using documentation and systematic note-taking techniques, and subsequently analyzed through qualitative methods by implementing the Natural Semantic Metalanguage approach conducted by Wierzbicka, supported by the semantic macroroles theory by van Valin and Lapolla. From this research, five Sanskrit event verbs were found in those chapters, namely cyavanti “to fall down”, pravartate “to develop”, vepamānaḥ “to tremble”, abhivijvalanti “to blaze”, and pratapanti “burns”. Further analysis showed that these event verbs can be classified into MOVE and HAPPEN types. In addition, the semantic macroroles of the Sanskrit event verb arguments found can be identified in the form of AGENT, PATIENT, EXPERIENCER, SOURCE, and THEME.

This study investigates the role of artificial intelligence (AI) in enhancing language learning, with a focus on five key applications: automatic text analysis, personalized learning, adaptive feedback, language error detection, and automatic translation. The study addresses the challenge of integrating AI effectively in educational contexts while balancing technological potential with pedagogical guidance. The objective is to provide a comprehensive understanding of how AI tools contribute to more adaptive, efficient, and engaging language learning experiences. A systematic literature review method was employed, selecting and critically analyzing studies published between 2020 and 2025 that examined AI-assisted language learning strategies. The findings indicate that automatic text analysis supports comprehension monitoring and guided learning, while personalized learning adapts content to individual learner needs, enhancing motivation and retention. Adaptive feedback delivers immediate, targeted guidance that fosters accuracy and self-regulated learning, and language error detection tools enable learners to identify and correct grammatical and lexical mistakes, promoting metalinguistic awareness. Automatic translation broadens access to authentic texts and cross-cultural materials, supporting comprehension and independent learning. Synthesizing these findings highlights the transformative potential of AI to improve learning outcomes while also revealing challenges such as tool reliability, ethical considerations, and the need for teacher oversight. The study concludes that AI, when thoughtfully integrated, complements instruction, enhances learner engagement, and supports differentiated and data-driven teaching strategies, providing valuable insights for language educators and guiding future research on AI-enabled language learning.

Public Relations (PR) of the State Islamic University of North Sumatra (UINSU) is a strategic unit that manages various important documents in the institution's administrative and communication activities. However, document loan management in this unit is still done manually, making it vulnerable to data loss, late returns, and difficulty in monitoring document status. This community service research aims to design and implement an integrated web-based document loan information system in the UINSU Public Relations sector. The system was developed using the PHP programming language with a MySQL database, implementing a modern, responsive interface. The system's main features include item/document data management, loan and return recording, and real-time stock monitoring. The results of the community service show that the system is able to improve document management efficiency, reduce recording errors, and make it easier for officers to monitor loan status. This system is expected to become a document asset management model that can be adopted by other units within the UINSU environment.

Language is a means of communication between individuals and groups to convey ideas, concepts, or insights. Language can be expressed orally or in writing. Spoken language is temporary or contemporary, while written language is permanent. Spoken language is delivered without an intermediary media, whereas writing serves as an academic archive to ensure that the conveyed insights are preserved. Therefore, writing is done, for example, in encyclopedias, which contain collections of information about science, knowledge, history, arts, technology, and others in a broad and easily understandable manner. Writing books is very important in delivering accurate and easily understood information, so the use of language must adhere to linguistic rules. However, errors are often found that can disrupt clarity and accuracy of information. This research aims to identify types of sentence errors in the encyclopedia book titled “Islamic Kingdoms in Indonesia.” The study examines the use of language in accordance with linguistic rules using a qualitative method and a descriptive approach, analyzing data from various chapters in the book in depth. The results show errors in sentence structure, punctuation, and incorrect terminology, which can reduce the quality of the information. The benefit of this research is to provide recommendations for writers and publishers to improve the encyclopedia so that it becomes more informative and easier to understand, as well as to enhance the quality of scholarly works in the field of historiography.